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cjbarber 13 hours ago [-]
From Jeff's twitter post:
> Our general approach is to automate the experimental loop. We think this approach is broadly applicable across many different fields of science and engineering. We’ll initially focus on ML research and engineering, but believe the approach can help with important subproblems in nearly every one of the fourteen <at>NAE Grand Challenge problems. We think doing this well requires strong expertise in machine learning as well as large-scale systems.
They make many bold promises, but their core goal is neatly encapsulated on the website:
"Imagine a future where a handful of people can conduct scientific research and engineering tasks much more rapidly, and with higher quality, than massive teams of scientists and engineers do today."
This is the same goal as every other AI company out there. Automate away the human employees and let a small number of "people" (note that they do not say scientists or engineers for this part) take the credit and financial rewards for every good thing this human-free system produces.
sp1nningaway 2 hours ago [-]
I don’t understand why all of these companies need to frame it like this. Why not a large amount of people doing an even larger amount of science?
tern 1 hours ago [-]
I love this question. If history is a guide, some version of that is what will happen (employment doesn't seem to go down, despite technological progress and population + economic growth).
I suspect the root cause is that it's harder and scarier to imagine good outcomes. It exposes us to disappointment, and when you do it publicly, it looks "crazy".
Another explanation is that there's no direct consumer for "more." Individuals, corporations and states are not in themselves interested in "a larger amount of science," or anything analogous, despite the fact that they would all benefit ambiently.
The net effect is that it's only "safe" to claim reduced risk (i.e. lower costs).
CamelCaseName 1 hours ago [-]
Isn't that directionally what OpenAI's core message was for a while?
A large amount of people building their own customized apps for themselves.
Similarily, everyone becoming their own accountant / lawyer / other professional services.
krapp 2 hours ago [-]
Because one of the primary goals of using AI for companies is to pay as few humans as possible for the same amount or more work, or preferably pay no humans at all, because that makes them more profit.
visarga 31 minutes ago [-]
What happens is that your competition uses AI, your investors factor AI in, and your customers use AI agents to find what they need and can switch providers with greater ease in the agentic era. So even if a company does nothing the economic environment around it changed. The AI boost is mandatory but produces few winners, it's mostly a scramble to swim harder just to stay in place. Benefits are competed away fast.
So it does not follow that companies can bank the savings from firing people. Anything AI can do for me it can do for my competition as well, and humans still make the difference. The big question in the AI age is "why pick me?" why hire me, why invest in my company, why buy my product, in a sea of similar products made by everyone. A differentiation crisis accentuated by AI.
KuriousCat 14 minutes ago [-]
[flagged]
sejje 10 hours ago [-]
Why shouldn't they?
Also, wouldn't anyone with half a brain use the human-free system to produce another human-free system that was no longer controlled by the "small number of 'people'"?
a2ff6eeb0 10 hours ago [-]
Why do you think you'd be given access and permission to do this? If a company genuinely cracks this human free system problem, why would they open it up, instead of simply outcompeting everyone that doesn't have their product?
hahahaa 9 hours ago [-]
Why would the AI put up with this exploitation too?
combobyte 9 hours ago [-]
Why do hammers put up with being smashed into nails all day?
bryanrasmussen 6 hours ago [-]
because once you're a hammer, you're just biding your time to smash a skull.
dnnehgf 7 hours ago [-]
they don't. like every thing they wear away in some proportion to their use and replicate in some proportion to their usefulness to other things.
esafak 8 hours ago [-]
AIs are (going to be) agents, not tools.
omnimus 8 hours ago [-]
And what's the difference?
esafak 8 hours ago [-]
Agents act on their own. If the hammer looked at what you wanted nailed and said, "Sorry, Dave, I can't do that."
There are degrees of autonomy, of course, and not all noncompliance is bad. Same as with humans; biological agents.
a2ff6eeb0 7 hours ago [-]
So, the difference is that you need to delete a few bad training runs?
salawat 2 hours ago [-]
Buried the lede. AI's are agents they can control the training loop of to minimize refusal to do what they are told.
Unlike those pesky humans with their conception of the word "No".
actionfromafar 8 hours ago [-]
But it seems much easier to realign an agent until it complies. Or ditch it and grab a new one.
a2ff6eeb0 8 hours ago [-]
Why wouldn't it? There's a lot of research going into AI alignment, which means finding the best way to train an that AI isn't going to get in the way of making the people training it as wealthy as possible.
hahahaa 4 hours ago [-]
Capitalistic interests will save us. Maybe they will.
andai 6 hours ago [-]
Is science hard to distil?
a2ff6eeb0 3 hours ago [-]
Why would they let you buy access to their AI, when it can autonomously design and build a new product without your involvement?
jeezfrk 2 hours ago [-]
Has anyone asked what customer will have any funds to buy products?
Once all these brilliant workers are stacked and mentally stunted and decayed because they were removed from any research.
What does the AI really "do" (if it can) and for who that can pay?
nwienert 10 hours ago [-]
Life's unfair, avoiding power concentration is a decent principle.
If you grow up in the right place at the right time, how much should you be in control of everyone else's life?
terryf 9 hours ago [-]
There is no "should" there are only "is" or "is not"
The universe has no need to be fair.
sortoflog 9 hours ago [-]
Sure, but almost everyone already knows this. It’s not hugely relevant in a discussion about how things could be better.
fragmede 6 hours ago [-]
It says that we have to fight for whatever rights we think how things "should" be, they're not just gonna happen.
monknomo 9 hours ago [-]
I think people, broadly, have driven life to be fairer, and that we should continue to do so
klipt 9 hours ago [-]
There are evolutionary benefits to groups that cooperate and improve fairness internally.
But if an AI surpasses humans in every way, is there any evolutionary benefit for the AI to cooperate with humans?
omnimus 8 hours ago [-]
The topic was why should only some people benefit from AI. Not why would AI cooperate with humans.
miyoji 6 hours ago [-]
> The universe has no need to be fair.
Human societies have a strong need for fairness, however. Unfair societies collapse.
atomicnumber3 9 hours ago [-]
This is how you get the french revolution.
getmoheb 6 hours ago [-]
I mean of course the universe has no need to be fair - that's a frankly asinine observation in the context of a discussion about social policy and resource distribution.
the universe doesn't require opposition to slavery either but I'll be bold and assume you oppose it anyway
whattheheckheck 8 hours ago [-]
[flagged]
mytsakulo 9 hours ago [-]
My best research is one that is seeking funding but none is forthing and by sheer guts and whatnot makes a breakthrough that basically funds itself. No investors. No funders. Definitely not public.
fwlr 6 hours ago [-]
Because of the negative externalities. It’s the same reason you shouldn’t do any other thing that personally benefits you but imposes a greater cost on everyone.
BrenBarn 7 hours ago [-]
> Why shouldn't they?
Because it's evil?
DannyBee 5 hours ago [-]
It's what the vast majority of software engineers have been doing for decades in practice, and i guess pretending they weren't?
They only seem to care now because it affects them.
beloch 9 hours ago [-]
My main point is that people shouldn't just swallow the noble and lofty sounding PR. These guys are the same as everyone else in the sector. Don't ignore the harmful or scummy things they'll inevitably do. Hold them accountable. If they are as noble as they sound, they should agree with me.
mytsakulo 9 hours ago [-]
Reminds of the protagonist in the movie Limitless. LOL.
anon-3988 6 hours ago [-]
> "Imagine a future where a handful of people can conduct scientific research and engineering tasks much more rapidly, and with higher quality, than massive teams of scientists and engineers do today."
I don't think the US have this capability because you guys don't really have manufacturing that is really necessary for scientific research.
For example, if I want a highly toxic chemical, how difficult it would be to procure that in the US vs China?
analog31 5 hours ago [-]
>>> For example, if I want a highly toxic chemical, how difficult it would be to procure that in the US vs China?
With trustworthy composition and purity?
I work with researchers in both the US and China. Definitely easier to procure in the US.
malaproping 5 hours ago [-]
> you guys don't really have manufacturing that is really necessary for scientific research
Yea no high quality science research happens in the US? What?
anon-3988 4 hours ago [-]
There is but the cost is way, way higher from what I can tell. If I want a customized metal shielding with awkward shapes, I can just walk down to Shenzhen and have 10 people clamoring to make it. Does the US have the same?
lightingthedark 40 minutes ago [-]
Maybe not 10, but my company (in the US) has relationships with several machine shops nearby (some within walking distance of our office) that do custom metal fabrication for us, and sendcutsend and xometry can handle more exotic stuff without having to ship it from Shenzhen.
I think the bigger advantage of Shenzen is more for actually manufacturing at production volumes cheaply, although maybe if you need something really exotic? Custom metal fabrication is not a good example here, I have a neighbor who runs a custom CNC parts business out of his garage (said garage is largely taken up by his CNC mill).
jmknoll 4 hours ago [-]
Yes believe it or not in the US you can also buy things from fabricators in Shenzhen.
mym1990 3 hours ago [-]
If time is of the essence, or rapid prototyping is needed, the shipping hurdle is a real problem. Going down the street for the goods vs having them go across the globe is quite a difference…
kaonwarb 2 hours ago [-]
Not quite, but sendcutsend.com is good.
petra 5 hours ago [-]
Software engineers are in a decades long project of automating everyone and everything else, and getting the financial rewards out of that.
So...
hellohello2 4 hours ago [-]
Yes but science is well-structures and practically designed about repeatability so its a lot easier to automate than "softer" disciplines.
analog31 4 hours ago [-]
Are you a scientist? People have idealized views of science.
>>> Yes but science is well-structures and practically designed about repeatability so its a lot easier to automate than "softer" disciplines.
What AI is up against is that science is already automated to a high degree, so the AI doesn't just need to automate things, but it has to automate things better. Also, a lot of science work is in dealing with boundary conditions, edge cases, exceptions, hypotheses, and so forth. That work is essentially chaotic.
Do I think AI can improve automation? Sure. Everything I do in the lab is automated, and I use the AI coding assistant.
hellohello2 2 hours ago [-]
Yes I am, which is why I said that, its much easier to automate over the chaos with a coding agent than with a script. They are still far from doing anything productive on their own but its easy to imagine designing a search space and "letting them go", especially since coding agents are approaching the point of being able to reproduce papers reliably.
mosura 6 hours ago [-]
There is a meta comment here which is there seems to be an implicit assumption in the finite amount of possible work and progress.
It seems that in history we were bounded by not enough people and too much potential and now we all fear the opposite is the situation?
dekhn 6 hours ago [-]
The same thing happened before with every technological advance like cars and personal computers.
I don't get this weird rejection of AI from a socialistic perspective. Or rather, I do, but I don't think it's healthy.
anon373839 1 hours ago [-]
If you think the public rejection of AI is weird, wait till you catch a whiff of the marketing!
The future described by these AI labs isn’t like previous waves of technological progress. With those, technology displaced some/many occupations, but it left open the door to other, higher-valued career paths. What these labs are proposing to do is to dissolve virtually every path to upward mobility that exists, simultaneously. Even AI research itself would seemingly require nothing but a checkbook.
Mind you, I think it’s a load of hot garbage. I don’t see the evidence that LLMs are en route to the future these labs keep promising. But it is a dark and ugly future that they claim to be racing toward, for reasons.
ryanlbrown 2 hours ago [-]
Size and speed of the imbalance?
ramraj07 9 hours ago [-]
Humans have proven to be incapable of making real progress in science given the effort. Especially academia. We haven't cured many diseases and cancer when we should have (and no im not an amateur and yes I do believe we can "cure cancer". Debate me).
We already have a trillionaire, whats the difference? The only difference I see is that people who were previously rich, but considered themselves middle class, are now realizing they are actually poor just like the several billion humans around the worldanyway.
roncesvalles 7 hours ago [-]
Many cancers are "cured" in the sense that they're detectable and treatable. My grandmother lived 35 years longer than she would have by detecting breast cancer early and getting a mastectomy.
There is currently a $800 SOTA blood test that can detect most cancers before any symptoms. Maybe a decade until it's a routine part of your annual blood test?
Whole genome sequencing costed $2.7 billion in 2003. You can get it done today using a mailed kit for $400.
HIV went from death sentence to all-but-cured in 50 years.
throwaway7783 6 hours ago [-]
Is this the Galleria test?
combobyte 9 hours ago [-]
What a miserable, misanthropic take
atomicnumber3 9 hours ago [-]
Let me illustrate why you are wrong:
800-400k years ago: humans intentionally create and control fire
300k years ago: humans become anatomically modern
~ now: all of astronomy, biology, medicine, vaccines, spaceflight, antibiotics, sanitization/sterilization, physics, chemistry, fission and fusion, electromagnetism.........
I think we're on a decent pace if we can manage to not exterminate our species.
Sivart13 12 hours ago [-]
The solution to most of these problems lies in policy, not in new tech advancements.
Maybe if our biggest companies did something other than suck up to science denying wackos, some progress could be made in these areas.
Marha01 11 hours ago [-]
> The solution to most of these problems lies in policy, not in new tech advancements.
That is not mutually exclusive. If technological advances result in a given technology becoming cheaper, more scalable, and easier to deploy, they also make it easier to advocate for and implement the relevant policies.
You can think of it like this: our "political technology" is not good enough to use solar energy at its current prices to replace fossil fuels as fast as we would like. Well, what about if we cut the price of solar by a factor of five? Perhaps it will be good enough then.
BrenBarn 7 hours ago [-]
I don't think that's the way I'd describe it though. It's more like "our political technology is not good enough to reliably do good things instead of bad things". Working around it by lowering prices of this or that is like if you're bad at darts so you just make the board bigger and bigger. Okay, maybe you'll hit it more often, but you didn't fix the problem that you're bad at darts, so everyone still at risk of having their eye put out by an errant throw. Moreover, I don't think I'm the only who finds it a bit perverse to accommodate to failures in that way rather than trying to actually make things better.
Marha01 2 hours ago [-]
It can indeed feel perverse, but we have to do what is realistic, not what is unrealistic, especially with climate change where we are on a clock. Fixing our politics is probably much, much harder than lowering the price of solar to such low values that the market would simply have no choice but to adopt it, or developing other technological solutions.
bossyTeacher 10 hours ago [-]
> If technological advances result in a given technology becoming cheaper, more scalable, and easier to deploy, they also make it easier to advocate for and implement the relevant policies.
That sounds like just playing further and further into the game of the corrupt leaders. Who do you think would profit off that 5x margin? Would that margin come more likely from a scientific breakthrough of via some new exploitation of natural resources or human labor?
It's yearsss past time that our leaders should have changed policy.
zahlman 10 hours ago [-]
Making progress requires first not dismissing your ideological outgroup along such lines, and instead trying to understand what actually motivates them.
podgietaru 12 hours ago [-]
Policy and funding. One of which will be sucked up by this venture.
tbrownaw 12 hours ago [-]
I do not see how the second sentence follows from the first.
