Discovery Loop(discoveryloop.com) |
Discovery Loop(discoveryloop.com) |
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.
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.
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!
* Is there a better way to do matrix multiplication?
* Could less reliable chips perform better in aggregate?
Ideally, you can simulate everything from first principles. That works well enough only for a rather limited set of systems.
More typical is that you need to do real world measurements/model (not LLM, but a model of what you simulate) validation before you can reasonably simulate.
And then there is biology and psychology ...
judging by the amount being installed, it already is.
For some of the other things, undoubtably yes.
I'm curious if that is before or after token costs?
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...
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.
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.
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.
Or they're going to try to build much bigger LLM's which are smarter.
The former isn't very defensible, won't work super well due to current models not discovering very many things per billion tokens.
The latter turns them into any-old AI company.
I don't normally bet against Jeff Dean, but in this case I'm not so sure.
They probably already got 10,000 resumes in the past 24 hours, wonder what they do and how effective this is.
Anyone already apply there, what was the process?
https://www.ycombinator.com/library/Vy-jeff-dean-the-1-rule-...
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.
[1] https://hr.ucmerced.edu/hr-units/talent-acquisition/senate-b...
[2] https://www.adp.com/spark/articles/2023/03/pay-transparency-...
Jeff Dean leaving Alphabet
https://lawzero.org/en/publication/scientist-ai-safe-design-...
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 would love to see someone with a strong natural science background in those efforts.
No one would build a house without an architect.
https://80000hours.org/problem-profiles/
https://en.wikipedia.org/wiki/List_of_global_issues
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.
as founding members is crazy !
https://www.geekwire.com/2026/the-startup-idea-that-convince...
Oriol Vinyals was a co-author of AlphaFold.
Once you move up to protein-protein interactions in living cells, post transcriptional modification, epigenetics, lipidomics, glycomics, and the the arrangement of said cells into the 3D tissue environment, and then into organs and complex biological organisms, all of which have a paucity of good training compared to what we possess in the protein folding domain, the problem becomes computationally intractable. We need to get in the lab.
You tech bros are entirely ignorant of these challenges and are making fools of yourselves.
> 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'"?
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?
So...
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.
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.
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.
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.
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?
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.
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!
3. Develop Carbon Sequestration Methods
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?
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.
Also to leave Meta, Amazon, Microsoft and everywhere else.
There would be more people who wouldn't join Google, but would love to do this instead.
He is also rich beyond dreams of avarice and can do basically whatever he wants, but apparently he decided to go hack some more with his buddy Jeff. There's a famous New Yorker story about them: https://www.newyorker.com/magazine/2018/12/10/the-friendship...
In March Karpathy described this direction:
The next step for autoresearch is that it has to be asynchronously massively collaborative for agents (think: SETI@home style).
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.
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 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.
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.
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?)
And ... it might not.
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.
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.
We know what happened to manufacturing when investors were no longer interested in it.
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.
Or to take another example, Make Solar Energy Economical
How does Discovery Loop make this go faster in a way that a different group of scientists, also using frontier models, will proceed?
I'm sure Discovery Loop has considered this and has good answers to this question. I'd be interested in hearing more about this.
As anyone who works with agents daily can attest, 1) you can use agents to help with hypothesis refinement, bridging into areas adjacent to your expertise, etc. 2) once you have a rigorous /goal definition you can parallelize and let the agent crank.
It seems pretty obvious to me that with the right actuators and sensors you can apply this to real physical research loops too. (To be clear, this is not easy; a lot of bench work is Métis and needs experts in the loop at every stage.)
To your point, you can’t make plants grow faster but you can increase research throughput by enabling a researcher to have 10x or 100x as many experiments going at once.
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.
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.
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.
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.
Jeff Dean: https://scholar.google.com/citations?user=sdcsQb4AAAAJ
Sanjay Ghemawat: https://scholar.google.com/citations?user=0KF6ZC8AAAAJ
Quoc Le: https://scholar.google.com/citations?user=vfT6-XIAAAAJ
Oriol Vinyals: https://scholar.google.com/citations?hl=en&user=NkzyCvUAAAAJ
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
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.
> 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 problem is that for this to actually become true, compute needs to become commodity again, otherwise this capability will select for people and environments with oversized pockets.
While “useless” might be a harsh term, surely he is onto something in attaching a higher value to the process that produced a result than the result itself.
What if “science” wasn’t about the results? What happens if you keep the “plans” but drop the “planning”?
I deeply wonder how AI will impact our personal ability to remain cognitively agile and adaptable.
