10 ms·
Discovery Loop
- drcongo 2mo agoNot through conscience.
- ValentineC 2mo agoI wonder if Jeff Dean facts [1] (I hope people remember the reference) will carry over to the new startup. [1] https://github.com/LRitzdorf/TheJeffDeanFacts https://github.com/LRitzdorf/TheJeffDeanFacts
- deleted 2mo ago[deleted]
- hoyd 2mo ago«Jeff Dean's PIN is the last 4 digits of pi.» 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 2mo ago0000 in base pi. Oh Jeff.
- tcp_handshaker 2mo agoThose 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.
- deleted 2mo ago[deleted]
- bonsai_bar 2mo agoYou sound like you're quite jealous of him.
- root-parent 2mo agoI had never heard of many of these, was surprised, went to research, and so far, the list seems correct.
- twister2920 2mo agonot sure how you got that from a long list of criticisms
- dekhn 2mo agoActually the list is technically accurate. So maybe it's sour grapes, but it's correct sour grapes.
- scottyah 2mo agoBut they're all highly unsubstantial, sounds like hit-piece lazy journalism. Almost all are just that Jeff was in a leadership role and part of committees that had things under them go bad. One was just saying that people disagreed with what he said when he actually put out a statement to clear confusion when an employee went a bit rogue (went to media instead of going to someone like Jeff) in an attempt to get a promotion. I just don't see anything damning on the list that isn't someone's opinion on public perception of his actions.
- shawn_w 2mo agoI suppose you think Chuck Norris Facts are fake too.
- Johnny_Bonk 2mo agoFor sure made with Claude code for front end, but I’m excited to see where they go
- ablation 2mo agoAbsolutely reeks of Claude. This is the new aesthetic.
- input_sh 2mo agoThe new Bootstrap, but somehow even shittier as the content itself is also bland and only vaguely matches the subject. Might as well put lorem ipsum in there, it's just as "informative".
- johanyc 2mo agoMy first thought when I see the website too
- calufa 2mo agoAs 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.
- deeviant 2mo agoLLM 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 2mo agoLLMs 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 2mo ago
- flakiness 2mo agoTo 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 2mo agoA 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.
- flakiness 2mo agoFair point. Their page doesn't list any investors.
- valleyer 2mo agoThe Times article lists several.
- mgfist 2mo 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 2mo agoFor 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.
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- 1970-01-01 2mo agoI'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".
- XenophileJKO 2mo agoHow is that different than video input?
- 1970-01-01 2mo agoThere are over 2 dozen known senses to reality. Video input is a fraction of a sense. https://en.wikipedia.org/wiki/Sense#Artificial_sensation_and_perception https://en.wikipedia.org/wiki/Sense#Artificial_sensation_and...
- LarsDu88 2mo agoI'm almost certain the goal of this startup is to make physical automated research labs guided by RL
- montebicyclelo 2mo agoDid the ycombinator podcast which included giving advice to startup founders just a few days ago: https://www.ycombinator.com/library/Vy-jeff-dean-the-1-rule-for-building-in-ai https://www.ycombinator.com/library/Vy-jeff-dean-the-1-rule-...
- xnx 2mo agoAs always, a very good presentation.
- melodyogonna 2mo agoOh 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 2mo agoGoogle is backing it.
- deleted 2mo ago[deleted]
- FailMore 2mo agoGoogle down $160Bn so far since the leaving announcements. Those are some valuable people!
- IAmGraydon 2mo agoGoogle is literally at the same stock price it was on Monday. This is a normal daily fluctuation for them.
- mosfets 2mo agoIs this a joke? Site is not loading for me.
- stephantul 2mo agoI’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.
- tcp_handshaker 2mo agoLets keep your comment out of the VC pitch deck shall we?
- hobofan 2mo 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.
- porridgeraisin 2mo agoYep. 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 2mo agoThe purpose of hiring grad students isn’t to advance science, it’s to train experts.
- pickleRick243 2mo agoIt'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. ...
- flakiness 2mo 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...
- cjbarber 2mo agoFrom 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. See also: https://www.nae.edu/20782/grand-challenges-project 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
- tcp_handshaker 2mo agoAcquisition back by Google in 3 years, with nothing to show for it. VCs will make a ton.