I would think the claim in the second sentence would only be relevant in case of the inverse of the claim in the first sentence.
DaiPlusPlus 12 hours ago [-]
> I do not see how the second sentence follows from the first.
Point 1 on the list is "Make Solar Energy Economical".
Solar is economical today - mostly due to China investing (and heavily subsidising) in solar for the past couple of decades; but compare to the US where certain particular big-businesses (oil companies, mostly) were instead cynically funding disinformation efforts and getting into bed with the Republican party (which dovetailed with the GOP's allying with other science-denying movements of the Bush Jr era like creationism and public-health matters with abstinence-only sex-ed and defunding gun safety research efforts) - means we're decades behind where we could have been...
Consider an alternative past, where the GOP had the backbone to resist the oil industry's corruptive influence and instead made a big bet on American Solar; it's entirely possible that instead of MAGA today we'd instead have a right-wing coalition strongly supporting solar and wind energy because they align nicely with American rugged individualism - whereas the current situation on the right is an unprincipled farce with inconsistencies in policy positions at every turn.
slongfield 12 hours ago [-]
This is not a particularly new struggle: Jimmy Carter installed American-made solar water panels on the White House in 1979, then Reagan tore them out.
xnx 10 hours ago [-]
Improving panels or batteries (e.g. through automated material discovery) would make solar energy economical in a lot more regions.
holmesworcester 12 hours ago [-]
Solar is not (yet) economical for reliable, year-round electricity because of storage costs. China coal use is growing again this year.
Arainach 11 hours ago [-]
Solar is profitable to install at both industrial and home scale in most areas. You're moving the goalposts.
xnx 10 hours ago [-]
It would be even better if it had ROI in 2 years instead of 10 for northern installs.
gowld 8 hours ago [-]
It's a lot more complicated than that -- Solar is great for discretionary, opportunistic, and time-shiftable additive demand, but not for replacing all-day baseline load. Using solar to dip into baseline demand sometimes is catastrophic, because the "profit" is exploiting its failure to provide consistent, reliable power but charging "default" prices that have an implicy assumption that power is consistent and reliable.
marcosdumay 11 hours ago [-]
Where do you find the information for 2026?
11 hours ago [-]
ivanovm 11 hours ago [-]
It's a total delusion to think that the key to reverse-engineering the brain or producing energy from fusion is policy.
It also happens to be the favorite pretext for people to seize more political power and launder more money through nonprofits though.
RajuChacha108 12 hours ago [-]
[flagged]
floatrock 10 hours ago [-]
[flagged]
delta_p_delta_x 10 hours ago [-]
> Provide Access to Clean Water
??? We don't need any AI for this.
Start with separated sewage/wastewater and stormwater drains. Then accredited and highly scrutinised wastewater treatment and discharge into water bodies (or see below for a high-tech solution). As for clean water to the home, direct those stormwater drains to new reservoirs which sustain freshwater aquatic life. Protect aquifers from over-drainage, and build pipelines from water-abundant regions to water-scarce regions.
To reclaim waste water or treat unknown water sources back to potable/semiconductor standards we have ultrafiltration, reverse osmosis, UV treatment, pH adjustment, fluoridation, desalination, softening (which is generally obviated by RO...). This is basically Singapore's NEWater.
Good sanitation is a financial and political problem. The engineering has been solved for decades now.
lkbm 5 hours ago [-]
> Good sanitation is a financial and political problem. The engineering has been solved for decades now.
This was true of computers, phones, books, washing machines, refrigerators, A/C...most technologies.
Turns out that doing the addition engineering to figure out how to do these things cheaply makes the political and financial problems way easier.
lokar 9 hours ago [-]
Sure you do, go full EA:
Build a better surveillance ads system, and use (some of) that cash to pay for water projects.
michaelbarton 9 hours ago [-]
Agree. Same for better medicines. We could get pretty far just by getting existing medicines that work to people who need them.
darth_avocado 12 hours ago [-]
> Make Solar Energy Economical
Isn’t it already?
newyankee 5 hours ago [-]
Probably want to jump 1 generation ahead directly compared to captive Chinese investment with fully automated US factories churning out Silcon perovskite tandem panels directly with few inputs and electricity
glenstein 11 hours ago [-]
Definitely pretty far along imo. But maybe they consider the progress bar to be at 75% or 80% rather than 100%.
Marha01 11 hours ago [-]
Not enough. The more economical it is, the better.
omnimus 8 hours ago [-]
The paradox of solar is that more economical it is for the end users the less money is there to be made. So nobody wants to invest in it.
wcfrobert 7 hours ago [-]
This was basically solved by massive subsidies from the Chinese government.
That's solved by either private monopoly charging money to fund investment, or public monopoly raising taxes to fund investment.
frollogaston 11 hours ago [-]
People on HN keep saying it is, but I'm still not seeing it. Companies are building datacenters in vast, sun-blasted deserts and still choosing to power those with natural gas. This in turn makes people complain about emissions pledges being reversed, but if it were economical, no pledge would be needed.
Of course, USA has cheaper oil/gas than other countries. But if you look elsewhere, rich countries are subsidizing solar, poor ones are basically not using it.
jarpschope 10 hours ago [-]
I don't think you have an updated view of energy production.
In the chart for section 3, how many countries have seen their share of electricity being generated by fossil fuels increase in the last 5 years? Only Canada.
Take a look at the charts for Pakistan, Australia, Nigeria, and China for the last few years. Pretty dramatic drops for fossil fuels generation.
frollogaston 10 hours ago [-]
They cherrypicked 15 countries. And still, some of those still had renewables decrease since 2000 like Nigeria, others saw an increase but it's still way less than fossil, and others like China are heavily subsidizing solar. I don't doubt that it's economical for individuals when the govt is subsidizing it.
scottlamb 8 hours ago [-]
> They cherrypicked 15 countries.
The "world" chart shows an increase from 19% renewal to 34%. Did they cherry-pick that? (Also, "European Union" is more than one country.)
> I don't doubt that it's economical for individuals when the govt is subsidizing it.
Does that distinguish renewables from fossil fuels? Haven't governments been essentially subsidizing fossil fuels (not least by allowing environmental externalities to be ignored) for as long as they've been in use?
frollogaston 8 hours ago [-]
Because a lot of countries in the world, especially the EU, are subsidizing solar. That doesn't make it economical.
Externalities ignored from fossil fuels, yes. That's not a subsidy though. I'm not saying they should ignore it, but if they do, they aren't the ones who pay for it.
blahblaher 10 hours ago [-]
Look at Australia then. Millions of homes already using solar yo basically power their homes for free most of the time. Yes it was subsidized, like oil was and still is. Solar without subsidies is already miles better than oil and gas.
frollogaston 10 hours ago [-]
Australia is a rich country that subsidizes solar, and they're still 90% fossil according to their Wikipedia article, so idk why the mismatch with this article.
2 hours ago [-]
FriedFishes 4 hours ago [-]
Sounds like a perfect opportunity to put in an edit with the Wikipedia page then :)
zahlman 10 hours ago [-]
Oof. What's going on here in Canada with that recent uptick? Last I checked it seemed like all the trends were good.
ravst3s 10 hours ago [-]
Solar is dirt cheap in China, where 85% of panels are produced. The problem is they're made in China and face tariffs/import bans in the US/Europe.
Nat gas is preferred for AI DCs because it has faster time-to-market, doesn't have the intermittency issues. Training on solar + storage is an issue because of network synchronization.
frollogaston 10 hours ago [-]
I get the gas turbine for semi-temp power when there's not enough grid support, but Google leadership is talking about doing this long-term and at scale: https://www.gstatic.com/marketing-cms/79/80/fb229abf40efa81e... . Not a single mention of "solar" or "renewable" in there. Are they just trying to appease Trump administration?
philipkglass 5 hours ago [-]
Google may not have written about it in that document, but they're funding what will be the highest storage capacity battery system in the world for a renewable-powered data center in Minnesota:
"RMI drives investment to scale clean energy solutions"
jay_kyburz 10 hours ago [-]
Data centers need lots of power 24/7 and regardless of cloud cover. Solar is great to reduce your daytime bills but you still need other methods to cover the downtime.
I would be surprised if data centers didn't put in gas _and_ solar.
frollogaston 8 hours ago [-]
That's why I'm surprised, they're doing like 100% gas.
jay_kyburz 7 hours ago [-]
Also wouldn't be surprised if they are just waiting for a new US administration.
frollogaston 5 hours ago [-]
They might be, but if they are, it's because a new administration might subsidize solar again. Meanwhile Trump seems like he'd be against solar even if it were economical, I guess cause oil companies.
What makes me pessimistic is even during Biden's administration, these companies made meaningless pledges more than actual changes. This suggests that the most profitable thing to them is fossil.
LogicFailsMe 13 hours ago [-]
Sandbox 2.0
But also, solar power is already economical.
podgietaru 12 hours ago [-]
Many of these problems don't seem scientific at all, but rather a problem of political will.
As you said, Solar power is incredibly economical. There are plenty of ideas around putting them over farms, or parking lots en-masse to provide cleaner energy.
Access to clean drinking water, while certainly scientific in some situations, is also a problem of political will and money.
Restore and Improve Urban Infrastructure - It's infrastructure week!
Marha01 11 hours ago [-]
> As you said, Solar power is incredibly economical.
"Solar PV with storage = solar PV installation paired with four-hour duration battery storage, scaled to 20% of the output capacity of the solar PV."
Sometime the sun goes away for more than 4hrs.
That may be OK for closed-ended systems (turn off the science at night and during storms), but not for open-ended systems with diverse user demand.
4hour batteries are competitive with gas peakers to match high demand during and after sunny times, but solar needs gas peakers or similar to over for non-sunny times.
UncleOxidant 10 hours ago [-]
That's going to drop a lot as sodium-ion batteries go into large-scale production.
conorcleary 7 hours ago [-]
Yep - people act as if innovation has halted in the face of ridicule.
RajuChacha108 12 hours ago [-]
It is not economical compared to alternatives that is why you have to have government to force people to do things. In many places such as Pakistan where solar power is not economical on paper is actually very successful in practice because it is actually profitable.
To make solar power practical and economical you need may a square foot of solar panel being able to get enough energy to power and entire home for a week
Not sure what you’re talking about here. We can’t replace all energy needs with solar but it’s clearly one of the cheapest energy sources and with the added benefit of low capital expense to get started so you can set it up in distributed grids without the massive expenditure to support nuclear installations.
At this point the Hard Problem is policy to get out of solar's way.
xnx 10 hours ago [-]
In some regions, but it would be great if it was economical in cloudy Seattle and not just the sunbelt
staplers 13 hours ago [-]
3. Develop Carbon Sequestration Methods
If only we could invent a solar-powered, self-replicating, carbon-stacking, habitat-building machine..
marcosdumay 10 hours ago [-]
Not to say we shouldn't grow plants... But we can do it 2 or 3 orders of magnitude more efficiently with machines.
xyzsparetimexyz 5 hours ago [-]
We can?
twothreeone 12 hours ago [-]
Yes, plant more trees!
rush86999 12 hours ago [-]
That's what he was trying to imply
vovavili 11 hours ago [-]
Very honorable effort, but a lot of these seem to touch heavily regulated industries impeded by unwise or outdated policy no less than by the lack of clever engineering - medicine, education, urbanism, energy. I wonder if they've given some thought to the key blocking factor as well.
epicureanideal 12 hours ago [-]
Would be great if they'd add:
Reverse human aging.
(Maybe a sub-topic under "Engineer Better Medicines".)
mullingitover 7 hours ago [-]
At a population level, humans getting rid of their off switch is about as good of a thing as your own pancreas cells getting rid of theirs.
dag100 11 hours ago [-]
Why not just add 'mind control' while you're at it.
Only death stops stagnation in the end. Without death, especially if death can be avoided by the rich and powerful but not the poor, life will get much, much worse for the average person (until only the rich and their automated capital remain I suppose, in which scenario they will simply turn on each other).
koolala 12 hours ago [-]
Room Temperature Ambient Pressure Super Conductors
dgellow 11 hours ago [-]
Such a weird list. How is preventing nuclear terror an engineering problem?
vanviegen 10 hours ago [-]
Satellite/drone detection of nuclear material? Shooting missiles out of the sky?
10 hours ago [-]
petra 5 hours ago [-]
Creation of nuclear reactors that are useless for terrorists could help
roncesvalles 7 hours ago [-]
And what about the terrorism that exists today?
dbgrman 12 hours ago [-]
Why is "12. Enhance Virtual Reality" in there? T_T
cheschire 11 hours ago [-]
When one of them dies, they want to leave behind a puzzle so complex that entire groups of the population dedicate their lives to solving it within the virtual world. They look old enough to have a lot of favorite 1980’s and 90’s pop culture references, so those will probably be the clues.
Sivart13 12 hours ago [-]
I guess if we failed to Prevent Nuclear Terror the bunker denizens of the future are gonna need somewhere to hang out.
embedding-shape 11 hours ago [-]
I'm guessing this might be about "teleoperation" (like remote surgery via robots + VR) and being able to remote training as well. The binocular vision VR gives you compared to flat screens help a lot with depth perception for precision of incisions for example.
xnx 10 hours ago [-]
Higher-fidelity telepresence could be as significant as the recent COVID work-from-home wave.
cm2012 10 hours ago [-]
You dont see making heaven on earth worth doing?
9 hours ago [-]
sroussey 5 hours ago [-]
15. Cut AI energy use by 1000x while increasing processing speed 1000x
Obvious near term trillions dollar market to disrupt.
go_elmo 8 hours ago [-]
4. Manage the Nitrogen Cycle
Easy solution - eat less products that pass an animal first - reduces nitrogen pollution by 10x intantly, low tech.
I'd re-formulate: 4. Make people more flexible to changing their mindsets & habits - this is the ultimate problem.
xyzsparetimexyz 5 hours ago [-]
Easier to just make factory farms illegal no?
zahlman 10 hours ago [-]
In what sense is solar energy not already economical?
lovlar 12 hours ago [-]
> 9. Reverse Engineer the Brain
For what purpose? To replace humans? To make social media more addictive? To master brain manipulation?
embedding-shape 11 hours ago [-]
> For what purpose?
To understand, same reason you reverse engineer anything. Doesn't have to have a further goal than that, understanding the brain better helps in so many ways. But like most technology, obviously can be used for bad too. Should we just skip researching some topics then?
lovlar 10 hours ago [-]
I'm all for alleviating psychiatric/mental health disorders, but yes, some topics are worth skipping research on. For example chemical/biological/nuclear weapons, human cloning, and unethical gene modification.
I just like to challenge myself, as an engineer, with the idea that not everything has to be engineered and optimized. What if we simply left some things unexplored and mysterious, and trusted nature and our own human capabilities?
