Wow. Jeff and Sanjay both departing. Truly end of a golden era.
There is an entire cohort of work-optional very senior engineers for whom one of the last reasons for hanging on was "at least Jeff and Sanjay are around".
Their entire business is predicated on search dominance, which is now on much shakier footing. Agreed that those comments were ridiculous pre-ChatGPT, but now they have a genuine challenger.
This take only makes sense if you don’t know what people use Google search for. If you’re looking for your local Ford dealership, or to book a Carnival cruise, or need a disability lawyer, or to refinance your credit card debt, you’re searching for an ad. You’re not using Chat-GPT for that. You’re asking Chat-GPT about a research project. It’s stealing away all the hard to monetize searches and leaving the incredibly lucrative searches.
Your narrative depressed Google’s stock price for years, and bears finally gave up since they kept coming out with huge earnings beats.
That’s over half of their business, but they do have some diversification with YouTube, Play Store, and cloud services.
Some of their newer efforts like Waymo and AI hosting for Apple could turn into large businesses to make up for any lost search revenue.
They also have significant costs to maintain their search revenue, such as $20B a year to Apple alone to make Google the default search engine in Safari.
If search becomes less lucrative, they would presumably pay less for such deals.
So yeah, definitely a time of disruption for Google and they need to keep moving fast on many fronts, but they are still well positioned in multiple markets to be successful.
A model serves a different purpose from a web crawler.
I'd prefer to be able to find source material over steering a model I have no control over while managing hallucinated outputs without the ability to fact check.
Just because it sourced some materials using RAG doesn't make its outputs valid, accurate, or factual.
> Lastly, after an incredible 27-year run, Jeff Dean is at a moment where he wants to try something new, and we’re excited to support him in that. Jeff and Google Senior Fellow Sanjay Ghemawat are launching an independent public benefit corporation to accelerate discoveries in ML, science, and engineering.
Oof. Good for Jeff and Sanjay (who just joined Twitter), bu that is a big loss for Google. Google stock is down 5%. It might not be much of an exaggeration to say these two are worth ~$200 billion.
For at least a year now the standard reflexive reply to “Google seems way behind OAI and Anthropic” has been “it’ll be ok, they’ve got Dean and Hassabis.” And now they don’t. What reason is there to be bullish about Google now?
As much as everyone wants to pay accomplished celebrities, all of these companies have young nameless geniuses that are about to make one for themselves. A guard passing torch can be opportunity.
Now, whether Google is the right environment to nurture, that’s its own quandary.
Maybe they'll replace Hassabis with someone more focussed on beating OAI and Anthropic at chatbots? He always seemed a bit more into science, protein folding, new drugs and the like.
It just depends on what are the most upvoted comments in HN. If they are bearish, you can be sure that you should be bullish in your investments. Meta was supposed to be broken as a business already, OpenAI and Anthropic would be failures as well.
Couple of things come to mind. One is that Web sites tend to actively fight AI companies' crawlers while actively courting Google's crawler.
Another is that they hold the key Transformer architecture patent. If it is still relevant (which I'm not personally clueful about) and if they start enforcing it, then we may see a reprise of the situation where Microsoft made money for years every time an Android phone was sold. Regardless of that particular patent, it's probably safe to say they'll be better-positioned than anyone else if AI companies start lobbing patent nukes at each other.
A third factor that shouldn't be discounted is that Google has access to warehouses of training data that other companies don't. Google Books alone is an Alexandria-scale archive that the courts forced them to keep to themselves. Those restrictive copyright decisions may turn out to be a blessing in disguise for Google because no one else will have been able to scrape the data.
Google's weakness (well one of) is its total lack of cohesion. If the Google Books team could, they would sell access to that data in a heartbeat to boost their metrics.
Whoa. So is Jeff effectively leaving Google to work on this new venture full time? Or is the venture a side project? It sounds like the former. I’m sure he’ll still have internal access as an advisor of sorts. But this feels like a seismic change. Much larger than I initially realized?
gemma-4 is an incredibly good model, beating several others five time its' size. Hope Jeff's departure won't impact their next-gen products! And best of success for their new ventures!