- tgma 2mo agoand... the VC is Google. Gotta compensate them somehow.
- DataDaoDe 2mo agoMy thoughts exactly
- dude250711 2mo agoFor all we know, they could have been successfully working on "10. Prevent Nuclear Terror" for the last 80+ years.
- ex1fm3ta 2mo agoSometimes 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
- xnx 2mo agoI'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 2mo agoI 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 2mo agoYes. 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.
- asimpletune 2mo agoThey're structuring the new company as public benefit corporation.
- an0malous 2mo agoDoes this mean anything besides for corporate virtue signaling?
- Aboutplants 2mo agoI’d wager it does the opposite of that in public opinion. There is a certain stink associated with it in current circles
- ares623 2mo agoAh following in the foot steps of OpenAI. Five years later: More like Discovery Knot amirite
- arjie 2mo agoThis 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 2mo ago> It might be a new scientific revolution to have computer-driven discovery. And ... it might not.
- wy1981 2mo agoJeff 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.
- nullsanity 2mo ago[dead]
- gosub100 2mo agoGemini 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 2mo agoAntigravity + 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 2mo agoOh 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 2mo agoYeah 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
- syntaxing 2mo agoThis 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.
- Taikhoom2010 2mo agoThe 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. https://taikhooms.substack.com/p/why-openrouter-can-be-the-next-great?r=2pgab7 https://taikhooms.substack.com/p/why-openrouter-can-be-the-n...
- make3 2mo agoI think Google's branding was starting to be too poor in AI to get top talent, they needed the refresh
- compiler-guy 2mo agoThe company is developing an application, or a class of applications. Not a new model.
- malux85 2mo agoModel 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.
- adfm 2mo agoFHE
- Taikhoom2010 2mo agoyes perhaps, although I think the best option for a enterprise is to train a model on it's own data.
- willy_k 2mo agoBest 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.
- deerstalker 2mo agoNational Labs in the US have been doing this for a while now. I feel like the private sector will take the lead soon.
- pphysch 2mo agoWhy? Science is wildly unprofitable on the scale of an individual private firm.
- bezko 2mo agoSo Ralph Wiggum in a suit?
- sidcool 2mo agoI am available for hire.
- deleted 2mo ago[deleted]
- searine 2mo agoComputation is not the hard part of discovery.
- ChrisArchitect 2mo agoRelated: Jeff Dean leaving Alphabet https://news.ycombinator.com/item?id=49184746 https://news.ycombinator.com/item?id=49184746
- swalsh 2mo agoBy the middle of the 2030's the world we live in will be unrecognizable.
- kingofthehill98 2mo agoI agree, for better or for worse. If I had to bet my money, it would be on "for worse".
- dude250711 2mo agoIt will not be owned by top 1%?
- swalsh 2mo agoThat seems to be the one unchanged variable of time.
- roughly 2mo agoThat’s a policy decision, don’t let them convince you otherwise.
- minittsnet 2mo ago[dead]
- warkdarrior 2mo agoThe change is that it'll be owned by the top 0.0000001% who control the LLMs that will be your new boss.
- fragmede 2mo agoWith 8 billion humans in the world, 0.0000001% is roughly eight people, and those eight would be Sam Altman, Dario Amodei, Demis Hassabis, Jensen Huang, Mark Zuckerberg, Elon Musk, Mira Murati, and Ilya Sutskever.
- WarmWash 2mo ago
- yddryhry 2mo ago[flagged]
- daishi55 2mo agoYeah 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.
- claiir 2mo agoThe site itself is really leaning into the “made with Fable” aesthetic
- pelagicAustral 2mo agoWhy 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?
- make3 2mo agoit's just a low effort snark comment, don't overthink it
- swalsh 2mo agoIf 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.
- slopinthebag 2mo agoBecause it’s lame and aesthetics matter.
- deleted 2mo ago[deleted]
- DaiPlusPlus 2mo 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.
- ramon156 2mo ago"Our mission is straightforward" continued by the most complex sentence on that page. Wondering what the definition of straightforward is now
- pphysch 2mo agoRight. 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 2mo agoYeah. ML is all well and good, but how are they going to do the science their machines design? Atoms cost money.