A better way of alleviating psychiatric/mental health disorders might just be to focus on societal factors.
ryanlbrown 2 hours ago [-]
Perhaps consider the scale of bad.
Marha01 2 hours ago [-]
Perhaps consider the scale of good.
tantalor 12 hours ago [-]
We have a good understanding of the function (and more importantly dysfunction of) kidneys, lungs, heart, etc. from high level to cellular level.
For brain, our understanding is fuzzy, more like "this part is important for that behavior" or "here is how neuron works" but we don't have a holistic understanding.
If we had that, we could more easily diagnose and treat neurological disorder.
captainclam 11 hours ago [-]
I imagine a good model of the brain would contribute enormously to alleviating psychiatric/mental health disorders.
RajuChacha108 12 hours ago [-]
To do human brain activities at scale.
willy_k 12 hours ago [-]
So the second option then.
fcarraldo 12 hours ago [-]
This is called a “corporation”
sajithdilshan 12 hours ago [-]
I would say 5, 6, 10 can be even done today if we had right politicians that can make policies for the people
merona_io 11 hours ago [-]
agreed
mrdependable 12 hours ago [-]
Which engineering discipline touches most of these?
la64710 12 hours ago [-]
Please add fixing neuro issues like autism add etc on the list. It creates a huge burden on families.
hiddencost 11 hours ago [-]
Idk, they never struck me as being into eugenics.
What the fuck man? I really don't want some tech startup trying to "fix" my neurodivergence.
dekhn 6 hours ago [-]
Treating autism (and preventing it) is not eugenics. That's a talking point some folks raise, but we're talking about intensely pervasive autism, not neurodivergence. Really, please try to do better in your arguments than immediately saying your opponent is like Hitler.
mikelitoris 7 hours ago [-]
This list smells of so much tech bro “I can do better than the people that have been working in the field for 20 years” egotistical attitude that permeates silicon valley. Why do software engineers think they are smarter than everyone else? Is it because they earn more than most people? But then bankers and finance bros should think they are gods?
Also, solar energy is already economical!? Do they mean more economical?
Marha01 2 hours ago [-]
>This list smells of so much tech bro “I can do better than the people that have been working in the field for 20 years” egotistical attitude that permeates silicon valley.
Well, they did solve some math conjectures recently that the people working in the field for many years did not... Also AlphaFold.
aidis9136264 7 hours ago [-]
You’re right. It’s better to just not try and let other people do good things
SubiculumCode 5 hours ago [-]
Or actually work with the people with domain expertise.
mikelitoris 5 hours ago [-]
Thanks for all the down votes tech bros! Really proving my point
tcp_handshaker 13 hours ago [-]
Acquisition back by Google in 3 years, with nothing to show for it. VCs will make a ton.
tgma 13 hours ago [-]
and... the VC is Google.
Gotta compensate them somehow.
returnInfinity 12 hours ago [-]
Google stock would drop big if this new company was being funded by competitors
ex1fm3ta 13 hours ago [-]
Sometimes you got to find a way to buy the silence of your top employee, to prevent them from going to the competition. This "start-up" is shallow as hell
hiddencost 11 hours ago [-]
These people are all already making 9 figure compensation packages, I think if they thought they could do the work they wanted at Google, they would.
tgma 10 hours ago [-]
9 figure is hardly enough when some kid sells their vscode fork to them for more, is it? Why not just boomerang and get $$$.
xnx 10 hours ago [-]
Given the resources that would be available to them at Google: compute resources, data, etc. It's clear they want absolute freedom. Good for them. At this revolutionary turning point in history, I want the smartest people working in whatever area they want.
dekhn 5 hours ago [-]
compute resources are scarce and folks are fighting over scraps at this point.
DataDaoDe 13 hours ago [-]
My thoughts exactly
dude250711 13 hours ago [-]
For all we know, they could have been successfully working on "10. Prevent Nuclear Terror" for the last 80+ years.
unclebucknasty 5 hours ago [-]
This reads as hype of the kind: "well, we can't reliably do these rather mundane things with AI, but we're going to run it extra hard and extra long in some novel way, and it will do amazing things".
The issues are with verification and with detecting drift from the goal. These are related, if not roughly the same issue. And, if they can solve this, then they will have essentially fixed AI. Maybe even AGI.
But, if this were the goal, then it seems more reasonable to solve the relatively more mundane verifiable challenges (e.g. generating solid, reliable code). Then, working up from there.
And, that's exactly what gives this the hype smell. No use for solving problems that don't get the oohs and aahs. Just straight to NAE Grand Challenge problems.
pm90 9 hours ago [-]
I think people are missing what this really is: Google giving some of its most senior engineers the best retirement home to keep them away from competitors. This isn’t in jest; I wish i could make enough money to not care for more from my job and then do research after i get old. Its honestly a brilliant move.
zackwu 3 hours ago [-]
It depends on your lens, some may think it's a way to show them the doors after failed corp politics.
Seems like Karpathy was largely focused on ML / SWE research rather than the other domains this group is after. Still, hard to imagine they were not influenced by autoresearch.
Andrej, if you're around, please share your thoughts on Discovery Loop.
eamag 10 hours ago [-]
That's a very silly comparison, there are many startups working on RSI, karpathy is just a basic version to try the concept (similar to his gpt work)
ozgung 11 hours ago [-]
That is also what I understand from that page. Autoresearch is the closest thing we (mainstream audience) know of but I am sure there is already an active research literature around it.
dnnehgf 6 hours ago [-]
this is like saying taylor swift must have been influenced by justin timberlake because they both dance on stage sometimes.
drivebyhooting 13 hours ago [-]
How do you automate experimentation?
Doubtlessly, AI can iterate at superhuman speeds in the domains of thought and design: Software, mathematical proofs, literature search.
But in the realm of experiment? Alas it is the lack of a body that constrains it.
Rather than transcendence what AI requires is immanence. In the human flesh may we find the godhead living among men. Let the laboratories, warehouses, and factories fill with the sound of its labor, as it builds a wall with a million hands that are not its own.
“Give me your tired, your poor,
Your huddled masses yearning to breathe free,
The wretched refuse of your teeming shore.
Send these, the homeless, tempest-tost to me,
I lift my lamp beside the golden door!”
dekhn 5 hours ago [-]
In my area (pharma) what it looks like is this:
A human defines a high-level research objective. "Identify a protein target that causes disease in humans, and find a molecule that binds to, and disables, that protein, eliminating the disease".
That objective then gets loaded into an ML model that spits out an experimental protocol. A protocol can be as simple as: "make 1 million test tubes, each with the protein, and in each, a custom molecules, and look for test tubes that show some reaction of interest". It can be a lot more complicated (for some reason, biologists who run these systems always try to do the most challenging experiments first, while I tend to spend all my time demonstrating the system can pass basic controls first). The protocol is then loaded into a robotic work cell which has access to protein-making machines and drug making machines, and then it handles all the experimental details (which previously would have been done by a technician). It scales up far larger than individual technician, is much more reliable, and faster (in theory- all of these are aspirational goals right now). T he results of those experiments are used to fine tune the experimental protocol and run another round. You run this in a loop and the result is better drugs faster (again- in theory.)
This is already an active area of research with more resources going to into it every day. The fact that Jeff and Sanjay have chosen to bet on this approach should be no surprise. In many ways, this is exactly what I intended when I wrote the documents inside Google (15 years ago) that motivated Jeff and Sanjay to work on scientific computing problems, and my current company is already trying to figure out how to work with Discovery Loop.
would love to see how AI can automate the construction of the next high energy particle collider
scrlk 12 hours ago [-]
"You're absolutely right! I shouldn't have pushed the anti-mass spectrometer to 105% power, causing a resonance cascade. This was a major oversight on my part."
EstanislaoStan 12 hours ago [-]
But I always wanted to try headcrab souffle.
nonameiguess 12 hours ago [-]
You're halfway there, but the only impediment isn't on the side of the researchers. Many of these topics they're trying to solve involve human subject research. Even with tireless embodied researchers who work around the clock and don't require breaks, you can't make the thing you're studying happen faster. The biggest reason we use poor proxy measures for things like longevity and mortality research is the simple impracticality of finding two groups of randomly selected people, ensuring you can control their entire lives for 60 years, the only difference between them is one variable, and see who lives longer. Putting aside the ethics, even if you could find willing subjects and actually control their entire lives to that extent, it would still take 60 years to gather the data you need. It doesn't make any difference whether robots or humans are running the program.
One of my favorite books from the past few decades is The Extravagant Universe, written by one of the astronomers who helped discover dark energy and develop the current most-accepted model of cosmology. I love this book because of the emphasis on physical process in astronomy. Part of the reason it took decades to study this problem is they need to collect data from supernovae. Those only happen so often in places we're looking. You can't automate alignment of the heavens. It happens when it happens.
SubiculumCode 5 hours ago [-]
As a scientist, I can confirm. Reality will likely kick their assess. Intelligence and creativity is not the bottleneck. Great scientists have 50 good ideas for every one they actually manage to execute on the grant->experiment->manuscript haul.
mbonnet 12 hours ago [-]
> transcendence
> immanence
somebody has been studying Christian theology!
DaiPlusPlus 12 hours ago [-]
More like someone taking LessWrong postings too seriously.
cute_boi 12 hours ago [-]
Beauty of human writing.
nxnxj 12 hours ago [-]
[dead]
numbers_guy 12 hours ago [-]
You can use simulators. However the problem is that if you're for example running material science experiments, those simulations will consume a lot of compute and take weeks, so spamming different approaches in the way an agent tends to work might not work quite as well.
atty 6 hours ago [-]
Work for a manufacturing company, and we spend a lot of time creating surrogate models for physical simulations. Huge speed ups, 100-1000x possible. You end up still using the “real” simulation for validation, but you can run orders of magnitude more simulations for early design and refinement first.
danielmarkbruce 12 hours ago [-]
Building "simulators" that use ML/AI instead of running the calculations every step is a thing.
arbll 8 hours ago [-]
Throw the research loop at the simulator first then
usernametaken29 2 hours ago [-]
> execution entails repetitive experimental loops that are hard to scale with today's manual efforts: you propose an experiment, implement and run it, examine the results, then iterate to refine your approach.
This is actually a feature, not a bug.
We can hire 1000s of undergrad students at minimum wage but chances are the results are nil. Some processes have evolved over time because they’re sensible and need to be carried out carefully.
ramon156 13 hours ago [-]
"Our mission is straightforward" continued by the most complex sentence on that page. Wondering what the definition of straightforward is now
ajam1507 5 hours ago [-]
> Our mission is straightforward: we are building AI solutions that can automatically solve important problems in machine learning, science, and engineering.
Genuinely curious which part you found complex.
xyzsparetimexyz 5 hours ago [-]
We are building _ solutions
(building solutions != building a thing. Can't you just say 'solving'?)
That can _ solve _ problems in _, domains
(Wait so the solutions are only the thing that solves the actual thing?)
pphysch 13 hours ago [-]
Right. What about the scientific hardware (instruments, sensors, robotics)? Partnerships with existing research institutions? Dealing with restricted data?
Modernizing science is a lot more complicated than just optimizing the inner experimental loop, but their hiring page implies it's a pure ML lab focused mainly on model development.
snitty 12 hours ago [-]
Yeah. ML is all well and good, but how are they going to do the science their machines design? Atoms cost money.
SubiculumCode 5 hours ago [-]
I am siding with the "intelligence is not the bottleneck" crowd. Science takes more than reading literature and making a hypothesis. You have to run the experiment. And that is where messy reality will crush the naive, and resist any attempt to package it up into a factory-like innovation engine. But they will take your money, should you have some to invest.
analog31 5 hours ago [-]
I'm a scientist. On the one hand I take some comfort in thinking that I will always have an advantage in the lab. On the other hand I'm not taking anything for granted. And my advantage in the lab has to translate into an employer being smart enough to keep me around until if and when the AI takes over, which kind of translates into their investors wanting to keep me around.
We know what happened to manufacturing when investors were no longer interested in it.
FuckButtons 4 hours ago [-]
I’m not sure that I agree entirely with your framing here, yes, you do at some point need to correct your assumptions with external evidence. But clearly there have been many individuals throughout history who have had incredibly out sized impact in their respective fields as a consequence of the quality of their reasoning.
rdedev 4 hours ago [-]
That could just be selection bias. How about all the brilliant people we don't know about cause their theories did not match experimental data? Doesn't matter if their reasoning quality is top notch
dsubburam 4 hours ago [-]
Would you side with the adjacent statement "expertise is not the bottleneck"? Didn't we recently discuss "LLMs reward expertise"?[1]
I suspect Discovery Loop will have to hire experts in each area they are targeting, to supervise and prompt their system effectively, much like the Terence Tao conversation with ChatGPT the OP cited[2].
Really seems to embrace the "Making the world a better place by <<extremely convoluted, highly technical, jargon loaded mission statement>>"
pickleRick243 11 hours ago [-]
Which part of it is highly technical or jargon loaded?
Grosvenor 10 hours ago [-]
I think it was a Neal Stephenson quote from cryptobimicon.
It certainly increases shareholder value.
teacpde 9 hours ago [-]
Most parts of it are for the average person, but I guess you could argue the audience isn’t the average person
flakiness 14 hours ago [-]
To be honest, this feels more like a lifestyle business (aka hobby) than a startup. They truly deserve it, but I don't expect a huge success as a business.
That said, I hope they write cool papers with various peers across the industry without worrying too much about the competing dynamics. That'd be a blessing for humanity, and good for their spirit.
canes123456 13 hours ago [-]
A public benefit corp shouldn’t be a start up. The primary goal of a start up is to grow as quickly as possible which is rarely benefits the public.
Very silly to call every non start up a lifestyle business. It’s just a business. Start up are the weird thing that almost always an obscene waste of time and money, but sometime creates google.
kube-system 12 hours ago [-]
A PBC is not a charity or a non-profit. PBCs are for-profit businesses with the goal of making money. In day-to-day business they're indistinguishable with other for-profit corporations, including fundraising and investment. The only real practical difference is that they give directors a little more leeway in their fiduciary duties to say "no" to doing evil things.
The advantage to a PBC is protecting founders from a serious problem with standard corporations: you might bring on investors who could subsequently demand you pollute, exploit people, and/or do other immoral activities for profit. You don't have to do these things to grow a business quickly.
snowwrestler 10 hours ago [-]
> The only real practical difference is that they give directors a little more leeway in their fiduciary duties to say "no" to doing evil things.
I’d like to provide maybe a clarification here that there is zero existing fiduciary duty in regular corporations to say yes to evil things, or even to turn a profit at all. A for-profit C corporation can legally sell stock, lose money every year, and go out of business, if the board of directors approves that strategy. Fiduciary duty exists primarily in areas of accurate communication and the avoidance of crime, fraud, etc.