Who knew the real revenue unlock wouldn’t be based on how much paranoid red-teaming the model underwent to resist users jailbreaking its ‘alignment’, and instead more on whether the model is post-trained to use ‘sed’ and ‘git’? Poor Gemini
Scientist-heavy orgs that want to solve everything in token space may overtook tool use; meanwhile Anthropic has been super focused on MCP, Claude Code etc for over a year
If you just talk to it over API (no web search) the Gemini models are extremely resistant to thinking the user may be living in a universe outside their training data. Try to discuss any news etc and they assume it’s fake or fiction
Out of the three main US AI companies' models, Gemini is obviously the less aligned (read: censored). So I really don't know what you're talking about.
WoW, so basically all senior members of GDM are now mostly gone? I thought Google was lagging in coding AI, but this suggests bigger issues.
I am not fan of the future of AI but this I am not sure how I feel about Google's (also Amazon recently laid off it's AGI team) AI initiatives blowing up before all the new AI Labs.
I don't get why Google failed here? maybe after a decade someone will write about it candidly.
If I had to guess, they have the wrong kind of bureaucracy for where things are headed - and it is manifesting through talented individuals deciding to leave.
I said for a few years to many a downvote on HN, everyone wants AI, nobody wants to pay the true costs, the AI race will turn into a "race to the bottom" that is, who can give you the most compute for the lowest cost, and still remain profitable?
Personally, In SWE, i think the industry has made a grave mistake with the agents and we're just one big Catastrophe waiting to happen. I do think that there is very real value when software engineers use these tools as something akin to exoskeletons that allow the human to do more, rather than just fully replacing them. However, I'm finding more and more that companies are slop shops and just attempting to automate all of their software engineering. That will certainly end terribly. I hope we are not cannon fodder.
For what? There are some things I want AI for because it does it well. There are some things I don't want AI for because it just makes a mess (hallucinations). Maybe the next AI will be different and we will have the conversation again.
Indeed, it kills our planet, our culture and our economy extremely well. Oh yes, and some code monkeys enjoy that it can make computer code on the side.
> I said for a few years to many a downvote on HN, everyone wants AI, nobody wants to pay the true costs, the AI race will turn into a "race to the bottom" that is, who can give you the most compute for the lowest cost, and still remain profitable?
I keep seeing this but this line of thinking doesn't make any sense. What does it really mean?
There are expensive models that increase the probability of you doing your task under a lower cost. That means you can't use Gemma for coding your new compiler - it would just be overall costlier.
Heavier models are cheaper at more complicated tasks because they use fewer turns and fewer mistakes.
Cheaper models are more likely to be cheap at less complicated tasks. Like if you just ask Gemma "Hi" it would probably be cheaper than asking Opus.
So what does this statement really mean? People don't want to pay the extra for a more costly model? Why wouldn't you? It reduces your overall cost!
Because real Fable usage starts at $20/month, and has oppressive usage limits even at that (ridiculous) monthly price.
Compared to my $3/month GLM-5.2 subscription, I have never felt like I was leaving capabilities on the table by refusing to cough up $20 for 15 minutes of Fable use per day.
This is the wrong way to look at it. If you have a complicated task , you can solve it for cheaper if you used Fable. It will use fewer turns to achieve the same result.
You can solve it for cheaper if you use GLM but if you are involved in it more, but that defeats the purpose.
The point is that there aren't many complex tasks were fable delivers a significant value increase over cheaper models.
Single prompting a very complex tasks is rare even on frontier models, because it can be done successfully only for specific situations (e.g. you have a very strong verification step the model can iterate on).
Most of my everyday usage is for smaller takes, were you don't really get the benefit of the most expensive models, and my guess is that is the case for the most users
Again this is a resolution problem. Your tasks are small enough that fit into a nice $3 quota. If you are an enterprise or a power user, the right-sizing argument doesn't work.
I'm talking about API prices - subscription is a different game.