- ajam1507 2mo ago> Our mission is straightforward: we are building AI solutions that can automatically solve important problems in machine learning, science, and engineering. Genuinely curious which part you found complex.
- xyzsparetimexyz 2mo agoWe are building _ solutions (building solutions != building a thing. Can't you just say 'solving'?) That can _ solve _ problems in _, domains (Wait so the solutions are only the thing that solves the actual thing?)
- decimalenough 2mo agoIt's clunky, but still clear. They're building AI things (systems, solutions, harnesses, whatever) that can tackle big research problems.
- numbers_guy 2mo agoWhen they say experiments, do they mean using physics simulators?
- danielmarkbruce 2mo agoin AI/ML, no. They are just going to automate AI/ML research to start with. Totally doable. For some of the other things, undoubtably yes.
- Noe2097 2mo agoThis 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 :)
- pelagicAustral 2mo agoReally seems to embrace the "Making the world a better place by <<extremely convoluted, highly technical, jargon loaded mission statement>>"
- pickleRick243 2mo agoWhich part of it is highly technical or jargon loaded?
- guessmyname 2mo agoCareers page (if anyone is interested) → https://jobs.ashbyhq.com/Discovery-Loop https://jobs.ashbyhq.com/Discovery-Loop
- brcmthrowaway 2mo agoI don't see the salary (on mobile). Isn't there a law stating it must be added?
- guessmyname 2mo agoOnly 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]. [1] https://hr.ucmerced.edu/hr-units/talent-acquisition/senate-bill-1162-sb-1162 https://hr.ucmerced.edu/hr-units/talent-acquisition/senate-b... [2] https://www.adp.com/spark/articles/2023/03/pay-transparency-laws-your-questions-answered.aspx https://www.adp.com/spark/articles/2023/03/pay-transparency-... [3] https://www.jazzhr.com/blog/pay-transparency https://www.jazzhr.com/blog/pay-transparency [4] https://jobs.ashbyhq.com/Discovery-Loop https://jobs.ashbyhq.com/Discovery-Loop
- jiveturkey 2mo agoIt'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.
- deleted 2mo ago[deleted]
- OutOfHere 2mo agoI 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.
- GodelNumbering 2mo agoThis 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 2mo agoWhat percentage of people work at a startup though? Not just new/small business, which could include restaurants, local services, etc., but tech/science startups that would meaningfully benefit from AI. I'd bet you could 10x the number and still be in low single digit percentages of the US workforce. And it seems pretty likely that AI-enabled startups will also employ less people per-startup. If AI causes a white-collar jobs apocalypse, I don't think startups are picking up the slack, although it'll plausibly cushion the blow somewhat for top-performing tech workers.
- reasonableklout 2mo agoYes. Startups are intensely competitive, exhausting, low-stability places to work. This is the definition of job displacement for most people.
- dfunckt 2mo agoThey kind of touch on this: > 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.
- scottyah 2mo agoThat's fine by me. I certainly won't be making any major discoveries on my own (not on this current life trajectory anyway), but am very grateful that other people have.
- drivebyhooting 2mo agoHow 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!”
- moelf 2mo agowould love to see how AI can automate the construction of the next high energy particle collider
- scrlk 2mo 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 2mo agoBut I always wanted to try headcrab souffle.
- scottyah 2mo agoIf you just got some agents to handle scheduling meetings, finding out which permits to get and applying for them, and finding capable sub-contractors, you'd save half the time.
- mbonnet 2mo ago> transcendence > immanence somebody has been studying Christian theology!
- constantinum 2mo agoIn 2018 there was a beautiful New Yorker article on Jeff Dean and Sanjay https://www.newyorker.com/magazine/2018/12/10/the-friendship-that-made-google-huge https://www.newyorker.com/magazine/2018/12/10/the-friendship...
- danielmarkbruce 2mo agoAutomating ML/AI research seems completely tractable. Most of the other claims seem much less doable.
- deleted 2mo ago[deleted]
- claiir 2mo agoThe job req has "Recursive Self-Improvement" as one of the "area of expertise" checkboxes lol
- meindnoch 2mo agoI smell vapor.