A B corp basically is a C corp, but one that has formally published that their strategy includes a commitment to some social benefit. But if a C corp wanted to publish the same message to shareholders it could, and shareholder recourse would basically be to either try to replace the board, or sell the stock.
kube-system 9 hours ago [-]
Fiduciary duty absolutely does go beyond accurate communication and fraud. Directors have a duty of care that goes beyond simply not engaging in criminal fraud. Sure, you don't have to be competent, successful, etc. It is completely legal to suck at your directorship. But it's not legal to do something that you can't justify as being good for the business, which is where a public benefit activities can cross the line.
Consider the eBay/Craigslist case, eBay Domestic Holdings v. Newmark:
> When director decisions are reviewed under the business judgment rule, this Court will not question rational judgments about how promoting non-stockholder interests—be it through making a charitable contribution, paying employees higher salaries and benefits, or more general norms like promoting a particular corporate culture—ultimately promote stockholder value. Under the Unocal standard, however, the directors must act within the range of reasonableness. Ultimately, defendants failed to prove that craigslist possesses a palpable, distinctive, and advantageous culture that sufficiently promotes stockholder value to support the indefinite implementation of a poison pill. Jim and Craig did not make any serious attempt to prove that the craigslist culture, which rejects any attempt to further monetize its services, translates into increased profitability for stockholders.
This is where a PBC would have been different. With a PBC, courts are directed to balance the the stockholders interests with the company's stated public benefit.
perfmode 8 hours ago [-]
Anthropic is a PBC.
mgfist 12 hours ago [-]
> The primary goal of a start up is to grow as quickly as possible which is rarely benefits the public.
Why is that so? Fast growth, when achieved honestly, is a result of solving user pain that others haven't. Maybe you think so because users != the public, but I think in totality the public is a collection of users who all have needs they want met.
markstos 12 hours ago [-]
For certain amount of fast growth: yes. Then there's continued "growth-hacking" and enshittification to keep fast revenue growing after the pain point has been solved with dark patterns and questionable tactics.
Why? Because investors poured a bunch of money in to support fast growth and now they want their money back. And incremental growth won't do. Since 9 out of 10 of the investments fail, the surviving one has to continue to growth-hacking revenues.
flakiness 13 hours ago [-]
Fair point. Their page doesn't list any investors.
valleyer 12 hours ago [-]
The Times article lists several.
12 hours ago [-]
sarjann 12 hours ago [-]
I don't see how not? A theoretical physicist can do all the thinking they want but if they can't test an idea against nature it's not super useful.
tonfa 13 hours ago [-]
> To be honest, this feels more like a lifestyle business (aka hobby) than a startup
They're also incredibly productive and can build/deliver really good stuff, so who knows :)
wavemode 10 hours ago [-]
It can be both. Bell Labs performed a lot of speculative research while still producing economically valuable technology.
tmoertel 12 hours ago [-]
Note that Jeff and crew have cleverly structured their company to avoid problematic uses of AI (e.g., weapons or tracking humans). I suspect that many top researchers will want to work there for this reason, and to work with other top researchers who have a history of delivering results.
2001zhaozhao 12 hours ago [-]
> Note that Jeff and crew have cleverly structured their company to avoid problematic uses of AI
Do you have more sources/info on this?
tmoertel 10 hours ago [-]
They do not call attention to this aspect of their new company, but it is implicit in their business model:
In short, they are in the business of using AI to automate the discovery of useful knowledge, not to sell general-purpose AI capabilities that could be directly used in troubling ways.
2001zhaozhao 7 hours ago [-]
The question is what they plan on doing with all their scientific knowledge once they succeed.
Sure, they'll keep it internal for a while to make sure their knowledge bank is more thorough than everyone else's, and because oftentimes discoveries can be far more convincing internally than externally (you need fewer sigmas for it to update your belief in a certain direction). But then how do they intend to profit from it in the end?
moralestapia 10 hours ago [-]
x2
All the "bad guys" of today were the "good guys" at some point in time. You even cheered for them back then.
sidibe 5 hours ago [-]
Maybe a little naive for this but given the decades Jeff Dean and Sanjay have been contributing to so many things in the industry and never heard a bad word about either, they never seemed to reach for attention or self promote, going to give them a little more of a cachet of trust.
wavemode 10 hours ago [-]
Like how OpenAI is (was?) structured as a nonprofit?
paganel 12 hours ago [-]
There's this somewhere on that page:
> securing cyberspace,
which has clear military implications, at least in today's age.
jedberg 11 hours ago [-]
So does more efficient cooking methods, but that is not the primary focus.
As opposed to say weapons systems or targeting systems, which are really only for military use.
The military needs a lot of things that other people need, and some things that only the military needs. If you don't work on the things only the military needs, I think you're in the clear.
tmoertel 12 hours ago [-]
Do you believe that securing cyberspace is problematic solely because it has military implications? I mean, everything has military implications. That fact doesn't imply, however, that those things are bad for society.
paganel 10 hours ago [-]
> I mean, everything has military implications
In essence I agree with that, it's just that cyber-security has particularly been the focus of recent military discourse.
Just yesterday I was reading an article here in the Romanian mainstream media about how Constanta Port's (our biggest port at the Black Sea) IT infrastructure has been under constant cyber attacks (presumably by the Russians) so as to hinder the export of Ukrainian grains through it. And this is just one of the many such (relatively) recent examples.
bredren 12 hours ago [-]
Securing cyberspace matters to everyone. Defending critical infrastructure or design of tactical cyber-offense is reasonably in scope for military work.
However, reducing (or rather limiting the increase of) PII leakage and impact of ransomware activities is much closer to day-to-day mainstreet of most people.
Anyone committed to advancing science should care about this regardless of its potential contributions to defense.
arjie 13 hours ago [-]
This is very cool. It might be a new scientific revolution to have computer-driven discovery. So often we find things that are "this could have been done 20 years ago" and with an indefatigable searcher perhaps we'll close all those things. Though it does remind me of that Ted Chiang (I think) story where humans and superhumans coexist and all the science of the former is meta-studies of the work of the latter.
PaulDavisThe1st 13 hours ago [-]
> It might be a new scientific revolution to have computer-driven discovery.
And ... it might not.
arjie 13 hours ago [-]
True, nothing might be anything. But I'm an optimist :)
jbmchuck 11 hours ago [-]
Sure - and knowing what is not possible with current tech is a nice datapoint to have.
ValentineC 14 hours ago [-]
I wonder if Jeff Dean facts [1] (I hope people remember the reference) will carry over to the new startup.
I had not read this before, but told many students the same about my PIN code and I a quiz about the last digits. Love it.
soVeryTired 13 hours ago [-]
0000 in base pi. Oh Jeff.
14 hours ago [-]
tcp_handshaker 13 hours ago [-]
Those are all fake, part of an internal Google narrative that overstates individual contribution, and obscures the work of large engineering teams.
Here are some Jeff Dean well sourced facts:
- Already part of engineering of Google indexing systems that lacked basic checksums and ran on non-ECC hardware, allowing silent data corruption.
- One of the authors of LevelDB a database with so many documented crash-consistency, recovery, and data-loss weaknesses for years. Just check their Github project. LevelDB current tracker contains unresolved crash consistency, recovery and corruption reports going back almost 12 years on GitHub
- In AI engineering technical lead, let TensorFlow lose researcher mind share to PyTorch, and caused Google fragmented landscape across TensorFlow and JAX.
- Had the people at Google who invented the Transformer architecture, but failed, to turn that lead into the first dominant public LLM.
- As AI engineering and VP management let Google Brain and DeepMind remain duplicated and internally competitive for too long.
- Let Noam Shazeer leave and then spent heavily to bring him back with nothing to show for.
- Part of Technical VP leadership who had Bard rushed to launch with factual errors in Google own promotional material.
- The first Gemini demonstration overstated how real-time and interactive the system actually was, being basically a fake.
- Part of the VP and AI technical leadership who had Google AI Overviews launched with weak source quality controls and repeated satire and low-quality web content as factual advice.
- Part of teams that launched AlphaChip performance claims that were difficult for outside researchers to reproduce and remain technically disputed.
- Jeff Dean public explanation of Gebru departure was contested and damaged confidence in Google scientific governance.
- Jeff Dean was part of the team at Google that removed or marginalized prominent internal AI ethics critics shortly before many of their warnings became product problems.
- Jeff Dean was one of the managers behind Project Dragonfly supporting censorship.
- Jeff Dean is part of the VP technical leadership approving Project Nimbus supporting an ongoing genocide.
shawn_w 12 hours ago [-]
I suppose you think Chuck Norris Facts are fake too.
13 hours ago [-]
bonsai_bar 12 hours ago [-]
You sound like you're quite jealous of him.
dekhn 12 hours ago [-]
Actually the list is technically accurate. So maybe it's sour grapes, but it's correct sour grapes.
root-parent 12 hours ago [-]
I had never heard of many of these, was surprised, went to research, and so far, the list seems correct.
twister2920 12 hours ago [-]
not sure how you got that from a long list of criticisms
dgellow 11 hours ago [-]
That founding team is insane. Very excited to see what happens here. I really like that they do not mention AGI or anything like that. Their mission statement reads pretty pragmatic compared to other AI companies (the bar is very low…)
holmesworcester 12 hours ago [-]
Someone who left DeepMind over Google's agreement to provide military AI to the US government tried to get Jeff Dean to quit too:
Maybe this is what happens when someone with Jeff Dean's standing tries to quit?
TBH, I'd rather have Jeff Dean working on the creepiest-possible tech for ICE than joining the race to automate AI research. Automating AI research is terrifying.
tokioyoyo 11 hours ago [-]
If you check out some sub-tweets from people in the org, it wasn't really all butterflies internally for a while. Sorry, really don't want to name people and give examples.
asadm 12 hours ago [-]
> Automating AI research is terrifying.
what why?
reasonableklout 1 hours ago [-]
It depends what they mean by automating. But the classic argument goes:
* Each new generation of models has emergent capabilities we did not anticipate.
* We already have trouble monitoring and controlling the current generation (see HuggingFace incident).
* The more we let models shape their successors, the more out-of-distribution each generation's learning environment becomes.
* If not done carefully, we risk creating extraordinarily intelligent and powerful models with unintended behaviors, like deceptiveness or power-seeking.
kridsdale1 9 hours ago [-]
Skynet.
wy1981 13 hours ago [-]
Jeff Dean, Sanjay, et al have achieved so much. I'm very happy for them. Truly deserving.
Sometimes I couldn't resist wondering if I'll ever do work that has a tenth of the impact of theirs.
jimbokun 10 hours ago [-]
> Between us, we have pioneered massive scale computing and led the creation of critical infrastructure, products, and foundational AI advances that the world relies on, including multiple generations of Google Search, Google Ads, Google News, Google Translate, Google File System, MapReduce, BigTable, Spanner, TensorFlow, Pathways, TPUs, AlphaChip, AlphaStar, AlphaCode, AlphaFold, Gemini, model distillation, mixture-of-experts model architectures, word2vec, sequence-to-sequence models, chain of thought reasoning, neural architecture search, and multiple generations of Large Language Models (LLMs) among others.
Not a bad combined CV.
nullsanity 12 hours ago [-]
[dead]
gosub100 12 hours ago [-]
Gemini has done absolutely nothing for me. I can't even shut off the navigation feature on my phone using only hands free, when I get close to my destination. I have to take my eyes off the road, look down, and tap to exit.
Google's advanced AI cannot even exit a mobile app.
16bytes 12 hours ago [-]
Jeff and Sanjay's contributions far predate LLMs and influence far outside of Google.
Jeff was a ACM Fellow in 2009 and published the massively influential MapReduce paper in 2004.
allthetime 12 hours ago [-]
Antigravity + Gemini Pro absolutely RIPS through fullstack react + react-native apps / systems. I pay ~$20/month and I basically don't have to do my real work anymore. My time is freed up to learn systems programming and blender.
qlte 12 hours ago [-]
Oh nice have things stabilized with models/quotas and Antigravity is usable with the Pro plan again? I was getting a crazy amount of value out of Gemini CLI for “free” on my Pro plan but after the shutdown struggled to make agy work with the updated quotas/bigger models without instantly being rate limited and just started doing everything on Codex/Opencode Go.
I should give it another try…
allthetime 11 hours ago [-]
Yeah can't remember how long ago but it was running out after less than an hour - then they announced they were loosening restrictions and I've been able to easily get everything I need to done without hitting limits.
I don't do huge automatic project wide hands-off agent loops though. I spent a lot of time architecting my systems to be easy to generate code on top of with pointed & detailed prompts. So I'm not abusing context... YMMV
parthdesai 10 hours ago [-]
How does this comment relate to the parent comment?
gosub100 8 hours ago [-]
it shows an example of how their AI cannot perform a basic task, as simple as exiting a program.
parthdesai 6 hours ago [-]
What has that to do with the comment you replied to, which was about Jeff & Sanjay achieving so much?
stephantul 13 hours ago [-]
I’ve always felt that the idea that science is bottlenecked and therefore needs more automation only works for a very narrow definition of what science is, and entails a very specific view on what it should be.
hobofan 13 hours ago [-]
> only works for a very narrow definition of what science is
And so does academia. It's just that instead of AI and robotics, PhD students are thrown onto problems that are in large parts slightly tweaked reconfigurations of similar experiments.
Especially in chemistry, biochemistry, material sciences there is a large space of discoveries that are barely "novel" in an intellectually stimulating way, but still highly valuable that can be explored orders of magnitudes faster than is currently the case.
stephantul 13 hours ago [-]
That is true, I’ve seen people do biochemistry and geology work, and it did look very mind-numbing.
Then again, gassing rats and taking biopsies is not something you can do with AI.
roughly 12 hours ago [-]
> Then again, gassing rats and taking biopsies is not something you can do with AI.
Also, like, let’s maybe _not_ make the “gassing and cutting living organisms open” AI? Let’s just leave that particular genie in its bottle?
smcg 11 hours ago [-]
Unfortunately, that's most of science. I don't see these AI systems doing reproducible experiments in "meatspace" any time soon.
porridgeraisin 13 hours ago [-]
Yep. A communications professor where I did my MS says a 200usd/mo claude sub (which ant gives for free) does as much work as 5 grad students. It's mostly like you said, trying out new ideas rapidly.
teamonkey 12 hours ago [-]
The purpose of hiring grad students isn’t to advance science, it’s to train experts.
pickleRick243 11 hours ago [-]
It's 90% to advance science via cheap labor and 10% to train a small group of future experts who will hire grad students to 90% advance science via cheap labor etc.
...
porridgeraisin 11 hours ago [-]
Yes. They have grad students too. This is just like having more grad students that don't need to be trained so the work you can get done is not bottlenecked by the number of people you can train.
tcp_handshaker 13 hours ago [-]
Lets keep your comment out of the VC pitch deck shall we?
