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cjbarber 4 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.
sejje 50 minutes 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 27 minutes 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?
beloch 4 minutes 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.
nwienert 38 minutes 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 2 minutes ago [-]
There is no "should" there are only "is" or "is not"
The universe has no need to be fair.
Sivart13 3 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 2 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.
qwertygnu 1 hours ago [-]
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.
bossyTeacher 23 minutes 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.
Making progress requires first not dismissing your ideological outgroup along such lines, and instead trying to understand what actually motivates them.
podgietaru 3 hours ago [-]
Policy and funding. One of which will be sucked up by this venture.
floatrock 1 hours ago [-]
Hey now, our biggest companies do more than suck up to science denying wackos, don't be so unfair... sometimes our biggest companies fund their wacko superpacs!
tbrownaw 3 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 2 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 2 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 35 minutes ago [-]
Improving panels or batteries (e.g. through automated material discovery) would make solar energy economical in a lot more regions.
holmesworcester 2 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 2 hours ago [-]
Solar is profitable to install at both industrial and home scale in most areas. You're moving the goalposts.
xnx 33 minutes ago [-]
It would be even better if it had ROI in 2 years instead of 10 for northern installs.
marcosdumay 1 hours ago [-]
Where do you find the information for 2026?
2 hours ago [-]
ivanovm 1 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 3 hours ago [-]
[flagged]
delta_p_delta_x 15 minutes 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.
michaelbarton 6 minutes 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 2 hours ago [-]
> Make Solar Energy Economical
Isn’t it already?
glenstein 1 hours ago [-]
Definitely pretty far along imo. But maybe they consider the progress bar to be at 75% or 80% rather than 100%.
Marha01 2 hours ago [-]
Not enough. The more economical it is, the better.
frollogaston 1 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 1 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.
zahlman 10 minutes ago [-]
Oof. What's going on here in Canada with that recent uptick? Last I checked it seemed like all the trends were good.
frollogaston 57 minutes 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.
blahblaher 33 minutes 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 27 minutes ago [-]
Australia is a rich country that subsidizes solar
ravst3s 54 minutes 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 41 minutes ago [-]
I get the gas turbine for semi-temp power when there's not enough grid support, but they're talking about doing this long-term: 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?
"RMI drives investment to scale clean energy solutions"
jay_kyburz 27 minutes 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.
LogicFailsMe 3 hours ago [-]
Sandbox 2.0
But also, solar power is already economical.
podgietaru 3 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 2 hours ago [-]
> As you said, Solar power is incredibly economical.
That's going to drop a lot as sodium-ion batteries go into large-scale production.
RajuChacha108 2 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.
In some regions, but it would be great if it was economical in cloudy Seattle and not just the sunbelt
glaslong 3 hours ago [-]
At this point the Hard Problem is policy to get out of solar's way.
staplers 3 hours ago [-]
3. Develop Carbon Sequestration Methods
If only we could invent a solar-powered, self-replicating, carbon-stacking, habitat-building machine..
marcosdumay 1 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.
twothreeone 3 hours ago [-]
Yes, plant more trees!
rush86999 3 hours ago [-]
That's what he was trying to imply
vovavili 2 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.
koolala 3 hours ago [-]
Room Temperature Ambient Pressure Super Conductors
zahlman 18 minutes ago [-]
In what sense is solar energy not already economical?
epicureanideal 3 hours ago [-]
Would be great if they'd add:
Reverse human aging.