- tmoertel 2mo agoNote 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.
- paganel 2mo agoThere's this somewhere on that page: > securing cyberspace, which has clear military implications, at least in today's age.
- tmoertel 2mo agoDo 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 2mo 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 2mo agoSecuring 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.
- 2mo ago
- 4lx87 2mo agoDiscovery and optimization are very different processes. Optimization is the process of finding the shortest path to a goal. Discovery is the process of stumbling on new goals and redrawing the map of what's possible. Ambitious goals and new discoveries happen via novelty-based search. Progress in scientific discovery is measured by how different/interesting the outcomes are, not by closeness to a predetermined goal. Discovery is a creative search that preserves optionality, whereas optimization restricts optionality. In other words, you usually don't discover anything novel unless you're trying new things that don't appear connected to the goal in the first place. Would an ML optimization loop have discovered transformers?
- jfreds 2mo ago> would an ML optimization loop have discovered transformers? I think that’s exactly the kind of problem this group is looking to solve. You make a compelling intuitive argument, but that’s not the same thing as a proof
- kulsumshannan 2mo agoThis seems interesting! I wonder how this will play out.
- roughly 2mo agoTwo to keep in mind with these kinds of things - 1. There’s some irreducible costs in terms of time and material in the physical world that are not amenable to the kind of optimization or parallelization or even just the raw speedup from Moore’s law or computational architecture improvements we’re used to with software. My experience is primarily in biology, where the examples here are things like “it takes 20 minutes for E. coli to replicate” - it has taken 20 minutes for E. coli to replicate for a billion years, and next year it will still take E. coli 20 minutes to replicate, no matter how good your software stack is. Similarly, it takes X amount of energy to grow enough E. coli to produce a meaningful result, and that energy costs money, whether it’s in the form of glycerine or heat or whatever you want, and that also won’t materially reduce in the same kinds of “orders of magnitude” sense we’re used to from software, which is what we’re usually expecting to make the economics of these things work out. 2. Complicating the above, physical systems are phenomenally multivariate - far, far more than you think, and biological systems especially are just unbelievably complex - which means the number of experiments and the length and duration of those experiments you need to run to get enough data to be reasonably confident you’re seeing genuine signal is Way higher than you think. Combine those two things and what you get is a money furnace, even before you get to the AI model training part, which is Also a money furnace. There’s low hanging fruits in all this, there’s areas where automating the approach can be really valuable, but typically the moment you turn this machine on, you’re gonna start burning money at a rate that would embarrass a finance bro on a coke bender, and that’s effectively unavoidable because the real world is not amenable to software’s scaling laws.
- xyzsparetimexyz 2mo agoThats why you simulate e coli at 30x in a sim environment that fable slopped together. Duh
- galoisscobi 2mo ago> Imagine a future where a handful of people can conduct scientific research and engineering tasks much more rapidly, and with higher quality, than massive teams of scientists and engineers do today. Imagine a future where only the anointed few elite minds can participate in science and engineering. Btw we’re hiring. Great message!
- TrackerFF 2mo agoI don't know why you're being downvoted. This is basically something scientists have been alarming about for the past year: We're moving into a future where science may be tiered into the haves (those with access to premium compute) and the have nots (hoi polloi with restricted access), which in turn could seriously influence what kind of science we'll get. Worst case, we'll get science that is completely dependent on business and politics. EDIT: I should note, this comment was aimed at a more general case.
- cwoolfe 2mo ago"The speed of light in a vacuum used to be about 35 mph. Then Jeff Dean spent a weekend optimizing physics."
- AIorNot 2mo agoAnother way to see this is: a bunch of renowned google engineers realized they can grab some of the VC pie for themselves https://www.geekwire.com/2026/the-startup-idea-that-convinced-a-uw-computer-science-legend-to-leave-google-after-27-years/ https://www.geekwire.com/2026/the-startup-idea-that-convince...
- Sathwickp 2mo agoIs it a very hard problem to solve that jeff and the other legendary engineers have decided to quit and start on this?
- thisoneworks 2mo agoI 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.
- bagacrap 2mo agoI suspect they want a bit more control over what they're working on. These days the bean counters are running Google.