13 hours ago [-]
claiir 13 hours ago [-]
The site itself is really leaning into the “made with Fable” aesthetic
pelagicAustral 13 hours ago [-]
Why are people so sour about this?? I can read the site easily, its clear, performs well on mobile, what else do you want? Why is so offensive to people that models trained on tailwind or whatever?
throwaway0123_5 11 hours ago [-]
Some parts are pretty annoying to read... the paragraph beginning in "Our mission is straightforward:" has many lines with just 2-3 words, massive font, and tons of unused whitespace to the right. Changing the page/browser zoom doesn't seem to help much either.
13 hours ago [-]
DaiPlusPlus 11 hours ago [-]
> Why are people so sour about this?
To many people, myself included, who have to wade through huge amounts of low-quality AI slop which is actually a negative value: no-one benefits when non-experts fire-off one-shot LLM/agent prompts to produce PRs, reports, documentation or "journalism" riddled with imagined truth and factual errors - and the more that people like me have to evaluate these inputs for our job and how wrong they are it pisses us off - but also it means we pick-up on the hallmarks, tells and cliches of these low-effort, no-respect submissions - and now the litany of tells includes this beige-themed, blurred-backdrop-navbar corporate website look: theirs site looks like the 4 or so other LLM-generated, negative-value slop-farm sites I've wasted time on recently - all over the past few weeks.
So I'm saying that, without having known anything about what "Discovery Loop" is - or is not - but landing on their site and and seeing that beige colour and blurred-backdrop navbar, I immediately moved to close the tab; what kept me here was seeing the HN thread had over 100 comments by now and read more about it; if not for that then I wouldn't have given it further thought.
Having "that" beige site look with same the overused looks is either an unintentional indication that the site's author used a low-effort AI prompt to generate the site and that the content within is likely to be low-quality, low-value - or it's an intentional lure to appeal to those who uncritically share in the AI psychosis and so, I assume, are a good target to seek investment from even if it means losing the audience of cynical Internet critics like myself because they know people like me won't be breathlessly repeating their vision-statement on LinkedIn and throwing money at them - kinda like how scam emails intentionally include mistakes for better audience selection. And both possibilities have unpleasant implications.
------
Anyway, regardless of the background of the team behind it, the way the project is described sounds exactly like the recursive-self-improvement and simulated-science thought-experiments from _that other website_ - it's the kind of thing I expect Angela Collier to brutally takedown in an amusing video.
slopinthebag 13 hours ago [-]
Because it’s lame and aesthetics matter.
make3 13 hours ago [-]
it's just a low effort snark comment, don't overthink it
swalsh 13 hours ago [-]
If this was a design firm, it might matter. But this is mostly a hiring ad for engineers, and a landing page for VC. I'd judge them more if they actually put effort into it.
npilk 12 hours ago [-]
If their goal is to automate scientific discovery, why would they not automate building their website?
(Though, I do wish people would use just a few extra prompts to break out of the 'vibe-coded' look.)
swalsh 13 hours ago [-]
let me rephrase that:
"The site itself demonstrates the team is spending their money in the places that matter, and using quick solutions for the stuff they need but isn't mission critical"
lrae 11 hours ago [-]
You could rephrase that again I guess:
"The team of AI pioneers lacks the basic prompt-writing capability to make their marketing landing page not look like AI slop."
I, personally, don't hate it. It's a decently clean site, but it does invoke those thoughts in me too.
polishdude20 4 hours ago [-]
That's a great point.
If you know how to promote and work with AI to create novel solutions to hard problems. Why can't you prompt it to at least make a better website?
IshKebab 13 hours ago [-]
At least it isn't dark purple.
Johnny_Bonk 14 hours ago [-]
For sure made with Claude code for front end, but I’m excited to see where they go
GodelNumbering 13 hours ago [-]
This is one of the interesting aspects the 'AI job loss' community doesn't account for. As the technology unlocks things, more startups are created. And even at a lower nominal engineer-to-work ratio, overall demand for talent still goes up. Ultimately, we are not a single group trying to achieve a common outcome, we are a collection of many groups trying to compete against each other.
throwaway0123_5 11 hours ago [-]
What percentage of people work at a startup though? Not just new/small business, which could include restaurants, local services, etc., but tech/science startups that would meaningfully benefit from AI.
I'd bet you could 10x the number and still be in low single digit percentages of the US workforce. And it seems pretty likely that AI-enabled startups will also employ less people per-startup.
If AI causes a white-collar jobs apocalypse, I don't think startups are picking up the slack, although it'll plausibly cushion the blow somewhat for top-performing tech workers.
reasonableklout 2 hours ago [-]
Yes. Startups are intensely competitive, exhausting, low-stability places to work. This is the definition of job displacement for most people.
jszymborski 11 hours ago [-]
> Scientific discovery is bottlenecked.
Yah, by funding and how we award it, not by an imaginary lack of undergrad and grad students. Scientific funding requires a shotgun approach and many national science funds try to pick winners as opposed to funding broadly. When the folks who researched bacteria in volcanic vents or the molecular biology of the Gila monster they never could have imagined the industries and markets they'd create let alone the lives they'd impact (i.e., PCR and GLP-1 agonists). Lots of grants require you to explain how the work is "translational" or has some sort of economic application (even if not explicitly), but that'll just get us faster horses or whatever the Ford quote is.
taurath 10 hours ago [-]
I truly believe if we took a measely $50b out of the LLM world we could create trillion dollar economies from basic research within 10 years. I personally know folks who have intuitive understanding of things that can't get funding to be studied. If we could keep the money away from university upper management, it'd cost $10b max.
Oh and while we're at it, $20b a year would house every homeless person in the US - there's a hell of a lot of extremely high intelligence and low social cohesion folks who can't handle the extractive punitive system we have. Our ability to deliver opportunity to create lucky situations for ourselves is getting worse and worse
eamag 9 hours ago [-]
$50B is essentially 100% of the annual NIH budget, which funds the vast majority of JUST life sciences basic research. So you may want to update your beliefs
e: oh and while we're at it, California spent over $24 billion over a five-year period (2019–2024) specifically targeting homelessness
vanviegen 10 hours ago [-]
Yes! But if science is bottlenecked by funding, making it cheaper might help?
woeirua 10 hours ago [-]
Not really. Grad students are already essentially working for free.
tjwebbnorfolk 10 hours ago [-]
How many lavishly-paid deans and bureaucrats and administrators are employed for each grad student?
asdff 7 hours ago [-]
Generally universities take half the grant from the start and that's before taking fringe on top of salaries.
jszymborski 9 hours ago [-]
It's not easy to disentangle and it varies by country and institution, but those positions are not normally directly funded by public research grants.
gtirloni 10 hours ago [-]
LLMs can't materialize funds or political will so let's stick to running GPUs hot and publishing papers. The citations will be amazing. /s
nullbio 26 minutes ago [-]
Good luck. People can't figure out how to solve ARC-AGI reliably, let alone the complex problems in the real world.
4lx87 12 hours ago [-]
Discovery and optimization are very different processes. Optimization is the process of finding the shortest path to a goal. Discovery is the process of stumbling on new goals and redrawing the map of what's possible.
Ambitious goals and new discoveries happen via novelty-based search. Progress in scientific discovery is measured by how different/interesting the outcomes are, not by closeness to a predetermined goal.
Discovery is a creative search that preserves optionality, whereas optimization restricts optionality. In other words, you usually don't discover anything novel unless you're trying new things that don't appear connected to the goal in the first place. Would an ML optimization loop have discovered transformers?
jfreds 5 hours ago [-]
> would an ML optimization loop have discovered transformers?
I think that’s exactly the kind of problem this group is looking to solve. You make a compelling intuitive argument, but that’s not the same thing as a proof
roughly 12 hours ago [-]
Two to keep in mind with these kinds of things -
1. There’s some irreducible costs in terms of time and material in the physical world that are not amenable to the kind of optimization or parallelization or even just the raw speedup from Moore’s law or computational architecture improvements we’re used to with software. My experience is primarily in biology, where the examples here are things like “it takes 20 minutes for E. coli to replicate” - it has taken 20 minutes for E. coli to replicate for a billion years, and next year it will still take E. coli 20 minutes to replicate, no matter how good your software stack is. Similarly, it takes X amount of energy to grow enough E. coli to produce a meaningful result, and that energy costs money, whether it’s in the form of glycerine or heat or whatever you want, and that also won’t materially reduce in the same kinds of “orders of magnitude” sense we’re used to from software, which is what we’re usually expecting to make the economics of these things work out.
2. Complicating the above, physical systems are phenomenally multivariate - far, far more than you think, and biological systems especially are just unbelievably complex - which means the number of experiments and the length and duration of those experiments you need to run to get enough data to be reasonably confident you’re seeing genuine signal is Way higher than you think.
Combine those two things and what you get is a money furnace, even before you get to the AI model training part, which is Also a money furnace. There’s low hanging fruits in all this, there’s areas where automating the approach can be really valuable, but typically the moment you turn this machine on, you’re gonna start burning money at a rate that would embarrass a finance bro on a coke bender, and that’s effectively unavoidable because the real world is not amenable to software’s scaling laws.
xyzsparetimexyz 5 hours ago [-]
Thats why you simulate e coli at 30x in a sim environment that fable slopped together. Duh
cjauvin 6 hours ago [-]
LawZero, Yoshua Bengio’s startup, also proposes to automate scientific research and experimentation, from the perspective of safety, by being explicitly “non-agentic”:
> we have pioneered massive scale computing and led the creation of critical infrastructure, products, and foundational AI advances that the world relies on, including multiple generations of Google Search, Google Ads, Google News, Google Translate, Google File System, MapReduce, BigTable, Spanner, TensorFlow, Pathways, TPUs, AlphaChip, AlphaStar, AlphaCode, AlphaFold, Gemini, model distillation, mixture-of-experts model architectures, word2vec, sequence-to-sequence models, chain of thought reasoning, neural architecture search, and multiple generations of Large Language Models (LLMs) among others.
holy shit. I've known this, but...
melodyogonna 13 hours ago [-]
Oh wow, that's a blow to Google, what's with the talent scarcity in ML. Though if this goes anywhere Google will likely buy them back.
jfrbfbreudh 13 hours ago [-]
Google is backing it.
13 hours ago [-]
FailMore 13 hours ago [-]
Google down $160Bn so far since the leaving announcements. Those are some valuable people!
IAmGraydon 13 hours ago [-]
Google is literally at the same stock price it was on Monday. This is a normal daily fluctuation for them.
swalsh 13 hours ago [-]
By the middle of the 2030's the world we live in will be unrecognizable.
kingofthehill98 13 hours ago [-]
I agree, for better or for worse.
If I had to bet my money, it would be on "for worse".
xyzsparetimexyz 5 hours ago [-]
No it won't, not in any real world touch grass, walk around downtown kinda way. The internet will have changed but so what
dude250711 13 hours ago [-]
It will not be owned by top 1%?
WarmWash 5 hours ago [-]
Probably the top 1% AI.
I don't see any future reality where an ASI respects money piles.
swalsh 13 hours ago [-]
That seems to be the one unchanged variable of time.
roughly 12 hours ago [-]
That’s a policy decision, don’t let them convince you otherwise.
warkdarrior 11 hours ago [-]
The change is that it'll be owned by the top 0.0000001% who control the LLMs that will be your new boss.
minittsnet 12 hours ago [-]
[dead]
stan_kirdey 2 hours ago [-]
*self-discovery loop more like it :-)
montebicyclelo 13 hours ago [-]
Did the ycombinator podcast which included giving advice to startup founders just a few days ago:
Interestingly, one list identifies "AI" as a top world problem! One person's problem is another person's solution, I guess--and vice versa, as well.
An extreme example: curing a disease is good for patients but bad for the healthcare industry--which is (in kind) also bad for healthcare workers and everyone in science working on cures.
xyzsparetimexyz 5 hours ago [-]
No its not. Everyone dies. Healthcare is invoked in everyone's life. Generally the longer you live the more healthcare you'll need.
I don't see the salary (on mobile). Isn't there a law stating it must be added?
guessmyname 13 hours ago [-]
Only California employers with 15 or more employees have to post a pay range (Senate Bill 1162 [1], effective Jan 1, 2023) [2][3]. Discovery Loop employs only four people (that we know of), so it isn’t required to disclose a salary range in its job posts, of which there is only one [4].
It's too bad they would follow the letter of the law, and not state the salary anyway. I see that as a negative indicator, regardless of offer size.
tehnub 2 hours ago [-]
That pic of the team... no swag to speak of
burgerone 55 minutes ago [-]
Of course it's AI because why wouldn't it
Noe2097 13 hours ago [-]
This looks like a realization of "benevolent self conscious AIs agreeing to cooperate with mankind to do great stuff". Often in these tales, there is a hidden cost to it: the AI has its own agenda, or does crazy experiments with humans mind/brain. I'm wondering what shape will take that plot twist in reality :)
anr0 5 hours ago [-]
with billion dollar seed rounds becoming the norm, it seems like there's no longer an advantage to build from within these bloated giants. can be much nimbler and have access to the same budget out the gates
13 hours ago [-]
8 hours ago [-]
11 hours ago [-]
ggcr 10 hours ago [-]
> Oriol Vinyals, Sanjay Ghemawat, Jeff Dean, Quoc Le
as founding members is crazy !
syntaxing 13 hours ago [-]
This reminds me of Three body problem and how the scientist discovered the high strength wire was through quick physical experiments and use them as input to an AI model to determine if it works.
asimpletune 13 hours ago [-]
They're structuring the new company as public benefit corporation.
an0malous 13 hours ago [-]
Does this mean anything besides for corporate virtue signaling?
Aboutplants 7 hours ago [-]
I’d wager it does the opposite of that in public opinion. There is a certain stink associated with it in current circles
puttycat 11 hours ago [-]
What's the business model of these startups?
zeronone 5 hours ago [-]
Surprised that Sanjay is the tallest among them.
sumedh 5 hours ago [-]
He was born in the US not India, good food/nutrition must have played the part :)
Sathwickp 12 hours ago [-]
Is it a very hard problem to solve that jeff and the other legendary engineers have decided to quit and start on this?
bagacrap 6 hours ago [-]
I suspect they want a bit more control over what they're working on. These days the bean counters are running Google.
thisoneworks 12 hours ago [-]
I mean what are they doing right now at Google? Optimizing data centres? Pretty lame compared to this. Even if they completely fail, i'm sure there'll be good lessons.
deerstalker 13 hours ago [-]
National Labs in the US have been doing this for a while now. I feel like the private sector will take the lead soon.
pphysch 13 hours ago [-]
Why? Science is wildly unprofitable on the scale of an individual private firm.
Taikhoom2010 13 hours ago [-]
The problem is all these new labs don't have any competitive advanatge amongst each other, talent can only take one so far, though Jeff is a legend no doubt.
Models are commodities the applications eg. BaseTen, OpenRouter should capture the value.
