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Changes at Google DeepMind: Demis Hassabis from CEO to Chair, Jeff Dean departs

810 points · 862 comments · colesantiago

atleastoptimal · 1785947160 · focus · HN ↗
I think there's one weirdly simple reason DeepMind isn't doing as well as OpenAI and Anthropic. I may be wrong on this.
OpenAI and Anthropic went from tiny startups to huge companies. As a consequence the stock options/RSU's offered to the employees paid off a far higher percentage ROI than any stock options a DeepMind (and thus Google) employee would get (since Google is already huge). This disincentivizes people who truly believe in the economically transformative power of AI to work at Google since their benefits will be capped by Google being large + having public company obligations.
1. LZ_Khan · 1785947343 · focus · HN ↗
  I've always thought this as well.
  1. abakker · 1785947784 · focus · HN ↗
    Wouldn't this be a demonstration of the downsides of the anticompetitiveness of monopolies?
2. onlyrealcuzzo · 1785947875 · focus · HN ↗
  There is no other way to describe the Gemini 3.5 pro delay than as a complete and unmitigated disaster.
  It's a huge company.
  It's unlikely there is any one person to blame (and entirely possible he has none of it). But things need to change.
  1. sigmoid10 · 1785948239 · focus · HN ↗
    Google was always at the frontier of real research, but has been abysmal at shipping good products (at least since Sundar). The core company is run for margins and interest rates by the business people nowadays.
  2. tanh · 1785948254 · focus · HN ↗
    Yeah. I’m guessing they’re behind the Chinese models in capability now
  3. overfeed · 1785948399 · focus · HN ↗
    > But things need to change.
    Not all change is good, as proven by Zuckerberg's response after the lackluster Llama 4 release. The radical restructuring appears to have made things worse.
  4. pixl97 · 1785948626 · focus · HN ↗
    Huge companies tend to make money from network effects, rent seeking, and lock in. They tend to be horrifically bad when it comes to innovation, especially when it may disrupt exiting departments in the company. Those departments will fight for their life and generally muck things up.
    Very few companies have leadership that can prevent this infighting and force teams on directed goals.
  5. godwinson__4-8 · 1785948874 · focus · HN ↗
    People keep saying the same thing about Google lagging behind and always end up looking rather silly. Google was going to lose search to OpenAI. Then people complained there was too much AI in Google search. Now it's pretty good and par for the course.
    Yes it's a huge company.
    So they are slower. Then they will surface it across their massive product base and keep generating cash. While having a hand in Anthropic and others via investment anyway.
    Google doesn't need to offer you the bleeding edge at startup pace. They're playing a different game. When the bubble pops they will be well positioned really no matter the outcome to continue to capitalize as their competitors implode or get absorbed.
    The idea a delay is a "complete and unmitigated disaster" is just laughable. People have been saying this about Google since ChatGPT first invaded the public consciousness. Google will continue to do well, the histrionics of people like you aside.
  6. EthanHeilman · 1785949108 · focus · HN ↗
    I disagree. Google is one of the few parties that can monetize AI because Google has a massive moat in the form of their products: gmail, chrome, photos, search, etc... and Google already has the custom-built chips and datacenters.
    Google spending money on competing head to head with your LLMs is a waste of money for Google. If anthropic wins, Google copies their approach, buys anthropic for cheap or both. All the investors throwing money into OpenAI, Anthropic, are just accidentally subsidizing Google's product development. Google shouldn't spend its AI research capital in an arms race with Anthropic but instead should invest in AI approaches that no one else is investigating at scale. That way Google can hedge against LLMs hitting a wall.
    There is a real but small danger to Google that Anthropic replaces Google as a search engine, but that is an uphill fight for Anthropic. Google has massive brand recognition, network effects with gmail and chrome, Anthropic can't just copy what works from Google. On the other hand Google can copy what works for Anthropic. Google would have to play poorly to lose that fight.