- thatsadude 2mo agoThis is “google brain”
- bredren 2mo agoThis seems to be an institutional, massively scaled version of https://github.com/karpathy/autoresearch https://github.com/karpathy/autoresearch. 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). Tweet is protected but in SERP caches: https://x.com/karpathy/status/2030705271627284816 https://x.com/karpathy/status/2030705271627284816 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.
- ozgung 2mo agoThat 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.
- eamag 2mo agoThat'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)
- dnnehgf 2mo agothis is like saying taylor swift must have been influenced by justin timberlake because they both dance on stage sometimes.
- crossroadsguy 2mo agoWell, your comparison now makes it less far-fetched of an analogy.
- m3kw9 2mo agoThe AI designed italics on thin font is hard to not see as slop.
- aaronharnly 2mo agoYou 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 2mo agoThey would argue they are focused on more important stuff, but marketing shouldn't be underestimated.
- holmesworcester 2mo agoSomeone who left DeepMind over Google's agreement to provide military AI to the US government tried to get Jeff Dean to quit too: https://turntrout.com/why-i-left-google-deepmind 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.
- asadm 2mo ago> Automating AI research is terrifying. what why?
- kridsdale1 2mo agoSkynet.
- reasonableklout 2mo agoIt depends what they mean by automating. But the classic argument goes: * Each new generation of models has emergent capabilities we did not anticipate. * We already have trouble monitoring and controlling the current generation (see HuggingFace incident). * The more we let models shape their successors, the more out-of-distribution each generation's learning environment becomes. * If not done carefully, we risk creating extraordinarily intelligent and powerful models with unintended behaviors, like deceptiveness or power-seeking.
- tokioyoyo 2mo agoIf 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.
- dgellow 2mo agoThat 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…)
- aykutseker 2mo ago[flagged]
- ggcr 2mo ago> Oriol Vinyals, Sanjay Ghemawat, Jeff Dean, Quoc Le as founding members is crazy !
- mem1nce 2mo agonice
- Wonnk13 2mo agonot that it really matters, but is he leaving Google?
- jszymborski 2mo 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.
- gtirloni 2mo agoLLMs can't materialize funds or political will so let's stick to running GPUs hot and publishing papers. The citations will be amazing. /s
- vanviegen 2mo agoYes! But if science is bottlenecked by funding, making it cheaper might help?
- woeirua 2mo agoNot really. Grad students are already essentially working for free.
- tjwebbnorfolk 2mo agoHow many lavishly-paid deans and bureaucrats and administrators are employed for each grad student?
- jszymborski 2mo agoIt's not easy to disentangle and it varies by country and institution, but those positions are not normally directly funded by public research grants.
- deleted 2mo ago[deleted]
- puttycat 2mo agoWhat's the business model of these startups?
- omederos 2mo agoWhat a team.
- varjag 2mo agoDiscovery systems are making a comeback huh.
- xuehaohu 2mo agoBig news aside, it feels exciting to see them leave and pursue startup. They could have stayed back, and retire
- bagacrap 2mo agoThis is their version of retirement. Did you think Jeff Dean was going to stop doing tech and play golf?
- maCDzP 2mo agoI 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 2mo 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?
- maCDzP 2mo agoHeh, I run my experiments on Claude subscription. And that cost I’ll file as an ”opportunity cost”. But if I would have build this by hand and given myself a salary, then paying Claude to do it is way cheaper.
- 7e 2mo agoJesus, 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.
- pm90 2mo agoI think people are missing what this really is: Google giving some of its most senior engineers the best retirement home to keep them away from competitors. This isn’t in jest; I wish i could make enough money to not care for more from my job and then do research after i get old. Its honestly a brilliant move.
- mpfh 2mo ago[dead]
- zackwu 2mo agoIt depends on your lens, some may think it's a way to show them the doors after failed corp politics.
- decimalenough 2mo agoSanjay has been Google's most tenured IC since forever and is basically as immune to politics as you can be in a megacorp. 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-that-made-google-huge https://www.newyorker.com/magazine/2018/12/10/the-friendship...
- roflmaostc 2mo agoReading this article, now I can understand why there is jokes about Jeff Dean's binary readability...