(Maybe a sub-topic under "Engineer Better Medicines".)
dag100 2 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).
dbgrman 3 hours ago [-]
Why is "12. Enhance Virtual Reality" in there? T_T
cheschire 1 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 3 hours ago [-]
I guess if we failed to Prevent Nuclear Terror the bunker denizens of the future are gonna need somewhere to hang out.
cm2012 15 minutes ago [-]
You dont see making heaven on earth worth doing?
xnx 29 minutes ago [-]
Higher-fidelity telepresence could be as significant as the recent COVID work-from-home wave.
embedding-shape 1 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.
dgellow 2 hours ago [-]
Such a weird list. How is preventing nuclear terror an engineering problem?
vanviegen 52 minutes ago [-]
Satellite/drone detection of nuclear material? Shooting missiles out of the sky?
jay_kyburz 25 minutes ago [-]
We know where all the bombs are. They are connected to a button on Trumps desk.
lovlar 3 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 1 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 36 minutes 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.
tantalor 2 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 2 hours ago [-]
I imagine a good model of the brain would contribute enormously to alleviating psychiatric/mental health disorders.
RajuChacha108 3 hours ago [-]
To do human brain activities at scale.
willy_k 2 hours ago [-]
So the second option then.
fcarraldo 2 hours ago [-]
This is called a “corporation”
sajithdilshan 3 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 2 hours ago [-]
agreed
mrdependable 3 hours ago [-]
Which engineering discipline touches most of these?
la64710 3 hours ago [-]
Please add fixing neuro issues like autism add etc on the list. It creates a huge burden on families.
hiddencost 2 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.
tcp_handshaker 4 hours ago [-]
Acquisition back by Google in 3 years, with nothing to show for it. VCs will make a ton.
returnInfinity 3 hours ago [-]
Google stock would drop big if this new company was being funded by competitors
tgma 4 hours ago [-]
and... the VC is Google.
Gotta compensate them somehow.
ex1fm3ta 3 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 2 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 28 minutes 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 21 minutes 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.
DataDaoDe 4 hours ago [-]
My thoughts exactly
dude250711 4 hours ago [-]
For all we know, they could have been successfully working on "10. Prevent Nuclear Terror" for the last 80+ years.
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 8 minutes 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 2 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.
drivebyhooting 3 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!”
would love to see how AI can automate the construction of the next high energy particle collider
scrlk 3 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 2 hours ago [-]
But I always wanted to try headcrab souffle.
nonameiguess 3 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.
mbonnet 3 hours ago [-]
> transcendence
> immanence
somebody has been studying Christian theology!
cute_boi 3 hours ago [-]
Beauty of human writing.
DaiPlusPlus 2 hours ago [-]
More like someone taking LessWrong postings too seriously.
nxnxj 3 hours ago [-]
[dead]
numbers_guy 3 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.
danielmarkbruce 3 hours ago [-]
Building "simulators" that use ML/AI instead of running the calculations every step is a thing.
ramon156 4 hours ago [-]
"Our mission is straightforward" continued by the most complex sentence on that page. Wondering what the definition of straightforward is now
pphysch 3 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 3 hours ago [-]
Yeah. ML is all well and good, but how are they going to do the science their machines design? Atoms cost money.
pelagicAustral 3 hours ago [-]
Really seems to embrace the "Making the world a better place by <<extremely convoluted, highly technical, jargon loaded mission statement>>"
pickleRick243 2 hours ago [-]
Which part of it is highly technical or jargon loaded?
Grosvenor 35 minutes ago [-]
I think it was a Neal Stephenson quote from cryptobimicon.
It certainly increases shareholder value.
dgellow 2 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…)
tmoertel 3 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 2 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 21 minutes 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.
moralestapia 1 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.
wavemode 1 hours ago [-]
Like how OpenAI is (was?) structured as a nonprofit?
paganel 3 hours ago [-]
There's this somewhere on that page:
> securing cyberspace,
which has clear military implications, at least in today's age.
jedberg 1 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 3 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 34 minutes 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 3 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.
flakiness 4 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 4 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 3 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 56 minutes 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.
mgfist 3 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 3 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 4 hours ago [-]
Fair point. Their page doesn't list any investors.
valleyer 3 hours ago [-]
The Times article lists several.