    Probably the worse case for Google is that software becomes so cheap and easy to create and maintain that all of Google's product offerings become commoditized. Even in that world Google has a lock on infrastructure. Perhaps ASI software creation completely removes that as well? If so we are living in a post-singularity world and probably the stockmarket doesn't exist anymore either.
3. jmyeet · 1785948187 · focus · HN ↗
  We'll see if anyone gets to cash in on those. All you need is one down round and that gets wiped out. Or if the IPO gets delayed and disappoints then the stock can drop well before the lockouts expire. OpenAI and Anthropic are essentially offering Monopoly money in the hopes that one day you can exchange it for real money.
  1. tonfa · 1785949051 · focus · HN ↗
    > OpenAI and Anthropic are essentially offering Monopoly money in the hopes that one day you can exchange it for real money.
    I thought employees have already had opportunities to cash out (there's enough funding rounds for that).
    (Tho how much you can sell was limited, iirc to double digit millions...)
4. xnx · 1785948417 · focus · HN ↗
  OpenAI and Anthropic have the freedom to do absolutely insane things like negligently hack other companies. It would be stock price suicide if anything even remotely happened with Google.
  1. VulgarExigency · 1785948835 · focus · HN ↗
    There's no doubt in my mind that they set up the conditions for their models to escape the sandboxes. "haha oops our incredibly powerful models escaped we need 1 trillion more dollars and really this is yet another reason why no one else should be allowed to build this technology"
  2. [deleted] · 1785950742 · focus · HN ↗
    [deleted]
  3. [deleted] · 1785950856 · focus · HN ↗
    [deleted]
  4. somenameforme · 1785952681 · focus · HN ↗
    Google's AI was telling people to put elmer's glue on pizza to help the cheese stick [1], Gemini was turning the Founding Fathers black [2], and more. Oh and the pizza recipe was based on a joke from a reddit user named "fucksmith" - part of data that Google apparently paid some $60 million to Reddit to access. The one and only effect of this was lots of amusing posts and articles. Their stock price went up during the whole ordeal.
    [1] - <a href="https://www.forbes.com/sites/jackkelly/2024/05/31/google-ai-glue-to-pizza-viral-blunders/" rel="nofollow">https://www.forbes.com/sites/jackkelly/2024/05/31/google-ai-...
    [2] - <a href="https://www.axios.com/2024/02/23/google-gemini-images-stereotypes-controversy" rel="nofollow">https://www.axios.com/2024/02/23/google-gemini-images-stereo...
  5. user43928 · 1785953145 · focus · HN ↗
    If Google put out a blog post about Gemini 4 having escaped its sandbox via 0-day exploit to then hack other companies, I unironically believe this would result in a boost to their stock price.
    They could really use some encouraging news about the competitiveness of their AI lab.
  6. ddp26 · 1785955725 · focus · HN ↗
    Would it though? Meta and Microsoft have had very scandalous AI things happen, and their shares didn't tank (or quickly recovered)
  7. ur-whale · 1786021181 · focus · HN ↗
    > It would be stock price suicide if anything even remotely happened with Google.
    aka they're dead in the water.
5. overgard · 1785948724 · focus · HN ↗
  I think something that doesn't get talked about a lot is how bad most large tech companies are at creating new products, in general. Like, if you look at most big tech companies, they have their core offering that got them to be really large and rich, and a few other products that are somewhat successful, and then a really long tail of markets they try to enter and failed at, or projects that were modestly successful but got killed because they weren't game changers (RIP Google Reader). Most of the time when a large company does something new that succeeds, it's via an acquisition of a smaller company (ie, Google with Android or Meta with Instagram and Whatsapp)
  It's funny, because I think the company that's going to be best positioned coming out of this bubble is in fact google, because they have the expertise and the capital. But I honestly can't tell you right now what their AI product even is -- I've seen so many things go into the graveyard a few months after its launched that I'm utterly confused what their offering even is at this point.
6. mrpopo · 1785948737 · focus · HN ↗
  > people who truly believe in the economically transformative power of AI
  People who truly care about becoming rich*
  DeepMind made enormous transformative discoveries, for instance in the world of protein folding. But that will just save human lives, not let CEOs fire their people to grab a larger piece of cake for themselves.