- pilooch 2mo agoThe risk is they are a magnet for many more talented ML scientists to leave google.
- gopalv 2mo ago> a magnet for many more talented ML scientists to leave google. 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.
- AmbroseBierce 2mo ago"the benefits of science and technology to the world" just like AI has brought such benefits? Because I haven't seen them, for example it hasn't helped reduce inequality (nor poverty), or reduce climate change, or pollution, or daily stress, if anything it seems to be worsening some of these issues. So forgive me if I'm skeptic when renowned AI scholars claim to start something for "the benefits of science and technology", because it really seems like we have very different definitions of these words.
- deleted 2mo ago[deleted]
- raver1975 2mo agoI already did automate the experimental loop. https://alethean.org https://alethean.org
- cityzen 2mo agoCan’t wait until they get acquired by Google.
- roflmaostc 2mo agoGoogle already invested into them.
- jschveibinz 2mo agoHere are just a few of viewpoints on what constitute world problems to solve: https://80000hours.org/problem-profiles/ https://80000hours.org/problem-profiles/ https://en.wikipedia.org/wiki/List_of_global_issues https://en.wikipedia.org/wiki/List_of_global_issues https://encyclopedia.uia.org/ https://encyclopedia.uia.org/ Interestingly, one list identifies "AI" as a top world problem! One person's problem is another person's solution, I guess--and vice versa, as well. An extreme example: curing a disease is good for patients but bad for the healthcare industry--which is (in kind) also bad for healthcare workers and everyone in science working on cures.
- xyzsparetimexyz 2mo agoNo its not. Everyone dies. Healthcare is invoked in everyone's life. Generally the longer you live the more healthcare you'll need.
- cjauvin 2mo agoLawZero, Yoshua Bengio’s startup, also proposes to automate scientific research and experimentation, from the perspective of safety, by being explicitly “non-agentic”: https://lawzero.org/en/publication/scientist-ai-safe-design-not-desiring https://lawzero.org/en/publication/scientist-ai-safe-design-...
- BenFranklin100 2mo agoFrom the self-stated bios, this group consists solely of CS guys. No biologist, physicist, linguist, chemist, biophysicist to be found. Based on this observation alone I call nonsense. These is AI bullshittery. These guys aren’t close enough to the problems to understand the challenges. Source: PhD Computational biophysicist turned experimentalist. I work with genuine scientists across a range of disciplines from neurodegeneration, cancer, to fibrosis. Getting in the lab and generating data is absolutely key, among other things.
- nl 2mo agoDo you actually think that this group of founders will have trouble finding domain experts wanting to work with them?
- BenFranklin100 2mo ago“Imagine a future where a handful of people can conduct scientific research and engineering tasks much more rapidly, and with higher quality, than massive teams of scientists and engineers do today. By automating the loops of discovery, the world will be able to make much more rapid advances across countless fields of science.” The key point is these jackasses explicitly state, “ a handful of people” can replace “massive teams of scientists and engineers”. These guys don’t even understand the nature of the challenge and neither do you apparently. If they did, they would realize that it indeed does require “massive teams of engineers and scientists” to solve our most pressing problems.
- nl 2mo ago> don’t even understand the nature of the challenge Oriol Vinyals was a co-author of AlphaFold.
- BenFranklin100 2mo agoAgain Nick, you don’t understand the nature of the problem. In the vast sea of biology, protein folding is well circumscribed problem. Klaus Schulten’s group and dozens of other groups were already making good progress since the nineties chipping away at this problem. 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.
- kaishiro 2mo agoI know these sorts of meta comments are often frowned upon, but good god do I hate this approach of fading in every individual element on scroll down the page. It's one of my biggest pet peeves of "modern" web sites.
- luqtas 2mo agoyes! and giving current scientific research on reading efficiency pointing towards fixed pages being much better than scroll, the whole web is screwed but these fancy sites... a big merda
- SubiculumCode 2mo agoI am siding with the "intelligence is not the bottleneck" crowd. Science takes more than reading literature and making a hypothesis. You have to run the experiment. And that is where messy reality will crush the naive, and resist any attempt to package it up into a factory-like innovation engine. But they will take your money, should you have some to invest.