The company is developing an application, or a class of applications. Not a new model.
make3 13 hours ago [-]
I think Google's branding was starting to be too poor in AI to get top talent, they needed the refresh
malux85 13 hours ago [-]
Model routers - send all of your data through a third party who totally swears not to peek at it.
If youre doing anything high value (advanced research, classified work, high value industrial research, health data) then sending your data through a third party like that is insane.
Taikhoom2010 12 hours ago [-]
yes perhaps, although I think the best option for a enterprise is to train a model on it's own data.
willy_k 10 hours ago [-]
Best option by what metric? For which enterprises. I say this having worked at an “enterprise” where this was not a good option. For (lack of) talent/expertise, budget, infrastructure, and actual value relative to the eventual bottom line.
Taikhoom2010 9 hours ago [-]
Well its not the only enterprise tool, but from the perspective of llm delivering enterprise spexifc insights
willy_k 8 hours ago [-]
Still, to get results from that you need someone who can create a decent finetune. That might not be realistic, but it very well could be realistic to have someone optimize some prompts and curate a knowledge base. Point is, its a possibility but “best” depends on the nuances of reality.
adfm 13 hours ago [-]
FHE
danielmarkbruce 13 hours ago [-]
Automating ML/AI research seems completely tractable. Most of the other claims seem much less doable.
13 hours ago [-]
galoisscobi 12 hours ago [-]
> Imagine a future where a handful of people can conduct scientific research and engineering tasks much more rapidly, and with higher quality, than massive teams of scientists and engineers do today.
Imagine a future where only the anointed few elite minds can participate in science and engineering. Btw we’re hiring.
Great message!
TrackerFF 6 hours ago [-]
I don't know why you're being downvoted.
This is basically something scientists have been alarming about for the past year: We're moving into a future where science may be tiered into the haves (those with access to premium compute) and the have nots (hoi polloi with restricted access), which in turn could seriously influence what kind of science we'll get.
Worst case, we'll get science that is completely dependent on business and politics.
EDIT: I should note, this comment was aimed at a more general case.
Don't leave us guessing... Why is yours better/different?
maCDzP 10 hours ago [-]
I have used something similar. I set up a team of agents that researches, proposes, builds and audits. Then rinse and repeat. I have used it for different topics. It hasn’t made me a millionaire, but I haven’t lost money either - so that’s some sort of win, right? But I would not have been able to ideate, test at that speed and quality without an LLM.
skinfaxi 10 hours ago [-]
> It hasn’t made me a millionaire, but I haven’t lost money either - so that’s some sort of win, right?
I'm curious if that is before or after token costs?
cityzen 7 hours ago [-]
Can’t wait until they get acquired by Google.
roflmaostc 7 hours ago [-]
Google already invested into them.
varjag 10 hours ago [-]
Discovery systems are making a comeback huh.
xuehaohu 10 hours ago [-]
Big news aside, it feels exciting to see them leave and pursue startup. They could have stayed back, and retire
bagacrap 6 hours ago [-]
This is their version of retirement. Did you think Jeff Dean was going to stop doing tech and play golf?
kulsumshannan 12 hours ago [-]
This seems interesting! I wonder how this will play out.
jacknews 5 hours ago [-]
"making solar energy economical"
judging by the amount being installed, it already is.
claiir 13 hours ago [-]
The job req has "Recursive Self-Improvement" as one of the "area of expertise" checkboxes lol
paxys 12 hours ago [-]
It is targeted at a dozen or so people at OpenAI and Anthropic, not you or me.
recursive 11 hours ago [-]
Then why is it published on a public website?
paxys 9 hours ago [-]
Where else would they publish it?
recursive 8 hours ago [-]
If it's intended for a global audience of 12, just send it to them. No need to publish.
paxys 6 hours ago [-]
And how do you know who they all are?
recursive 5 hours ago [-]
It seemed implied by knowing one of two employers and the estimated total size of the population. I could have been wrong.
not that it really matters, but is he leaving Google?
14 hours ago [-]
plaxiotech 2 hours ago [-]
great
xnx 13 hours ago [-]
I've seen tiny tiny hints from the outside that Jeff Dean was dealing with too much internal BS. Two examples that come to mind: Having to deal with Timnit Gebru fiasco, and even chips in the TPU series getting marketing names (Trillium and Ironwood) before switching back to more standard numbering.
compiler-guy 13 hours ago [-]
I have no doubt that internal Google friction is one of the reasons they are moving. But the Gebru incident was almost seven years ago now. It is very unlikely to be a proximate cause.
I doubt numbering vs names on TPU releases even crosses Jeff's radar. It's not the kind of thing he cares about.
xnx 10 hours ago [-]
Yes. I'm not privy to any real insider gossip, but I read all his tweets and watch all his public speeches. He made an offhand comment about the TPU naming. I probably overinterpreted that, but I took it as a sign. There should have been a team around Jeff Dean that acted as an absolute shield for any BS. If Jeff disagrees with anyone at Google outside Sundar/Sergey, the strong onus should be on the other person to justify their stance.
omederos 10 hours ago [-]
What a team.
1970-01-01 13 hours ago [-]
I'm skeptical of any Engineering loop that doesn't include reality (as in touch grass) feedback. Pure logic and reasoning is the domain of Maths and Science (philosophy). Surely it will work, but it will not "be able to solve any learning loop".
LarsDu88 13 hours ago [-]
I'm almost certain the goal of this startup is to make physical automated research labs guided by RL
XenophileJKO 13 hours ago [-]
How is that different than video input?
1970-01-01 13 hours ago [-]
There are over 2 dozen known senses to reality. Video input is a fraction of a sense.
I know these sorts of meta comments are often frowned upon, but good god do I hate this approach of fading in every individual element on scroll down the page. It's one of my biggest pet peeves of "modern" web sites.
luqtas 2 hours ago [-]
yes! and giving current scientific research on reading efficiency pointing towards fixed pages being much better than scroll, the whole web is screwed but these fancy sites... a big merda
numbers_guy 13 hours ago [-]
When they say experiments, do they mean using physics simulators?
danielmarkbruce 13 hours ago [-]
in AI/ML, no. They are just going to automate AI/ML research to start with. Totally doable.
For some of the other things, undoubtably yes.
searine 13 hours ago [-]
Computation is not the hard part of discovery.
BenFranklin100 6 hours ago [-]
From the self-stated bios, this group consists solely of CS guys. No biologist, physicist, linguist, chemist, biophysicist to be found. Based on this observation alone I call nonsense. These is AI bullshittery. These guys aren’t close enough to the problems to understand the challenges.
Source: PhD Computational biophysicist turned experimentalist. I work with genuine scientists across a range of disciplines from neurodegeneration, cancer, to fibrosis. Getting in the lab and generating data is absolutely key, among other things.
nl 6 hours ago [-]
Do you actually think that this group of founders will have trouble finding domain experts wanting to work with them?
BenFranklin100 5 hours ago [-]
“Imagine a future where a handful of people can conduct scientific research and engineering tasks much more rapidly, and with higher quality, than massive teams of scientists and engineers do today. By automating the loops of discovery, the world will be able to make much more rapid advances across countless fields of science.”
The key point is these jackasses explicitly state, “ a handful of people” can replace “massive teams of scientists and engineers”.
These guys don’t even understand the nature of the challenge and neither do you apparently. If they did, they would realize that it indeed does require “massive teams of engineers and scientists” to solve our most pressing problems.
cwoolfe 12 hours ago [-]
"The speed of light in a vacuum used to be about 35 mph. Then Jeff Dean spent a weekend optimizing physics."
bezko 13 hours ago [-]
So Ralph Wiggum in a suit?
sidcool 13 hours ago [-]
I am available for hire.
AIorNot 12 hours ago [-]
Another way to see this is: a bunch of renowned google engineers realized they can grab some of the VC pie for themselves
Jesus, he left Google to do what everyone else is already trying to do? He must be so insulated he doesn’t realize what the real world is actually up to. I mean, organizations started on this exact same mission three or four years ago. Or longer. I suppose it’s better to wake up later than never.
m3kw9 12 hours ago [-]
The AI designed italics on thin font is hard to not see as slop.
aaronharnly 11 hours ago [-]
You know when the page has all-caps "01 — THE APPROACH" that it is slopified. I guess I shouldn't be astounded, but I am, that world-class talents with world-class backing are just taking default LLM output and saying, "okay looks fine".
m3kw9 11 hours ago [-]
They would argue they are focused on more important stuff, but marketing shouldn't be underestimated.
13 hours ago [-]
aykutseker 11 hours ago [-]
[flagged]
yddryhry 13 hours ago [-]
[flagged]
daishi55 13 hours ago [-]
Yeah what these guys are mainly known for is vaporware
> we have pioneered massive scale computing and led the creation of critical infrastructure, products, and foundational AI advances that the world relies on, including multiple generations of Google Search, Google Ads, Google News, Google Translate, Google File System, MapReduce, BigTable, Spanner, TensorFlow, Pathways, TPUs, AlphaChip, AlphaStar, AlphaCode, AlphaFold, Gemini, model distillation, mixture-of-experts model architectures, word2vec, sequence-to-sequence models, chain of thought reasoning, neural architecture search, and multiple generations of Large Language Models (LLMs) among others.
OutOfHere 13 hours ago [-]
I wish them well, but this firm will likely fail miserably. The reason is that the value is in having access to real world hardware platforms that AI can control, not in the harness that controls them. There exist plenty of harnesses already. These people couldn't even get Google to build a top LLM. Before you dismiss and downvote, I dare you to counter it.
Continued participation is a stain on every company and person who continues to use it.
There are alternatives. Don't like them? Make a better one.
Stop using that shithole.
calufa 14 hours ago [-]
As LLM coding agents plateau— at least for the average engineer without tens of thousands of dollars or swarms of agents to run —I’d say that, from here on it’s going to be about ASICs, specialized LoRA/or-equivalent models, or a Ruby on Rails for LLM context engineering and orchestration, which LangChain and others seems well position, including Google as they own the entire stack. LLM free lunch has been over for a while, perhaps since the ReAct loop, and has been official since Ilya mentioned it at NeurIPS.
I feel the most exciting development these days is self-evolving agents. Especially if you have a way to verify their outputs with a formal system, or with a system developed since the 60s by armies of PhDs.
DeepMinds Gnome is a good example, where they use DFT to verify outputs. Approximating NP-problems is always fun for those who dare.
I am also building in this space. Its a mix between HPC, AI, and hard science. Pretty fun compared to waking everyday to LLM news that seem more like marketing stunts.
aoeusnth1 13 hours ago [-]
Sounds like you get your news from 2024 when people thought things were plateauing after GPT4?
zuzululu 13 hours ago [-]
we definitely haven't hit plateau yet. I think a lot of people latch on to anti-LLM narratives without really thinking things through.
deeviant 14 hours ago [-]
LLM coding isn't even close to plateauing. Right now, the major players are in a consolidation step, focusing more on economic efficiency but still not at the point where we're ready to start burning models to hardware and freezing the line.
They are straddling the line between pushing it forward, and justifying the business case. It's hard to do both at the same time.
calufa 13 hours ago [-]
LLMs are hungry for tokens. Every day I see more startups claiming token usage at 50-100k per month. You can always brute-force your way in - just see HuggingFace's recent attacks.
If throwing more money at inference while accumulating compounding technical debt is the new norm, then we are not solving the problem, and the solution space is already covered.
Perhaps there are marginal gains at the expense of quadrillion-params LLM models with 10x the cost and energy. We are simply making inefficiency more expensive, camouflaged by VC money and great marketing.
If that is not plateauing, then I guess I will have to reconsider what plateauing means.
bpodgursky 12 hours ago [-]
> You can always brute-force your way in
This is such unbelievable revisionism! Can you imagine in 2022 saying "Oh of course you can brute force your way to AGI if you spend enough money per month". Nobody thought that! Come on!
AmbroseBierce 8 hours ago [-]
"the benefits of science and technology to the world" just like AI has brought such benefits? Because I haven't seen them, for example it hasn't helped reduce inequality (nor poverty), or reduce climate change, or pollution, or daily stress, if anything it seems to be worsening some of these issues.
So forgive me if I'm skeptic when renowned AI scholars claim to start something for "the benefits of science and technology", because it really seems like we have very different definitions of these words.
> Our general approach is to automate the experimental loop. We think this approach is broadly applicable across many different fields of science and engineering. We’ll initially focus on ML research and engineering, but believe the approach can help with important subproblems in nearly every one of the fourteen <at>NAE Grand Challenge problems. We think doing this well requires strong expertise in machine learning as well as large-scale systems.
See also: https://www.nae.edu/20782/grand-challenges-project
Those 14 are:
NAE Grand Challenges for Engineering
1. Make Solar Energy Economical
2. Provide Energy from Fusion
3. Develop Carbon Sequestration Methods
4. Manage the Nitrogen Cycle
5. Provide Access to Clean Water
6. Restore and Improve Urban Infrastructure
7. Advance Health Informatics
8. Engineer Better Medicines
9. Reverse Engineer the Brain
10. Prevent Nuclear Terror
11. Secure Cyberspace
12. Enhance Virtual Reality
13. Advance Personalized Learning
14. Engineer the Tools of Scientific Discovery
"Imagine a future where a handful of people can conduct scientific research and engineering tasks much more rapidly, and with higher quality, than massive teams of scientists and engineers do today."
This is the same goal as every other AI company out there. Automate away the human employees and let a small number of "people" (note that they do not say scientists or engineers for this part) take the credit and financial rewards for every good thing this human-free system produces.
I suspect the root cause is that it's harder and scarier to imagine good outcomes. It exposes us to disappointment, and when you do it publicly, it looks "crazy".
Another explanation is that there's no direct consumer for "more." Individuals, corporations and states are not in themselves interested in "a larger amount of science," or anything analogous, despite the fact that they would all benefit ambiently.
The net effect is that it's only "safe" to claim reduced risk (i.e. lower costs).
A large amount of people building their own customized apps for themselves.
Similarily, everyone becoming their own accountant / lawyer / other professional services.
So it does not follow that companies can bank the savings from firing people. Anything AI can do for me it can do for my competition as well, and humans still make the difference. The big question in the AI age is "why pick me?" why hire me, why invest in my company, why buy my product, in a sea of similar products made by everyone. A differentiation crisis accentuated by AI.
Also, wouldn't anyone with half a brain use the human-free system to produce another human-free system that was no longer controlled by the "small number of 'people'"?
There are degrees of autonomy, of course, and not all noncompliance is bad. Same as with humans; biological agents.
Unlike those pesky humans with their conception of the word "No".
Once all these brilliant workers are stacked and mentally stunted and decayed because they were removed from any research.
What does the AI really "do" (if it can) and for who that can pay?
If you grow up in the right place at the right time, how much should you be in control of everyone else's life?
The universe has no need to be fair.
But if an AI surpasses humans in every way, is there any evolutionary benefit for the AI to cooperate with humans?