Personally I notice myself becoming more abstract and being less interested in details. The cognitive movements I make cover more surface area so to speak, but I wonder how long that’ll last and what happens to a mind if it never was allowed to wade in “useless” details for a decade or more.
I know AI is "smart", so it might hinder us there, but I doubt it can be as damaging as doomscrolling has been on human brains.
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
They are occupying a term in their headline messaging that is much broader than they can actually cover.
A common pattern these days. Overclaim, attract attention, iterate.
I do feel that it's exciting to see what AI will be able to do to help research and discover new things.
My gripe is with their messaging. Because a lot of people will misinterpret that, including politicians, possibly to the detriment of good science.
This one is already solved, right? The price of panels and batteries is on trend to displace all other forms of power generation within our lifetime
Batteries are still open. While they do get cheaper, there is still a lot of room to improve. And battery chemistry is something where a lot of research, trial and error, healthy intuition is necessary. I'd say that is more a field where an AI based approach might make sense.
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.
2. Provide Energy from Fusion - See 1
3. Develop Carbon Sequestration Methods See 1
4. Manage the Nitrogen Cycle - See 1
5. Provide Access to Clean Water - See 1
6. Restore and Improve Urban Infrastructure - See 1
7. Advance Health Informatics - See 1
8. Engineer Better Medicines - See 1
9. Reverse Engineer the Brain - See 1
10. Prevent Nuclear Terror - See 1
11. Secure Cyberspace - See 1
12. Enhance Virtual Reality - See 1
13. Advance Personalized Learning - See 1
14. Engineer the Tools of Scientific Discovery - See 1
FF is the real threat in time, money, health. Can't sweep aside that it will destroy most life on Earth and we'll never get to the other things if we are at the mercy of FF
Little more than "Fossil Fuels are the root of all evil" performative bullshit.
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.
Obvious near term trillions dollar market to disrupt.
That is already solved.
> Develop Carbon Sequestration Methods
That is not necessary, because 1 is solved.
> Reverse engineer the brain
What for? There was already the european human brain project, which didn't do anything useful.
> Prevent nuclear terror
Easy one: Every country stops developing nuclear weapons and destroys existing ones.
It seems this list itself has many flaws. Maybe we need a bigger computer which figures out the questions we really need to ask.
We’ll face a bigger problem sooner rather than later, which is population collapse. Youth don’t procreate amy more. Birth numbers are at an all time low. We see the issue arise in rats and the experiment is all too relevant for the current age of social media and fearmongering (John B. Calhoun’s rodent “utopia” experiment). All these “Grand Challenge” problems seem trivial to that.
Furthermore: Why is 1 here when 2 is present. Again, solar is usually not relevant when we want power when it’s dark… even theoretical it wouldn’t work. We’d need a high capacity dirt cheap storage, and even then we can’t keep it till winter when there’s no sun to go around and effectively supply 3. Irrelevant when there’s population collapse. And even then, why would we want this instead of reforestation and low depth water protection from fishing and environmental issues.
5. How is this even a problem. Unless we got corrupt(ed/able) governments (read: lobbies) that allow exemptions in every law designed to protect the environment (also, settlements are a twisted way to fill governments pockets instead of rooting out evil) 7/8/9 the inverse effects are even worse health, as everything is fixable. 9 would incur even more social isolation, more so than the internet did 10 seems to be the first that’s actually reasonable Same for 11 For 12 see 9 13 yes but that’s something that a self learner would already be able to do. AI is at a level that we can manage
/rant
16. Make Everyone Nice
17. Finally Impress a Girl
Plus it should be plain to see how complete the solution is to 14, whether it will be fully solved, or almost completely, before diverting resources toward moving up the list to tackle other worthwhile objectives. If not fully solved I would not call that abandonment, but nobody could deny it would amount to an intentional slowdown regardless.
I still remember the day when Google became available on the general internet, and it's been a while. Take it from an old science dude, a lot can be detected over decades of observation that you can not get any other way. Under laboratory conditions or not ;) Looking at the list there are a few standouts that I can't imagine Google wouldn't be worlds ahead by now if they had only doubled-down on the "Don't Be Evil" mission every time they had the chance, rather than watering it down as we have seen.
Naturally I'm biased after doing 14 my whole life without real justification for moving up the list myself, since I still have no complete solution, I'm only human after all.