- analog31 2mo agoI'm a scientist. On the one hand I take some comfort in thinking that I will always have an advantage in the lab. On the other hand I'm not taking anything for granted. And my advantage in the lab has to translate into an employer being smart enough to keep me around until if and when the AI takes over, which kind of translates into their investors wanting to keep me around. We know what happened to manufacturing when investors were no longer interested in it.
- stogot 2mo agoAre you suggesting outsourcing? AI produces hypothesis, a chief scientist approves, and it’s outsourced to a lab in Vietnam to execute.
- analog31 2mo agoThat could happen today, but the chief scientist presumably comes up with the hypothesis. I still think the US has a comparative advantage in science, but it's under attack. 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.
- FuckButtons 2mo agoI’m not sure that I agree entirely with your framing here, yes, you do at some point need to correct your assumptions with external evidence. But clearly there have been many individuals throughout history who have had incredibly out sized impact in their respective fields as a consequence of the quality of their reasoning.
- zeronone 2mo agoSurprised that Sanjay is the tallest among them.
- sumedh 2mo agoHe was born in the US not India, good food/nutrition must have played the part :)
- jacknews 2mo ago"making solar energy economical" judging by the amount being installed, it already is.
- deleted 2mo ago[deleted]
- anr0 2mo agowith billion dollar seed rounds becoming the norm, it seems like there's no longer an advantage to build from within these bloated giants. can be much nimbler and have access to the same budget out the gates
- aaroninsf 2mo agoYou know what will be a good day? 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.
- tehnub 2mo agoThat pic of the team... no swag to speak of
- plaxiotech 2mo agogreat
- usernametaken29 2mo ago> execution entails repetitive experimental loops that are hard to scale with today's manual efforts: you propose an experiment, implement and run it, examine the results, then iterate to refine your approach. This is actually a feature, not a bug. We can hire 1000s of undergrad students at minimum wage but chances are the results are nil. Some processes have evolved over time because they’re sensible and need to be carried out carefully.
- stan_kirdey 2mo ago*self-discovery loop more like it :-)
- burgerone 2mo agoOf course it's AI because why wouldn't it
- nullbio 2mo agoGood luck. People can't figure out how to solve ARC-AGI reliably, let alone the complex problems in the real world.
- londons_explore 2mo agoEither these guys are going to try and build LLM swarms and agent loops.... 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.
- physix 2mo agoIn many domains, scientific research is physical. Are they going to deprecate labs and sort of scale that out into a pure compute problem? 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.
- ktallett 2mo agoYou can create a research twin that can predict but as you say, it only works once you have a lot of data. Both the data relevant to the experiment it came from (which is rarely published) and the complete failure data (which is almost never published in any form).
- physix 2mo agoPredictions are only one part of research. It's what theorists feed experimentalists with. Confirmation of predictions is by and large a very physical endeavour. Labs are not going away. 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.
- motoxpro 2mo agoFor a tech forum, there is a big lack of imagination as to how tech can help the world here.
- tsho 2mo agoI’m excited to see what they build.
- xnx 2mo ago2 things Jeff Dean has mentioned in talks as interesting areas for research: * Is there a better way to do matrix multiplication? * Could less reliable chips perform better in aggregate?
- duusejhshhs 2mo agoI keep being reminded of Eisenhower’s “plans are useless, but planning is indispensable”. 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.
- scottyah 2mo agoWe'll adapt. So far, it seems like every technological increase has demanded more cognitive ability, not less. Sure, we may not need 100 people who are experts at shoveling, but the people developing, maintaining, and even operating the excavators all have to be "smarter". All the thinking, learning, and training needed to stay alive in the cold might have been mostly lost when fire was controlled, but it comes with its own risks and learning curve. 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.
- duusejhshhs 2mo agoWe’ll adapt for sure, but not all adaptation is beneficial.. either way, it’ll happen and it’ll be one hell of a ride.
- retube 2mo agoI don't understand. how does some software algorithm replace physical experimentation?
- jdthedisciple 2mo agoNumerical mathematics
- don_esteban 2mo agoEh, that has limited applicability. 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 ...