> And gemma downloads also can be from auto CI pipelines etc. Nothing concrete
I have always found NPM download numbers truly suspect. Is no one caching? Are they estimating true number of downloads base on some estimate of cache hits?
> And gemma downloads also can be from auto CI pipelines etc. Nothing concrete
Thank you for adding some clarity to this. When I calculated 900 million downloads divided by 8.3 billion people in the world, I came with a number that made it look like about one person in 10 were downloading this model.
Hasn't that always been the case with Google? Outside of a few that are mostly good and have stuck around, I've always seen Google has having great tech but being quite bad and making products out of it.
It just tells you about their intended audience: Investors rather than consumers.
Nowadays, every company—even huge ones—prefers to be seen as a "growth opportunity", so they are trying to play up their ability to create new products which will somehow be so incredible that the line keeps moving up forever.
That said, there is definitely a correlation between companies chasing new products and leaving old ones to become crap.
I'd bet my mortgage that if the first sentence was "We've got amazing products, amazing talent, and world-class compute", you'd be in the comments complaining that they didn't put talent first.
> The moves suggest that DeepMind will be absorbed into Google’s broader business. [...]
> They added that while Google DeepMind would not become purely commercial, it was integrating further into Google’s business.
I guess might be quite a change (but writing was on the wall, the Deepmind -> Google Deepmind part was the first step)
This seems bad for AI safety/risk. Does DeepMind have any checks on model alignment now? What's stopping them from using AI for military/surveillance purposes?
They already quietly agreed to "all lawful use" with the Pentagon, to no real fanfare. Gemini Slaughterbot Edition, coming soon to a DHS facility near you?
If all the other AI companies are promising AGI by Q4 of next year, what else can you do to satisfy shareholders than also jump on that same bandwagon?
This is a promotion for Demis and this could be a path for Demis to be CEO of Alphabet in the future in the AI era.
Google already invested in Discovery Loop (Jeff Dean, Orol Vinyals, Quoc Le and Sanjay Ghemawat's company), so what is happening is still a win in investment terms.
The question is about Sundar's future at Google, he is a mobile era CEO at Alphabet and I would hazard a guess he will probably step down in less than 3 years.
I don't see Demis becoming CEO. He's a scientist and researcher. He wouldn't want to be bogged down by minutiae of corporate politics, org structure, government relations, mobile hardware, etc. Chair lets him have authority to explore any path of interest without overhead of operations.
My impression, inside and out of G, was that Sundar (and Ruth) were about scaling down R&D expenses (as a fraction of revenue), and focusing on exploiting the monopolies.
Perhaps now there could be a shift back to investing in R&D to get fresh monopolies.
The labs are all very interested in bio right now. Demis is working on Isomorphic rn (Google's version of that) but I could imagine a lab tempting him away to work on their equivalent if it had stronger momentum
We'll know that we've reached AGI when a key conservative political belief in the US is that AIs are not people and do not deserve rights.
We'll know that we've reached the singularity when there's a mysterious and superintelligent AI entity with technology and motivations that we as humanity do not understand and have no control over. Not sure why we want that, exactly, but that'll be the big sign.
That's the fun part. We don't. Could have happened 10 years ago without us noticing. I don't expect my skin cells to be able to recognize "me" anymore than I expect we will be able to recognize a superintelligent AGI. If it arrived 10 years ago, then the last 10 years could simply be its PR campaign. We wouldn't even be able to tell if it was successfully achieving its "goals" or not, assuming an AGI even has "goals"
1) I think about this a lot. The AI overview has already destroyed the need to even look further down the page for a lot of people. And if you look further down the page, there is often a whole page of AI generated blog spam, which is in turn being regurgitated by the AI overview up-top. The AI overview often regurgitates a completely false reddit comment from two days ago as well. That AI generated blog spam is probably reading the AI overview.
Can we please stop saying anything about "AGI"? I remember when people would be like "AGI in 3 months" / "AGI in 2024" / "AGI is confirmed in 2025" like stop, you don't know if it's even a thing, let alone if it's coming/imminent.