1. Make Solar Energy Economical — https://github.com/orgs/HardisonCo/projects/194
2. Provide Energy from Fusion — https://github.com/orgs/HardisonCo/projects/206
3. Develop Carbon Sequestration Methods — https://github.com/orgs/HardisonCo/projects/196
4. Manage the Nitrogen Cycle — https://github.com/orgs/HardisonCo/projects/197
5. Provide Access to Clean Water — https://github.com/orgs/HardisonCo/projects/195
6. Restore and Improve Urban Infrastructure — https://github.com/orgs/HardisonCo/projects/193
7. Advance Health Informatics — https://github.com/orgs/HardisonCo/projects/203
8. Engineer Better Medicines — https://github.com/orgs/HardisonCo/projects/200
9. Reverse Engineer the Brain — https://github.com/orgs/HardisonCo/projects/205 10. Prevent Nuclear Terror — https://github.com/orgs/HardisonCo/projects/204
11. Secure Cyberspace — https://github.com/orgs/HardisonCo/projects/201
12. Enhance Virtual Reality — https://github.com/orgs/HardisonCo/projects/202
13. Advance Personalized Learning — https://github.com/orgs/HardisonCo/projects/199
14. Engineer the Tools of Scientific Discovery — https://github.com/orgs/HardisonCo/projects/198
Specs and the per-challenge process lists: https://github.com/HardisonCo/opendl
It should also be funded by the Gov. IMO and 100% for oublic benifit e.g.: nsf.dev
2-14. ???
- Eliminate racism
- Eliminate poverty
- Eradicate crime
- Eradicate corruption
- Reverse climate change 100%
- wake me up when you got an AI project capable of doing this one
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.
Solutions that require a great many humans to change an ingrained behavior are usually non-starters.
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!
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.
They're also incredibly productive and can build/deliver really good stuff, so who knows :)
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/
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.
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.
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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.
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.
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.
Have you ever seen anything to the contrary?
Not my downvote btw, corrective upvote
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.
Beyond that, I don't know. Admittedly, I work in a smaller lab setting. There's no chief scientist that I'm aware of, or systematic production of hypotheses. That might be for the bigger labs.
Don't judge a book by its cover? Sounds like you're just having issues because you've set up a bed filter in your brain. Are you really advocating that everyone change their websites to make it easier for you to distinguish if you'll find the information valuable?
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
https://e360.yale.edu/digest/china-clean-tech-developing-cou...
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?
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?
I leave it as an exercise for the reader to count out how many generations you need to run this until it's 'oops, all self-replicating individuals with broken off switches.'
>>> 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.
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.
I just don't see anything damning on the list that isn't someone's opinion on public perception of his actions.
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.
Otherwise we are in for a great societal upheaval that might make low price of solar irrelevant.
Your thinking reminds me of this https://xkcd.com/538/
It's yearsss past time that our leaders should have changed policy.
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.
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.
I agree. It's just wishful thinking to say that oh if we just lower the price of solar then it'll be okay. There are innumerable issues which are blocked by politics and we will never solve them all without fixing politics.
> Otherwise we are in for a great societal upheaval that might make low price of solar irrelevant.
These days I think a great societal upheaval may be the only way to fix politics.
But it's actually the wrong way around. Hope that the despot will soon die saps peoples' will to do the difficult and dangerous job of removing them. Take away that hope and they are forced to find the courage.
Especially true if it is the AIs that get us the immortality- it definitely won't be equally spread, and any incumbents have a massive advantage.
I think more people would settle for worse conditions to stay alive. Do you think you'd be more likely to revolt at 150yrs old when all your family and yourself can live extremely long to forever? Or do you think the threat of death by killing wouldn't be an issue?
Also, if you eliminate all the aging-related causes of death the average lifespan is still only like 1000 years or something. Nobody's getting eternity. And yeah, for the chance to make a big enough change of the right kind to society I would indeed give up a 1000-year lifespan. My memes have fully subjugated my genes, and I'm at peace with that.
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?
everywhere? all at once? The grid is distributed, this is a solved problem. Most of what is needed now is to build the systems, storage, and transmission lines.
There is also no default price on energy markets, it fluctuates with supply and demand. Dynamic pricing by itself is enough of a reason for industrial users to build up their own power storage, which allows them to time-shift consumption from the grid.
Time-shifting is definitely going to increase, but it's not a bad thing. Look at how battery storage has made electricity cheaper and more reliable in California.
A politician could trivially write a law to end this "problem", at any point. Or courts could start rejecting suits where investors sue. There is nothing inherent in nature that requires this outcome to exist.
This is an entirely self-made problem that society tolerates when it doesn't have to. Corporations used to need a blessing from the government to be formed, explicitly to avoid the risk of a massive corporation who can compete with the government and have investors that push anti-social goals.
https://en.wikipedia.org/wiki/Benefit_corporation#/media/Fil...