- emsign 2mo agoNothing on that page says how they will actually do it. What is their method except "using AI"? And why has this over 750 upvotes? Meaningless AI company hype spam like this is exactly the reason why HN is so boring at certain times of the week.
- rakibuilds 2mo agoLooping is one best things I heard about AI development recently. Why should not they start a discovery Loop for the real world problem solving. Let's see how far they can go!
- niemandhier 2mo agoTheir “brain trust” has impressive experience, but mostly at things that are not natural science. Alpha fold and friends are an exception, but these mostly harnessed existing scientific data. I would love to see someone with a strong natural science background in those efforts. No one would build a house without an architect.
- bhanu786 2mo agoMay anyone tell me, what is it in simple terms with example
- VikRubenfeld 2mo agoIn many cases, isn't the time-consuming part of experiments irreducible? E.g. breeding plants? 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.
- theptip 2mo agoIt’s true in the limit, but I think we are nowhere near that limit. A friend recently started a bio startup and automated parts of mouse experiments enabling higher throughput on in vivo experimentation. This is not commonplace, and there is a lot of room for further automation here. 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.
- summerlight 2mo agoThis is a valid take but at this moment, AI is not trying to solve this fundamental dynamic. But it can still accelerate the process by aggressive exploration of the solution space which cannot be done even with an army of human researchers. Many ideas can be relatively quickly verified (and discarded if needed) by proper simulation even before real world experimentation, but we don't have enough capacity to process all potential ideas. If you can build a good model for simulation and establish a robust methodologies, we can use some ideas which never had a chance before.
- grapeorangesoda 2mo agoGarbage in. Garbage out. I can't believe how many people on this site worship talentless managers.
- FabCH 2mo agoJeff Dean invented MapReduce and Bigtable. Say what you want about their later years, but Dean and Ghemawat deserve their title of engineer.
- grapeorangesoda 2mo agoThey wrote the paper, they did not build it. Gemini (stolen technology they had nothing to do with) says: Jeff and Sanjay led the development, but they collaborated with a small team of engineers to build and refine the database. So, who were the engineers who actually built it? It lists "Fay Chang, Howard Gobioff, Mike Burrows, Wilson Hsieh, Deborah Wallach" but Idk if it's accurate. I know that these talentless managers didn't do anything, that's for sure
- FabCH 2mo agoIIRC Sanjay was literally never a manager and Jeff was not a manager until like a decade after MapReduce was built. And of course they didn’t build it alone, that’s the point of companies and teams.
- fragmede 2mo agoBefore Jeff Dean was a "manager", he got a > Ph.D. in computer science from the department that would become the Paul G. Allen School of Computer Science and Engineering at the University of Washington in 1996, working under Craig Chambers on compilers[8] and whole-program optimization techniques for object-oriented programming languages.[9] https://en.wikipedia.org/wiki/Jeff_Dean?#Early_life_and_education https://en.wikipedia.org/wiki/Jeff_Dean?#Early_life_and_educ... So he's got no shortage of talent as an IC.
- frozenseven 2mo agoFor reference, here are their Google Scholar pages: Jeff Dean: https://scholar.google.com/citations?user=sdcsQb4AAAAJ https://scholar.google.com/citations?user=sdcsQb4AAAAJ Sanjay Ghemawat: https://scholar.google.com/citations?user=0KF6ZC8AAAAJ https://scholar.google.com/citations?user=0KF6ZC8AAAAJ Quoc Le: https://scholar.google.com/citations?user=vfT6-XIAAAAJ https://scholar.google.com/citations?user=vfT6-XIAAAAJ Oriol Vinyals: https://scholar.google.com/citations?hl=en&user=NkzyCvUAAAAJ https://scholar.google.com/citations?hl=en&user=NkzyCvUAAAAJ
- gremlin0 2mo ago[flagged]
- hn5xz7plcj 2mo agoGood perspective on this
- RyoSaeba89 2mo ago[flagged]
- stmw 2mo agoOne thing I wonder about is how these high-profile startups handle their engineering hiring - in this case, it's just a link to an Ashby form. 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?
- titanomachy 2mo agoI assume that, like most really trendy companies, they hire mostly by internal referral.
- akashy123 2mo ago[flagged]