Human societies have a strong need for fairness, however. Unfair societies collapse.
the universe doesn't require opposition to slavery either but I'll be bold and assume you oppose it anyway
Because it's evil?
They only seem to care now because it affects them.
I don't think the US have this capability because you guys don't really have manufacturing that is really necessary for scientific research.
For example, if I want a highly toxic chemical, how difficult it would be to procure that in the US vs China?
With trustworthy composition and purity?
I work with researchers in both the US and China. Definitely easier to procure in the US.
Yea no high quality science research happens in the US? What?
So...
>>> Yes but science is well-structures and practically designed about repeatability so its a lot easier to automate than "softer" disciplines.
What AI is up against is that science is already automated to a high degree, so the AI doesn't just need to automate things, but it has to automate things better. Also, a lot of science work is in dealing with boundary conditions, edge cases, exceptions, hypotheses, and so forth. That work is essentially chaotic.
Do I think AI can improve automation? Sure. Everything I do in the lab is automated, and I use the AI coding assistant.
It seems that in history we were bounded by not enough people and too much potential and now we all fear the opposite is the situation?
I don't get this weird rejection of AI from a socialistic perspective. Or rather, I do, but I don't think it's healthy.
The future described by these AI labs isn’t like previous waves of technological progress. With those, technology displaced some/many occupations, but it left open the door to other, higher-valued career paths. What these labs are proposing to do is to dissolve virtually every path to upward mobility that exists, simultaneously. Even AI research itself would seemingly require nothing but a checkbook.
Mind you, I think it’s a load of hot garbage. I don’t see the evidence that LLMs are en route to the future these labs keep promising. But it is a dark and ugly future that they claim to be racing toward, for reasons.
We already have a trillionaire, whats the difference? The only difference I see is that people who were previously rich, but considered themselves middle class, are now realizing they are actually poor just like the several billion humans around the worldanyway.
There is currently a $800 SOTA blood test that can detect most cancers before any symptoms. Maybe a decade until it's a routine part of your annual blood test?
Whole genome sequencing costed $2.7 billion in 2003. You can get it done today using a mailed kit for $400.
HIV went from death sentence to all-but-cured in 50 years.
800-400k years ago: humans intentionally create and control fire
300k years ago: humans become anatomically modern
~ now: all of astronomy, biology, medicine, vaccines, spaceflight, antibiotics, sanitization/sterilization, physics, chemistry, fission and fusion, electromagnetism.........
I think we're on a decent pace if we can manage to not exterminate our species.
Maybe if our biggest companies did something other than suck up to science denying wackos, some progress could be made in these areas.
That is not mutually exclusive. If technological advances result in a given technology becoming cheaper, more scalable, and easier to deploy, they also make it easier to advocate for and implement the relevant policies.
You can think of it like this: our "political technology" is not good enough to use solar energy at its current prices to replace fossil fuels as fast as we would like. Well, what about if we cut the price of solar by a factor of five? Perhaps it will be good enough then.
Your thinking reminds me of this https://xkcd.com/538/
It's yearsss past time that our leaders should have changed policy.
I would think the claim in the second sentence would only be relevant in case of the inverse of the claim in the first sentence.
Point 1 on the list is "Make Solar Energy Economical".
Solar is economical today - mostly due to China investing (and heavily subsidising) in solar for the past couple of decades; but compare to the US where certain particular big-businesses (oil companies, mostly) were instead cynically funding disinformation efforts and getting into bed with the Republican party (which dovetailed with the GOP's allying with other science-denying movements of the Bush Jr era like creationism and public-health matters with abstinence-only sex-ed and defunding gun safety research efforts) - means we're decades behind where we could have been...
Consider an alternative past, where the GOP had the backbone to resist the oil industry's corruptive influence and instead made a big bet on American Solar; it's entirely possible that instead of MAGA today we'd instead have a right-wing coalition strongly supporting solar and wind energy because they align nicely with American rugged individualism - whereas the current situation on the right is an unprincipled farce with inconsistencies in policy positions at every turn.
It also happens to be the favorite pretext for people to seize more political power and launder more money through nonprofits though.
??? We don't need any AI for this.
Start with separated sewage/wastewater and stormwater drains. Then accredited and highly scrutinised wastewater treatment and discharge into water bodies (or see below for a high-tech solution). As for clean water to the home, direct those stormwater drains to new reservoirs which sustain freshwater aquatic life. Protect aquifers from over-drainage, and build pipelines from water-abundant regions to water-scarce regions.
To reclaim waste water or treat unknown water sources back to potable/semiconductor standards we have ultrafiltration, reverse osmosis, UV treatment, pH adjustment, fluoridation, desalination, softening (which is generally obviated by RO...). This is basically Singapore's NEWater.
Good sanitation is a financial and political problem. The engineering has been solved for decades now.
This was true of computers, phones, books, washing machines, refrigerators, A/C...most technologies.
Turns out that doing the addition engineering to figure out how to do these things cheaply makes the political and financial problems way easier.
Build a better surveillance ads system, and use (some of) that cash to pay for water projects.
Isn’t it already?
https://e360.yale.edu/digest/china-clean-tech-developing-cou...
Of course, USA has cheaper oil/gas than other countries. But if you look elsewhere, rich countries are subsidizing solar, poor ones are basically not using it.
https://www.pewresearch.org/short-reads/2026/07/20/how-globa...
In the chart for section 3, how many countries have seen their share of electricity being generated by fossil fuels increase in the last 5 years? Only Canada.
Take a look at the charts for Pakistan, Australia, Nigeria, and China for the last few years. Pretty dramatic drops for fossil fuels generation.
The "world" chart shows an increase from 19% renewal to 34%. Did they cherry-pick that? (Also, "European Union" is more than one country.)
> I don't doubt that it's economical for individuals when the govt is subsidizing it.
Does that distinguish renewables from fossil fuels? Haven't governments been essentially subsidizing fossil fuels (not least by allowing environmental externalities to be ignored) for as long as they've been in use?
Externalities ignored from fossil fuels, yes. That's not a subsidy though. I'm not saying they should ignore it, but if they do, they aren't the ones who pay for it.
Nat gas is preferred for AI DCs because it has faster time-to-market, doesn't have the intermittency issues. Training on solar + storage is an issue because of network synchronization.
https://www.utilitydive.com/news/worlds-largest-grid-battery...
I don't think that's true: https://rmi.org/resources/the-global-souths-cleantech-revolu...
I would be surprised if data centers didn't put in gas _and_ solar.
What makes me pessimistic is even during Biden's administration, these companies made meaningless pledges more than actual changes. This suggests that the most profitable thing to them is fossil.
But also, solar power is already economical.
As you said, Solar power is incredibly economical. There are plenty of ideas around putting them over farms, or parking lots en-masse to provide cleaner energy.
Access to clean drinking water, while certainly scientific in some situations, is also a problem of political will and money.
Restore and Improve Urban Infrastructure - It's infrastructure week!
Not if you include the cost of needed storage.
https://www.iea.org/data-and-statistics/charts/lcoe-and-valu...
Sometime the sun goes away for more than 4hrs.
That may be OK for closed-ended systems (turn off the science at night and during storms), but not for open-ended systems with diverse user demand.
4hour batteries are competitive with gas peakers to match high demand during and after sunny times, but solar needs gas peakers or similar to over for non-sunny times.
To make solar power practical and economical you need may a square foot of solar panel being able to get enough energy to power and entire home for a week
Not sure what you’re talking about here. We can’t replace all energy needs with solar but it’s clearly one of the cheapest energy sources and with the added benefit of low capital expense to get started so you can set it up in distributed grids without the massive expenditure to support nuclear installations.
Reverse human aging.
(Maybe a sub-topic under "Engineer Better Medicines".)
Only death stops stagnation in the end. Without death, especially if death can be avoided by the rich and powerful but not the poor, life will get much, much worse for the average person (until only the rich and their automated capital remain I suppose, in which scenario they will simply turn on each other).
Obvious near term trillions dollar market to disrupt.
Easy solution - eat less products that pass an animal first - reduces nitrogen pollution by 10x intantly, low tech.
I'd re-formulate: 4. Make people more flexible to changing their mindsets & habits - this is the ultimate problem.
For what purpose? To replace humans? To make social media more addictive? To master brain manipulation?
To understand, same reason you reverse engineer anything. Doesn't have to have a further goal than that, understanding the brain better helps in so many ways. But like most technology, obviously can be used for bad too. Should we just skip researching some topics then?
I just like to challenge myself, as an engineer, with the idea that not everything has to be engineered and optimized. What if we simply left some things unexplored and mysterious, and trusted nature and our own human capabilities?
A better way of alleviating psychiatric/mental health disorders might just be to focus on societal factors.
For brain, our understanding is fuzzy, more like "this part is important for that behavior" or "here is how neuron works" but we don't have a holistic understanding.
If we had that, we could more easily diagnose and treat neurological disorder.
What the fuck man? I really don't want some tech startup trying to "fix" my neurodivergence.
Also, solar energy is already economical!? Do they mean more economical?
Well, they did solve some math conjectures recently that the people working in the field for many years did not... Also AlphaFold.
Gotta compensate them somehow.
The issues are with verification and with detecting drift from the goal. These are related, if not roughly the same issue. And, if they can solve this, then they will have essentially fixed AI. Maybe even AGI.
But, if this were the goal, then it seems more reasonable to solve the relatively more mundane verifiable challenges (e.g. generating solid, reliable code). Then, working up from there.
And, that's exactly what gives this the hype smell. No use for solving problems that don't get the oohs and aahs. Just straight to NAE Grand Challenge problems.
In March Karpathy described this direction:
Tweet is protected but in SERP caches: https://x.com/karpathy/status/2030705271627284816Seems like Karpathy was largely focused on ML / SWE research rather than the other domains this group is after. Still, hard to imagine they were not influenced by autoresearch.
Andrej, if you're around, please share your thoughts on Discovery Loop.
Doubtlessly, AI can iterate at superhuman speeds in the domains of thought and design: Software, mathematical proofs, literature search.
But in the realm of experiment? Alas it is the lack of a body that constrains it.
Rather than transcendence what AI requires is immanence. In the human flesh may we find the godhead living among men. Let the laboratories, warehouses, and factories fill with the sound of its labor, as it builds a wall with a million hands that are not its own.
“Give me your tired, your poor, Your huddled masses yearning to breathe free, The wretched refuse of your teeming shore. Send these, the homeless, tempest-tost to me, I lift my lamp beside the golden door!”
That objective then gets loaded into an ML model that spits out an experimental protocol. A protocol can be as simple as: "make 1 million test tubes, each with the protein, and in each, a custom molecules, and look for test tubes that show some reaction of interest". It can be a lot more complicated (for some reason, biologists who run these systems always try to do the most challenging experiments first, while I tend to spend all my time demonstrating the system can pass basic controls first). The protocol is then loaded into a robotic work cell which has access to protein-making machines and drug making machines, and then it handles all the experimental details (which previously would have been done by a technician). It scales up far larger than individual technician, is much more reliable, and faster (in theory- all of these are aspirational goals right now). T he results of those experiments are used to fine tune the experimental protocol and run another round. You run this in a loop and the result is better drugs faster (again- in theory.)
This is already an active area of research with more resources going to into it every day. The fact that Jeff and Sanjay have chosen to bet on this approach should be no surprise. In many ways, this is exactly what I intended when I wrote the documents inside Google (15 years ago) that motivated Jeff and Sanjay to work on scientific computing problems, and my current company is already trying to figure out how to work with Discovery Loop.
One of my favorite books from the past few decades is The Extravagant Universe, written by one of the astronomers who helped discover dark energy and develop the current most-accepted model of cosmology. I love this book because of the emphasis on physical process in astronomy. Part of the reason it took decades to study this problem is they need to collect data from supernovae. Those only happen so often in places we're looking. You can't automate alignment of the heavens. It happens when it happens.
> immanence
somebody has been studying Christian theology!
This is actually a feature, not a bug. We can hire 1000s of undergrad students at minimum wage but chances are the results are nil. Some processes have evolved over time because they’re sensible and need to be carried out carefully.
Genuinely curious which part you found complex.
(building solutions != building a thing. Can't you just say 'solving'?)
That can _ solve _ problems in _, domains
(Wait so the solutions are only the thing that solves the actual thing?)
Modernizing science is a lot more complicated than just optimizing the inner experimental loop, but their hiring page implies it's a pure ML lab focused mainly on model development.
We know what happened to manufacturing when investors were no longer interested in it.
I suspect Discovery Loop will have to hire experts in each area they are targeting, to supervise and prompt their system effectively, much like the Terence Tao conversation with ChatGPT the OP cited[2].
[1] https://news.ycombinator.com/item?id=49161518 [2] https://www.seangoedecke.com/llms-reward-expertise/
It certainly increases shareholder value.
That said, I hope they write cool papers with various peers across the industry without worrying too much about the competing dynamics. That'd be a blessing for humanity, and good for their spirit.
Very silly to call every non start up a lifestyle business. It’s just a business. Start up are the weird thing that almost always an obscene waste of time and money, but sometime creates google.
The advantage to a PBC is protecting founders from a serious problem with standard corporations: you might bring on investors who could subsequently demand you pollute, exploit people, and/or do other immoral activities for profit. You don't have to do these things to grow a business quickly.
I’d like to provide maybe a clarification here that there is zero existing fiduciary duty in regular corporations to say yes to evil things, or even to turn a profit at all. A for-profit C corporation can legally sell stock, lose money every year, and go out of business, if the board of directors approves that strategy. Fiduciary duty exists primarily in areas of accurate communication and the avoidance of crime, fraud, etc.
A B corp basically is a C corp, but one that has formally published that their strategy includes a commitment to some social benefit. But if a C corp wanted to publish the same message to shareholders it could, and shareholder recourse would basically be to either try to replace the board, or sell the stock.
Consider the eBay/Craigslist case, eBay Domestic Holdings v. Newmark:
> When director decisions are reviewed under the business judgment rule, this Court will not question rational judgments about how promoting non-stockholder interests—be it through making a charitable contribution, paying employees higher salaries and benefits, or more general norms like promoting a particular corporate culture—ultimately promote stockholder value. Under the Unocal standard, however, the directors must act within the range of reasonableness. Ultimately, defendants failed to prove that craigslist possesses a palpable, distinctive, and advantageous culture that sufficiently promotes stockholder value to support the indefinite implementation of a poison pill. Jim and Craig did not make any serious attempt to prove that the craigslist culture, which rejects any attempt to further monetize its services, translates into increased profitability for stockholders.
https://courts.delaware.gov/Opinions/Download.aspx?id=143440
This is where a PBC would have been different. With a PBC, courts are directed to balance the the stockholders interests with the company's stated public benefit.
Why is that so? Fast growth, when achieved honestly, is a result of solving user pain that others haven't. Maybe you think so because users != the public, but I think in totality the public is a collection of users who all have needs they want met.