Public warning: please don't trade on Ed's idiotic analyses. Or if you do, look at his track record so far, and apply the Kelley Criterion to your bet sizing.
Ed Zitron has predicted 16 of the last 0 AI bubble bursts...
But more seriously, this has to do with DeepMind falling way behind the frontier in intelligence and cost per task. There's basically no reason to use a Gemini model today.
"Based on estimates of their burn rate and historic analyses, I hypothesize that OpenAI will collapse in the next 12-24 months unless it raises more funding than in the history of the valley and creates an entirely new form of AI."
And they did raise new funding as he predicted...Since July 2024, OpenAI has raised or secured roughly $170 billion in new capital. Numbers never see before. So yes its the one, and remarkably right so far.
Notice how he didn't say "I predict they will raise new funding", he predicted collapse, with the implicit retort that there's no way they will raise more funding than has ever been done before and invent a whole new AI. He was mocking the supposed things that would need to happen. He strongly assumed collapse.
2 years these charlatans have had their "imminent collapse" predictions repeatedly wrong, meanwhile all valuations, AGI progress in unsolved problems, and frontier leadership have been repeatedly vindicated that we are beginning ASI / the singularity.
Oh, come on. He's not perfect, but compared to CEOs and researchers predicting AGI and complete economic upheaval every 3 months, he's looking very good. He's no more a charlatan than Altman is.
His predictions (while often wrong) are at least somewhat justified and backed up by genuine scoops and original research. Altman goes on podcasts and talks about building Dyson spheres for energy.
Each generation of model is more expensive to train and run than the last.
More efficient hardware? That means throwing out billions of dollars worth of existing hardware and buying billions more in hardware. The cheapest hardware is the stuff they already have because spending $70B in hardware to halve a $2-4B electricity bill just doesn’t make financial sense (and that’s if doubling hardware efficiency can happen before they go under).
If they cut costs by using smaller models, they are then racing to the bottom vs China which seems hard to do (especially with China’s cheap solar energy).
As it stands, the leaked financials prove him correct. Given their losses (not counting restructuring) they are going to need enough funding to buy any of the bottom 300-400 of the F500 companies outright just to keep the lights on for the next year.
To say that’s an outrageous amount isn’t overstating in the slightest.
Given they are already being forced to drop inference prices in an attempt to compete with Chinese providers, I don’t know if billionaire investors will be willing to hand out that much money this time around if they can’t generate enough value to break even despite the hype.
Wow. Jeff and Sanjay both departing. Truly end of a golden era.
There is an entire cohort of work-optional very senior engineers for whom one of the last reasons for hanging on was "at least Jeff and Sanjay are around".
Google will be considered "the new IBM" in 20 years.
People have been saying that for over a decade now, and their business is still going.
Their entire business is predicated on search dominance, which is now on much shakier footing. Agreed that those comments were ridiculous pre-ChatGPT, but now they have a genuine challenger.
This take only makes sense if you don’t know what people use Google search for. If you’re looking for your local Ford dealership, or to book a Carnival cruise, or need a disability lawyer, or to refinance your credit card debt, you’re searching for an ad. You’re not using Chat-GPT for that. You’re asking Chat-GPT about a research project. It’s stealing away all the hard to monetize searches and leaving the incredibly lucrative searches.
Your narrative depressed Google’s stock price for years, and bears finally gave up since they kept coming out with huge earnings beats.
People 100% are asking ChatGPT for all those things.
That’s over half of their business, but they do have some diversification with YouTube, Play Store, and cloud services.
Some of their newer efforts like Waymo and AI hosting for Apple could turn into large businesses to make up for any lost search revenue.
They also have significant costs to maintain their search revenue, such as $20B a year to Apple alone to make Google the default search engine in Safari.
If search becomes less lucrative, they would presumably pay less for such deals.
So yeah, definitely a time of disruption for Google and they need to keep moving fast on many fronts, but they are still well positioned in multiple markets to be successful.
I disagree
A model serves a different purpose from a web crawler.
I'd prefer to be able to find source material over steering a model I have no control over while managing hallucinated outputs without the ability to fact check.