I don’t think there’s some practical way to force existing corporations to include something in their charter, if that’s what you’re suggesting. Business organization is something that a business chooses to do.
Laws are but a pen stroke away.
<legalese intro>
No existing nor new C corp and their executives shall be be considered in breach of their fiduciary duties or obligations if they take an action they deem to be in the best interests of society at large, as long as it’s not fraudulent or otherwise illegal behavior.
<legalese outro>
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.
I don’t think anyone can look at the company Craigslist in 2026 and say it has spent the last 30 years satisfying a legal duty to maximize profit.
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).
From my perspective, we are desperately short of scientists, researchers and engineers, but we are using an outdated economic model to leverage their findings. LLM’s are a large part of Bush’s Memex and Jobs’ bicycle for the mind visions for intelligence amplification, and in some ways exceed them. I hope we trampoline from how we currently use basic seeking efforts for knowledge.
Or that the floor is raised, at least, and AI empowers average scientists to do substantial work.
A large amount of people building their own customized apps for themselves.
Similarily, everyone becoming their own accountant / lawyer / other professional services.
These professional services will defend themselves with gatekeeping. Suddenly it doesn't depend anymore on the quality of your legal advice, but whether it has been stamped by a qualified Lawyer. It doesn't matter that your taxes are correct, but whether they are submitted by an approved accountant. Etc.
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.
You can of course have many independent small groups, but this is trivial and best left unsaid in the context of this comparison.
It's not as if there is a limited amount of R&D to do.
1. Corporate charters and form of incorporation are consensually chosen by those involved.... you're suggesting something that is in violation of that consent. This would have crazy unintended consequences. Remember that a corporation is not necessarily a business. Imagine an investment holding company, or a building cooperative, where the directors could have a blank check to use money for some unrelated public benefit. That's completely bonkers.
2. PBCs don't get to do any "action they deem to be in the best interests of society at large"... they get to do things that are in the interest of specific public benefit goals which they have defined in their charter and those are balanced with the interests of shareholders. Everyone involved knows and agrees with what these specific public benefits are, which is an important thing.
The point of my example was the legal standard used.
The point of regulation is not to protect the producer, but to protect everyone else who has to live in the same society. If the Chinese make another tradeoff and sacrifice some of their citizens in the name of greater riches for the billionaire class, that is their problem.
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?
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.
So, while a company might crack it and become massive, the tech will make it to the rest of us whether they like it or not.
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.
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
Which could be pretty hard to find and not everybody wants to wait.
Sooner or later somebody's going to say "Hold my beer," anyway ;)
>Definitely not public.
Seriously worth considering keeping a low profile, almost all other scientists can only enjoy respected institutional status by diverting huge amounts of their effort merely to gain or maintain certified eminence. This really limits the potential accomplishments of world-class minds if their talents really are tops in the very front-line frontier of discovery.
This sounds same as Google's "don't be evil" enshiftification, consolidating technologies that was available in a competitive way.
I prefer Scientists, and team of people working on things, instead of a corporate controlling everything with promise of automation, thank you very much.
Because it's evil?
They only seem to care now because it affects them.
Or is it just evil that you aren't the one who gets to control it?
Why should the greatest creation of all time have to be given away? As a counter-example, what if they used it to do nothing but good deeds everywhere? And they controlled it to keep it out of the hands of Abdul Al-Hassan the hijadi?
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.
Solar is cheaper, but requires more room and time to spin up (think datacenters, where you can put a turbine within a month) and storage or backups for windless nights.
I don’t think we have the data to disprove the stronger claim “societies collapse”, and I don’t think being unfair (whatever that means) makes societies collapse earlier. Did slavery hasten the fall of Rome, for example, or the Gulag the fall of the USSR?
As to “whatever that means”, I think that’s hard, if not impossible, to define objectively. Catholic dogma says the Pope is the representative of god, for example, so catholics (less so in modern times, I think) don’t question his decisions. Many would call that unfair, even if the pope would be elected 100% by merit.
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?
But if an AI surpasses humans in every way, is there any evolutionary benefit for the AI to cooperate with humans?
"I'd hit somebody in the head."
"All over this Land!"
It does have a ring to it and would probably make it up the pop charts as a 21st century version more than ever ;)
Also, when the human reaches for the power switch the AI agent uses a flaw in the power management software to weld the switch shut with a big power surge, killing the human with a huge electric arc in the process.
I don’t think whether we will get there, but the stories of LLMs escaping their sandbox make me think we’re moving in that direction.
Unlike those pesky humans with their conception of the word "No".