2 hours ago [-]
wavemode 59 minutes ago [-]
It can be both. Bell Labs performed a lot of speculative research while still producing economically valuable technology.
sarjann 3 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 4 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 :)
jszymborski 1 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 43 minutes 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 4 minutes 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 57 minutes ago [-]
Yes! But if science is bottlenecked by funding, making it cheaper might help?
woeirua 48 minutes ago [-]
Not really. Grad students are already essentially working for free.
tjwebbnorfolk 36 minutes ago [-]
How many lavishly-paid deans and bureaucrats and administrators are employed for each grad student?
gtirloni 58 minutes 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
arjie 4 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 4 hours ago [-]
> It might be a new scientific revolution to have computer-driven discovery.
And ... it might not.
arjie 4 hours ago [-]
True, nothing might be anything. But I'm an optimist :)
jbmchuck 2 hours ago [-]
Sure - and knowing what is not possible with current tech is a nice datapoint to have.
holmesworcester 2 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 2 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 2 hours ago [-]
> Automating AI research is terrifying.
what why?
wy1981 4 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 24 minutes 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 3 hours ago [-]
[dead]
gosub100 3 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.
allthetime 3 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 2 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 2 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 8 minutes ago [-]
How does this comment relate to the parent comment?
16bytes 2 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.
ValentineC 4 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 4 hours ago [-]
0000 in base pi. Oh Jeff.
4 hours ago [-]
tcp_handshaker 3 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 3 hours ago [-]
I suppose you think Chuck Norris Facts are fake too.
3 hours ago [-]
bonsai_bar 3 hours ago [-]
You sound like you're quite jealous of him.
root-parent 3 hours ago [-]
I had never heard of many of these, was surprised, went to research, and so far, the list seems correct.
dekhn 2 hours ago [-]
Actually the list is technically accurate. So maybe it's sour grapes, but it's correct sour grapes.
twister2920 3 hours ago [-]
not sure how you got that from a long list of criticisms
stephantul 4 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 4 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 4 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 3 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 2 hours ago [-]
Unfortunately, that's most of science. I don't see these AI systems doing reproducible experiments in "meatspace" any time soon.
porridgeraisin 4 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 3 hours ago [-]
The purpose of hiring grad students isn’t to advance science, it’s to train experts.
porridgeraisin 1 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.
pickleRick243 2 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.
...
tcp_handshaker 4 hours ago [-]
Lets keep your comment out of the VC pitch deck shall we?
4 hours ago [-]
GodelNumbering 3 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 2 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.
4lx87 3 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?
Johnny_Bonk 4 hours ago [-]
For sure made with Claude code for front end, but I’m excited to see where they go
claiir 4 hours ago [-]
The site itself is really leaning into the “made with Fable” aesthetic
pelagicAustral 4 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 2 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.
DaiPlusPlus 2 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.
3 hours ago [-]
slopinthebag 3 hours ago [-]
Because it’s lame and aesthetics matter.
make3 3 hours ago [-]
it's just a low effort snark comment, don't overthink it
swalsh 3 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 3 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 3 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 2 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.
IshKebab 3 hours ago [-]
At least it isn't dark purple.
roughly 3 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.
maCDzP 21 minutes 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 19 minutes 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?
ggcr 57 minutes ago [-]
> Oriol Vinyals, Sanjay Ghemawat, Jeff Dean, Quoc Le
as founding members is crazy !
swalsh 4 hours ago [-]
By the middle of the 2030's the world we live in will be unrecognizable.
kingofthehill98 4 hours ago [-]
I agree, for better or for worse.
If I had to bet my money, it would be on "for worse".
dude250711 3 hours ago [-]
It will not be owned by top 1%?
swalsh 3 hours ago [-]
That seems to be the one unchanged variable of time.
roughly 3 hours ago [-]
That’s a policy decision, don’t let them convince you otherwise.
warkdarrior 1 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 2 hours ago [-]
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1 hours ago [-]
melodyogonna 4 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 4 hours ago [-]
Google is backing it.
4 hours ago [-]
FailMore 4 hours ago [-]
Google down $160Bn so far since the leaving announcements. Those are some valuable people!