7. vineyardmike · 1785948834 · focus · HN ↗
  The answer is far more benign.
  They getting a higher ROI renting their TPUs to Anthropic et al instead of performing training and serving their own models. Google cloud has insane backlog, and has rapidly expanded to satisfy it. While those DCs get built, they’re cannibalizing their own products for it.
  This makes sense because (1) they are investors in Anthropic, so they still win and (2) they can always catch up on model training later when the profit opportunity shifts, or abandon it if there is no way to recapture that value.
  1. WarmWash · 1785950104 · focus · HN ↗
    Awfully ironic that Google makes more money (probably an order or magnitude or so) from it's direct competitors than it does from a it's own product.
  2. jatins · 1785951245 · focus · HN ↗
    I don’t think so. If Kimi and Deepseek can launch models better than Gemini with much much lesser resources then it is increasingly looking like an organization issue at Google
  3. ilaksh · 1785956290 · focus · HN ↗
    I think the reason Google hasn't prioritized larger models that are more intelligent than everyone else's, even though they probably could, is because they have 4 billion active users already. For example, they send AI Overviews for a large portion of Google searches now.
    So I think they have to prioritize scaling for their models to a higher degree than other groups. Being within say 5% or so in most cases is probably adequate and matters more overall for their user base than being the absolute best coder. So they may be setting compute constraints for training or inference that are firmer than other teams.
  4. chermi · 1785971071 · focus · HN ↗
    I don't think Google is that freaking short-sighted. Even if you're not trying to be frontier, the value of having domain knowledge via experience for AI is worth saving internal compute alone. By all accounts Google believes in ai as much as everyone else.
    If AI turns out 1/100 as important as they seem to think, it would be insane to intentionally be slack on it.
8. logicchains · 1785948847 · focus · HN ↗
  It's not a ML talent problem. You don't need to be a genius deep learning researcher to think "Hey, maybe if we massively throttle and degrade the quality of our model while still charging the same price, that might drive people away" (as happened with Gemini 2.5 Pro, the one model where Google really was SOTA). Google's likely been providing insufficient training compute to DeepMind the same way they've been nickel-and-diming their customers, funneling it all to Search instead because that's where the money comes from.
  1. underlipton · 1785975686 · focus · HN ↗
    Is that what's happening? Search has sucked for a while, and I'd just assumed it was partly because they'd been pushing compute to AI-related activities.
9. cedws · 1785949745 · focus · HN ↗
  Is this not an apples-and-pears comparison? DeepMind is a research lab, not an LLM-pilled money furnace.
10. majormajor · 1785950268 · focus · HN ↗
  That was true early but OpenAI/Anthropic have done a ton of hiring over the past couple years at already-huge valuations, as much on the strength of big current base salary + equity, not just future increase speculation.
  1. solenoid0937 · 1785959473 · focus · HN ↗
    Everyone knows there isn't a moat.
    No one joins OpenAI/Anthropic unless they think these companies will reach superintelligence.
    So most people joining believe their equity will 10-100x even from where it is today.
    (Coincidentally, the talent that believes we will reach AGI overlaps a lot with the best talent, which has a magnetic effect.)
11. Bjorkbat · 1785950337 · focus · HN ↗
  One theory I've been entertaining is that whenever GPT-3.5 came out a lot of people were talking about the "bitter lesson" and how scale was all we really needed to get to AGI. No need for any fancy tricks, just release a larger model trained on more data, by the time we released a hypothetical "GPT-5 sized" model we'd have AGI.
  Anyway, the actual theory is that Google and Meta have fallen behind because they've been playing by this playbook of focusing on scale and training data, whereas OpenAI and Anthropic have done so well because they are likely doing much more interesting things to improve their models over time. It makes sense when you realize that one of Google's key strengths, besides talent, is that they have an incredible amount of data they can use for training due to being both the world's leading search engine as well as having all that video data from YouTube. Scaling the training data makes more sense to them than it does to Anthropic and OpenAI, who are both relatively data-disadvantaged.