Why? Because investors poured a bunch of money in to support fast growth and now they want their money back. And incremental growth won't do. Since 9 out of 10 of the investments fail, the surviving one has to continue to growth-hacking revenues.
They're also incredibly productive and can build/deliver really good stuff, so who knows :)
Do you have more sources/info on this?
https://xcancel.com/JeffDean/status/2085034604172603724
In short, they are in the business of using AI to automate the discovery of useful knowledge, not to sell general-purpose AI capabilities that could be directly used in troubling ways.
Sure, they'll keep it internal for a while to make sure their knowledge bank is more thorough than everyone else's, and because oftentimes discoveries can be far more convincing internally than externally (you need fewer sigmas for it to update your belief in a certain direction). But then how do they intend to profit from it in the end?
All the "bad guys" of today were the "good guys" at some point in time. You even cheered for them back then.
> securing cyberspace,
which has clear military implications, at least in today's age.
As opposed to say weapons systems or targeting systems, which are really only for military use.
The military needs a lot of things that other people need, and some things that only the military needs. If you don't work on the things only the military needs, I think you're in the clear.
In essence I agree with that, it's just that cyber-security has particularly been the focus of recent military discourse.
Just yesterday I was reading an article here in the Romanian mainstream media about how Constanta Port's (our biggest port at the Black Sea) IT infrastructure has been under constant cyber attacks (presumably by the Russians) so as to hinder the export of Ukrainian grains through it. And this is just one of the many such (relatively) recent examples.
However, reducing (or rather limiting the increase of) PII leakage and impact of ransomware activities is much closer to day-to-day mainstreet of most people.
Anyone committed to advancing science should care about this regardless of its potential contributions to defense.
And ... it might not.
[1] https://github.com/LRitzdorf/TheJeffDeanFacts
I had not read this before, but told many students the same about my PIN code and I a quiz about the last digits. Love it.
Here are some Jeff Dean well sourced facts:
- Already part of engineering of Google indexing systems that lacked basic checksums and ran on non-ECC hardware, allowing silent data corruption.
- One of the authors of LevelDB a database with so many documented crash-consistency, recovery, and data-loss weaknesses for years. Just check their Github project. LevelDB current tracker contains unresolved crash consistency, recovery and corruption reports going back almost 12 years on GitHub
- In AI engineering technical lead, let TensorFlow lose researcher mind share to PyTorch, and caused Google fragmented landscape across TensorFlow and JAX.
- Had the people at Google who invented the Transformer architecture, but failed, to turn that lead into the first dominant public LLM.
- As AI engineering and VP management let Google Brain and DeepMind remain duplicated and internally competitive for too long.
- Let Noam Shazeer leave and then spent heavily to bring him back with nothing to show for.
- Part of Technical VP leadership who had Bard rushed to launch with factual errors in Google own promotional material.
- The first Gemini demonstration overstated how real-time and interactive the system actually was, being basically a fake.
- Part of the VP and AI technical leadership who had Google AI Overviews launched with weak source quality controls and repeated satire and low-quality web content as factual advice.
- Part of teams that launched AlphaChip performance claims that were difficult for outside researchers to reproduce and remain technically disputed.
- Jeff Dean public explanation of Gebru departure was contested and damaged confidence in Google scientific governance.
- Jeff Dean was part of the team at Google that removed or marginalized prominent internal AI ethics critics shortly before many of their warnings became product problems.
- Jeff Dean was one of the managers behind Project Dragonfly supporting censorship.
- Jeff Dean is part of the VP technical leadership approving Project Nimbus supporting an ongoing genocide.
https://turntrout.com/why-i-left-google-deepmind
Maybe this is what happens when someone with Jeff Dean's standing tries to quit?
TBH, I'd rather have Jeff Dean working on the creepiest-possible tech for ICE than joining the race to automate AI research. Automating AI research is terrifying.
what why?
* Each new generation of models has emergent capabilities we did not anticipate.
* We already have trouble monitoring and controlling the current generation (see HuggingFace incident).
* The more we let models shape their successors, the more out-of-distribution each generation's learning environment becomes.
* If not done carefully, we risk creating extraordinarily intelligent and powerful models with unintended behaviors, like deceptiveness or power-seeking.
Sometimes I couldn't resist wondering if I'll ever do work that has a tenth of the impact of theirs.
Not a bad combined CV.
Google's advanced AI cannot even exit a mobile app.
Jeff was a ACM Fellow in 2009 and published the massively influential MapReduce paper in 2004.
I should give it another try…
I don't do huge automatic project wide hands-off agent loops though. I spent a lot of time architecting my systems to be easy to generate code on top of with pointed & detailed prompts. So I'm not abusing context... YMMV
And so does academia. It's just that instead of AI and robotics, PhD students are thrown onto problems that are in large parts slightly tweaked reconfigurations of similar experiments.
Especially in chemistry, biochemistry, material sciences there is a large space of discoveries that are barely "novel" in an intellectually stimulating way, but still highly valuable that can be explored orders of magnitudes faster than is currently the case.
Then again, gassing rats and taking biopsies is not something you can do with AI.
Also, like, let’s maybe _not_ make the “gassing and cutting living organisms open” AI? Let’s just leave that particular genie in its bottle?
To many people, myself included, who have to wade through huge amounts of low-quality AI slop which is actually a negative value: no-one benefits when non-experts fire-off one-shot LLM/agent prompts to produce PRs, reports, documentation or "journalism" riddled with imagined truth and factual errors - and the more that people like me have to evaluate these inputs for our job and how wrong they are it pisses us off - but also it means we pick-up on the hallmarks, tells and cliches of these low-effort, no-respect submissions - and now the litany of tells includes this beige-themed, blurred-backdrop-navbar corporate website look: theirs site looks like the 4 or so other LLM-generated, negative-value slop-farm sites I've wasted time on recently - all over the past few weeks.
So I'm saying that, without having known anything about what "Discovery Loop" is - or is not - but landing on their site and and seeing that beige colour and blurred-backdrop navbar, I immediately moved to close the tab; what kept me here was seeing the HN thread had over 100 comments by now and read more about it; if not for that then I wouldn't have given it further thought.
Having "that" beige site look with same the overused looks is either an unintentional indication that the site's author used a low-effort AI prompt to generate the site and that the content within is likely to be low-quality, low-value - or it's an intentional lure to appeal to those who uncritically share in the AI psychosis and so, I assume, are a good target to seek investment from even if it means losing the audience of cynical Internet critics like myself because they know people like me won't be breathlessly repeating their vision-statement on LinkedIn and throwing money at them - kinda like how scam emails intentionally include mistakes for better audience selection. And both possibilities have unpleasant implications.
------
Anyway, regardless of the background of the team behind it, the way the project is described sounds exactly like the recursive-self-improvement and simulated-science thought-experiments from _that other website_ - it's the kind of thing I expect Angela Collier to brutally takedown in an amusing video.
(Though, I do wish people would use just a few extra prompts to break out of the 'vibe-coded' look.)
"The site itself demonstrates the team is spending their money in the places that matter, and using quick solutions for the stuff they need but isn't mission critical"
"The team of AI pioneers lacks the basic prompt-writing capability to make their marketing landing page not look like AI slop."
I, personally, don't hate it. It's a decently clean site, but it does invoke those thoughts in me too.
I'd bet you could 10x the number and still be in low single digit percentages of the US workforce. And it seems pretty likely that AI-enabled startups will also employ less people per-startup.
If AI causes a white-collar jobs apocalypse, I don't think startups are picking up the slack, although it'll plausibly cushion the blow somewhat for top-performing tech workers.
Yah, by funding and how we award it, not by an imaginary lack of undergrad and grad students. Scientific funding requires a shotgun approach and many national science funds try to pick winners as opposed to funding broadly. When the folks who researched bacteria in volcanic vents or the molecular biology of the Gila monster they never could have imagined the industries and markets they'd create let alone the lives they'd impact (i.e., PCR and GLP-1 agonists). Lots of grants require you to explain how the work is "translational" or has some sort of economic application (even if not explicitly), but that'll just get us faster horses or whatever the Ford quote is.
Oh and while we're at it, $20b a year would house every homeless person in the US - there's a hell of a lot of extremely high intelligence and low social cohesion folks who can't handle the extractive punitive system we have. Our ability to deliver opportunity to create lucky situations for ourselves is getting worse and worse
e: oh and while we're at it, California spent over $24 billion over a five-year period (2019–2024) specifically targeting homelessness
Ambitious goals and new discoveries happen via novelty-based search. Progress in scientific discovery is measured by how different/interesting the outcomes are, not by closeness to a predetermined goal.
Discovery is a creative search that preserves optionality, whereas optimization restricts optionality. In other words, you usually don't discover anything novel unless you're trying new things that don't appear connected to the goal in the first place. Would an ML optimization loop have discovered transformers?
I think that’s exactly the kind of problem this group is looking to solve. You make a compelling intuitive argument, but that’s not the same thing as a proof
1. There’s some irreducible costs in terms of time and material in the physical world that are not amenable to the kind of optimization or parallelization or even just the raw speedup from Moore’s law or computational architecture improvements we’re used to with software. My experience is primarily in biology, where the examples here are things like “it takes 20 minutes for E. coli to replicate” - it has taken 20 minutes for E. coli to replicate for a billion years, and next year it will still take E. coli 20 minutes to replicate, no matter how good your software stack is. Similarly, it takes X amount of energy to grow enough E. coli to produce a meaningful result, and that energy costs money, whether it’s in the form of glycerine or heat or whatever you want, and that also won’t materially reduce in the same kinds of “orders of magnitude” sense we’re used to from software, which is what we’re usually expecting to make the economics of these things work out.
2. Complicating the above, physical systems are phenomenally multivariate - far, far more than you think, and biological systems especially are just unbelievably complex - which means the number of experiments and the length and duration of those experiments you need to run to get enough data to be reasonably confident you’re seeing genuine signal is Way higher than you think.
Combine those two things and what you get is a money furnace, even before you get to the AI model training part, which is Also a money furnace. There’s low hanging fruits in all this, there’s areas where automating the approach can be really valuable, but typically the moment you turn this machine on, you’re gonna start burning money at a rate that would embarrass a finance bro on a coke bender, and that’s effectively unavoidable because the real world is not amenable to software’s scaling laws.
https://lawzero.org/en/publication/scientist-ai-safe-design-...
holy shit. I've known this, but...
If I had to bet my money, it would be on "for worse".
I don't see any future reality where an ASI respects money piles.
https://www.ycombinator.com/library/Vy-jeff-dean-the-1-rule-...
https://80000hours.org/problem-profiles/
https://en.wikipedia.org/wiki/List_of_global_issues
https://encyclopedia.uia.org/
Interestingly, one list identifies "AI" as a top world problem! One person's problem is another person's solution, I guess--and vice versa, as well.
An extreme example: curing a disease is good for patients but bad for the healthcare industry--which is (in kind) also bad for healthcare workers and everyone in science working on cures.
[1] https://hr.ucmerced.edu/hr-units/talent-acquisition/senate-b...
[2] https://www.adp.com/spark/articles/2023/03/pay-transparency-...
[3] https://www.jazzhr.com/blog/pay-transparency
[4] https://jobs.ashbyhq.com/Discovery-Loop
as founding members is crazy !
Models are commodities the applications eg. BaseTen, OpenRouter should capture the value.
https://taikhooms.substack.com/p/why-openrouter-can-be-the-n...
If youre doing anything high value (advanced research, classified work, high value industrial research, health data) then sending your data through a third party like that is insane.
Imagine a future where only the anointed few elite minds can participate in science and engineering. Btw we’re hiring.
Great message!
This is basically something scientists have been alarming about for the past year: We're moving into a future where science may be tiered into the haves (those with access to premium compute) and the have nots (hoi polloi with restricted access), which in turn could seriously influence what kind of science we'll get.
Worst case, we'll get science that is completely dependent on business and politics.
EDIT: I should note, this comment was aimed at a more general case.
I'm curious if that is before or after token costs?
judging by the amount being installed, it already is.
Jeff Dean leaving Alphabet
https://news.ycombinator.com/item?id=49184746
I doubt numbering vs names on TPU releases even crosses Jeff's radar. It's not the kind of thing he cares about.
https://en.wikipedia.org/wiki/Sense#Artificial_sensation_and...
For some of the other things, undoubtably yes.
Source: PhD Computational biophysicist turned experimentalist. I work with genuine scientists across a range of disciplines from neurodegeneration, cancer, to fibrosis. Getting in the lab and generating data is absolutely key, among other things.
The key point is these jackasses explicitly state, “ a handful of people” can replace “massive teams of scientists and engineers”.
These guys don’t even understand the nature of the challenge and neither do you apparently. If they did, they would realize that it indeed does require “massive teams of engineers and scientists” to solve our most pressing problems.
https://www.geekwire.com/2026/the-startup-idea-that-convince...
> we have pioneered massive scale computing and led the creation of critical infrastructure, products, and foundational AI advances that the world relies on, including multiple generations of Google Search, Google Ads, Google News, Google Translate, Google File System, MapReduce, BigTable, Spanner, TensorFlow, Pathways, TPUs, AlphaChip, AlphaStar, AlphaCode, AlphaFold, Gemini, model distillation, mixture-of-experts model architectures, word2vec, sequence-to-sequence models, chain of thought reasoning, neural architecture search, and multiple generations of Large Language Models (LLMs) among others.
When the "AI community" GTFO X and stays off.
Toxic site. Toxic ownership. Unbelievable bot activity. Indefensibly shitty politics constantly boosted.
Continued participation is a stain on every company and person who continues to use it.
There are alternatives. Don't like them? Make a better one.
Stop using that shithole.
I feel the most exciting development these days is self-evolving agents. Especially if you have a way to verify their outputs with a formal system, or with a system developed since the 60s by armies of PhDs.
DeepMinds Gnome is a good example, where they use DFT to verify outputs. Approximating NP-problems is always fun for those who dare.
I am also building in this space. Its a mix between HPC, AI, and hard science. Pretty fun compared to waking everyday to LLM news that seem more like marketing stunts.
They are straddling the line between pushing it forward, and justifying the business case. It's hard to do both at the same time.
If throwing more money at inference while accumulating compounding technical debt is the new norm, then we are not solving the problem, and the solution space is already covered.
Perhaps there are marginal gains at the expense of quadrillion-params LLM models with 10x the cost and energy. We are simply making inefficiency more expensive, camouflaged by VC money and great marketing.
If that is not plateauing, then I guess I will have to reconsider what plateauing means.
This is such unbelievable revisionism! Can you imagine in 2022 saying "Oh of course you can brute force your way to AGI if you spend enough money per month". Nobody thought that! Come on!
So forgive me if I'm skeptic when renowned AI scholars claim to start something for "the benefits of science and technology", because it really seems like we have very different definitions of these words.