IAmGraydon 4 hours ago [-]
Google is literally at the same stock price it was on Monday. This is a normal daily fluctuation for them.
xuehaohu 25 minutes ago [-]
Big news aside, it feels exciting to see them leave and pursue startup. They could have stayed back, and retire
varjag 29 minutes ago [-]
Discovery systems are making a comeback huh.
flakiness 4 hours ago [-]
> 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...
Noe2097 3 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 :)
3 hours ago [-]
puttycat 1 hours ago [-]
What's the business model of these startups?
montebicyclelo 4 hours ago [-]
Did the ycombinator podcast which included giving advice to startup founders just a few days ago:
Is it a very hard problem to solve that jeff and the other legendary engineers have decided to quit and start on this?
thisoneworks 2 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.
I don't see the salary (on mobile). Isn't there a law stating it must be added?
guessmyname 3 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.
syntaxing 4 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 4 hours ago [-]
They're structuring the new company as public benefit corporation.
an0malous 4 hours ago [-]
Does this mean anything besides for corporate virtue signaling?
danielmarkbruce 3 hours ago [-]
Automating ML/AI research seems completely tractable. Most of the other claims seem much less doable.
3 hours ago [-]
deerstalker 4 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 3 hours ago [-]
Why? Science is wildly unprofitable on the scale of an individual private firm.
Taikhoom2010 4 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 3 hours ago [-]
I think Google's branding was starting to be too poor in AI to get top talent, they needed the refresh
malux85 4 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 3 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 26 minutes 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.
adfm 3 hours ago [-]
FHE
omederos 55 minutes ago [-]
What a team.
kulsumshannan 3 hours ago [-]
This seems interesting! I wonder how this will play out.
Wonnk13 1 hours ago [-]
not that it really matters, but is he leaving Google?
4 hours ago [-]
7e 8 minutes ago [-]
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.
thatsadude 2 hours ago [-]
This is “google brain”
claiir 3 hours ago [-]
The job req has "Recursive Self-Improvement" as one of the "area of expertise" checkboxes lol
paxys 3 hours ago [-]
It is targeted at a dozen or so people at OpenAI and Anthropic, not you or me.
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 4 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 55 minutes 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.
1970-01-01 4 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 3 hours ago [-]
I'm almost certain the goal of this startup is to make physical automated research labs guided by RL
XenophileJKO 4 hours ago [-]
How is that different than video input?
1970-01-01 4 hours ago [-]
There are over 2 dozen known senses to reality. Video input is a fraction of a sense.
The AI designed italics on thin font is hard to not see as slop.
aaronharnly 2 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 1 hours ago [-]
They would argue they are focused on more important stuff, but marketing shouldn't be underestimated.
4 hours ago [-]
aykutseker 2 hours ago [-]
[flagged]
yddryhry 4 hours ago [-]
[flagged]
daishi55 3 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 3 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.
mosfets 4 hours ago [-]
Is this a joke? Site is not loading for me.
galoisscobi 3 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!
calufa 4 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 4 hours ago [-]
Sounds like you get your news from 2024 when people thought things were plateauing after GPT4?
zuzululu 4 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 4 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 4 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 3 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!
> 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.
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'"?
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.
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.
It's yearsss past time that our leaders should have changed policy.
Your thinking reminds me of this https://xkcd.com/538/
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.
Isn’t it already?
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.
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.
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.
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...
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).
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.
Gotta compensate them somehow.
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!”
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!
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.
It certainly increases shareholder value.
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.
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.
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.
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 :)
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
And ... it might not.
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?
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.
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
Jeff was a ACM Fellow in 2009 and published the massively influential MapReduce paper in 2004.
[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.
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?
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.
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?
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.
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.
I'm curious if that is before or after token costs?
as founding members is crazy !
If I had to bet my money, it would be on "for worse".
holy shit. I've known this, but...
https://www.ycombinator.com/library/Vy-jeff-dean-the-1-rule-...
[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
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.
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.
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.
Imagine a future where only the anointed few elite minds can participate in science and engineering. Btw we’re hiring.
Great message!
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!