Just because it sourced some materials using RAG doesn't make its outputs valid, accurate, or factual.
So is IBM.
Isn't IBM still going?
> Lastly, after an incredible 27-year run, Jeff Dean is at a moment where he wants to try something new, and we’re excited to support him in that. Jeff and Google Senior Fellow Sanjay Ghemawat are launching an independent public benefit corporation to accelerate discoveries in ML, science, and engineering.
Oof. Good for Jeff and Sanjay (who just joined Twitter), bu that is a big loss for Google. Google stock is down 5%. It might not be much of an exaggeration to say these two are worth ~$200 billion.
For at least a year now the standard reflexive reply to “Google seems way behind OAI and Anthropic” has been “it’ll be ok, they’ve got Dean and Hassabis.” And now they don’t. What reason is there to be bullish about Google now?
Data centers, TPUs, customers, data streams, more money than god, most mature crawler system
Are any of those advantages getting stronger over time? I guess TPUs but Google is selling several gigawatts to Anthropic
Google owns 14% of Anthropic. If Anthropic gets to superintelligence, Google wins as well. Google doesn't really need a frontier lab of its own.
Crawler and Google Scholar and Google Books.
> Data centers, TPUs
Those 2 are definitely NOT Google's strong points. Maybe by means of marketing.
Oracle, Amazon, Microsoft, Equinix and many more are in the data center race.
As for TPUs... Broadcom, Mediatek and all the other partners you hear less about are likely more important. Google just has the flashy media outreach.
As much as everyone wants to pay accomplished celebrities, all of these companies have young nameless geniuses that are about to make one for themselves. A guard passing torch can be opportunity.
Now, whether Google is the right environment to nurture, that’s its own quandary.
>all of these companies have young nameless geniuses that are about to make one for themselves
They all leave to start new companies. Everyone on the Attention is all you need paper is at a startup.
I keep hearing this, but Hassabis did not leave Google/Alphabet. He merely changed from an administrative position to a more technical one.
Maybe they'll replace Hassabis with someone more focussed on beating OAI and Anthropic at chatbots? He always seemed a bit more into science, protein folding, new drugs and the like.
It just depends on what are the most upvoted comments in HN. If they are bearish, you can be sure that you should be bullish in your investments. Meta was supposed to be broken as a business already, OpenAI and Anthropic would be failures as well.
Couple of things come to mind. One is that Web sites tend to actively fight AI companies' crawlers while actively courting Google's crawler.
Another is that they hold the key Transformer architecture patent. If it is still relevant (which I'm not personally clueful about) and if they start enforcing it, then we may see a reprise of the situation where Microsoft made money for years every time an Android phone was sold. Regardless of that particular patent, it's probably safe to say they'll be better-positioned than anyone else if AI companies start lobbing patent nukes at each other.
A third factor that shouldn't be discounted is that Google has access to warehouses of training data that other companies don't. Google Books alone is an Alexandria-scale archive that the courts forced them to keep to themselves. Those restrictive copyright decisions may turn out to be a blessing in disguise for Google because no one else will have been able to scrape the data.
Google's weakness (well one of) is its total lack of cohesion. If the Google Books team could, they would sell access to that data in a heartbeat to boost their metrics.
Which would be disastrous to the conglomorate as a whole. It's good for Google that they can't.
Whoa. So is Jeff effectively leaving Google to work on this new venture full time? Or is the venture a side project? It sounds like the former. I’m sure he’ll still have internal access as an advisor of sorts. But this feels like a seismic change. Much larger than I initially realized?
it's a new venture that he can then sell back to google, and continue his ongoing loop
gemma-4 is an incredibly good model, beating several others five time its' size. Hope Jeff's departure won't impact their next-gen products! And best of success for their new ventures!
Who knew the real revenue unlock wouldn’t be based on how much paranoid red-teaming the model underwent to resist users jailbreaking its ‘alignment’, and instead more on whether the model is post-trained to use ‘sed’ and ‘git’? Poor Gemini
Scientist-heavy orgs that want to solve everything in token space may overtook tool use; meanwhile Anthropic has been super focused on MCP, Claude Code etc for over a year
Gemini isn't as heavily aligned as OAI / Ant models ..?