  You can kind of see this when you look at the Gemini 3 scorecard when it came out (<a href="https://blog.google/products-and-platforms/products/gemini/gemini-3/" rel="nofollow">https://blog.google/products-and-platforms/products/gemini/g...) and notice that while it wasn't as good as Claude And GPT at coding, it scored higher on a bunch of other non-coding benchmarks, and I think the reason why is simply because of Google's data advantage.
  If true, I feel even more vindicated for believing that the "scale is all we need" narrative was bullshit.
  1. redox99 · 1785950828 · focus · HN ↗
    Other than attention optimizations and other minor changes, the top Chinese models (which are way better than gemini) have basically the same architecture as GPT2. Of course RL is key for agentic workloads, but I'd say it's correct that progress has been mostly scaling models,adding more data and cleaning it better.
  2. aidis9136264 · 1785974866 · focus · HN ↗
    Google has a ton of smart researchers trying all sorts of stuff. They didn’t really go all in on any one thing. They hedge their bets.
    But they suck at harnesses, developer tooling etc. their internal environment is very complex and an intern on a MacBook with codex can probably move faster than a seasoned deepmind engineer
  3. nolist_policy · 1786000571 · focus · HN ↗
    > Anyway, the actual theory is that Google and Meta have fallen behind because they've been playing by this playbook of focusing on scale and training data, whereas OpenAI and Anthropic have done so well because they are likely doing much more interesting things to improve their models over time.
    Google Gemma disproves this
12. [deleted] · 1785952537 · focus · HN ↗
  [deleted]
13. deeviant · 1785953447 · focus · HN ↗
  I think it's just more about market incentive. At it's core, LLMs are bad for google's previous business model, which was to send you to as many sites 'good enough' for what you were looking for and plant Ad land mines along the way, in the search results and in the websites themselves.
  The new paradigm is you ask the llm a question, get the answer and cutout the middle man. (yes the answer may or may not be as good as the old google result, but for the sake of the argument lets say it is), Google was in danger of simply getting their arm cut off. so they focused on scaling so they could add LLMs to the search, which they largely have. You can't offer an opus like model on something as big as search (and which is offered for 'free'), so they focused on that model, and the infrastructure to run it, because they cannot afford to lose search.
  Meanwhile, they know the power of frontier models, they are working to have the infrastructure to be a huge player in them and I'm sure they will have a frontier capable model, eventually. They are playing a longer game, because they can, and I think it's going to work out very well for them.
14. ralph84 · 1785965130 · focus · HN ↗
  Google was offering researchers the Bell Labs/Xerox PARC model of comfortable budgets and pay but capped upside. And just like with Bell Labs and Xerox PARC the inventions at Google got productized elsewhere by people chasing the uncapped upside. Google would have been happy to keep LLMs in the research lab forever and never productize any of it. ChatGPT forced their hand.
15. chermi · 1785970930 · focus · HN ↗
  This makes a lot of sense to me. Probably doesn't explain everything but I could see it explaining a lot. Could also explain openai and anthropic delaying IPO (among other factors)
16. [deleted] · 1785972755 · focus · HN ↗
  [deleted]
17. SamvitJ · 1785973112 · focus · HN ↗
  From what I've heard, DeepMind's pay structure is not tied to Google compensation bands. Which means that top performers and key hires can be and are compensated extremely generously if the need calls for it. Another Alphabet subsidiary, Waymo, was well-known for doing this back in the day.
  But yes, even large RSU grants cannot replicate the upside of joining a company that increases in valuation 1000X, but to be fair, that is not a position the vast majority of OpenAI or Anthropic employees find themselves in either.
18. elAhmo · 1786018089 · focus · HN ↗
  DeepMind is just a part of Google which does research stuff, and Google is a massive company that does loads of things but mostly sells ads.
  OpenAI and Anthropic are in a completely different game, their primary business model is making a product out of advancements that come out of DeepMind and co.

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