Yes, Gemini let's me do SARS-CoV-2 evolution research (perfectly safe, should never be blocked but is impossible with OAI/Ant)
If you just talk to it over API (no web search) the Gemini models are extremely resistant to thinking the user may be living in a universe outside their training data. Try to discuss any news etc and they assume it’s fake or fiction
Out of the three main US AI companies' models, Gemini is obviously the less aligned (read: censored). So I really don't know what you're talking about.
What do you mean by scientist-heavy orgs solving everything in token space? I feel like they use them to make or run tools almost exclusively.
WoW, so basically all senior members of GDM are now mostly gone? I thought Google was lagging in coding AI, but this suggests bigger issues.
I am not fan of the future of AI but this I am not sure how I feel about Google's (also Amazon recently laid off it's AGI team) AI initiatives blowing up before all the new AI Labs.
I don't get why Google failed here? maybe after a decade someone will write about it candidly.
> don't get why Google failed here?
If I had to guess, they have the wrong kind of bureaucracy for where things are headed - and it is manifesting through talented individuals deciding to leave.
> Google DeepMind: We are building strong momentum: Flash is in high demand, our Cyber model is live, and Gemma models have surpassed 900M+ downloads
Considering these are the best stats they could find, gemini usage+general situation must be really, really bleak.
High demand means nothing. A model being live is nothing to brag about. And gemma downloads also can be from auto CI pipelines etc. Nothing concrete
> Flash is in high demand
I said for a few years to many a downvote on HN, everyone wants AI, nobody wants to pay the true costs, the AI race will turn into a "race to the bottom" that is, who can give you the most compute for the lowest cost, and still remain profitable?
Does everyone want AI?
Single data point; no, I don't. I preferred the pre-AI world. It makes me sad that we'll never see it again.
Personally, In SWE, i think the industry has made a grave mistake with the agents and we're just one big Catastrophe waiting to happen. I do think that there is very real value when software engineers use these tools as something akin to exoskeletons that allow the human to do more, rather than just fully replacing them. However, I'm finding more and more that companies are slop shops and just attempting to automate all of their software engineering. That will certainly end terribly. I hope we are not cannon fodder.
You could always become Amish and then it all goes away... ;)
I think (hope?) we will.
Check out the New Luddite movement [1] [2]
[1] https://www.cnn.com/2025/10/08/business/ai-luddite-movement-...
[2] https://en.wikipedia.org/wiki/Neo-Luddism
For what? There are some things I want AI for because it does it well. There are some things I don't want AI for because it just makes a mess (hallucinations). Maybe the next AI will be different and we will have the conversation again.
Indeed, it kills our planet, our culture and our economy extremely well. Oh yes, and some code monkeys enjoy that it can make computer code on the side.
I guess it should be said, of everyone who wants AI, they don't want to pay the expense for it to the level they want to use it.
No.
But people want what AI does for them. It's a tragedy of the commons situation.
That said though, Flash isn't it. The prices on the latest flash models put Sonnet and Terra to shame.
> I said for a few years to many a downvote on HN, everyone wants AI, nobody wants to pay the true costs, the AI race will turn into a "race to the bottom" that is, who can give you the most compute for the lowest cost, and still remain profitable?
I keep seeing this but this line of thinking doesn't make any sense. What does it really mean?
There are expensive models that increase the probability of you doing your task under a lower cost. That means you can't use Gemma for coding your new compiler - it would just be overall costlier.
Heavier models are cheaper at more complicated tasks because they use fewer turns and fewer mistakes.
Cheaper models are more likely to be cheap at less complicated tasks. Like if you just ask Gemma "Hi" it would probably be cheaper than asking Opus.
So what does this statement really mean? People don't want to pay the extra for a more costly model? Why wouldn't you? It reduces your overall cost!
> Why wouldn't you? It reduces your overall cost!
Because real Fable usage starts at $20/month, and has oppressive usage limits even at that (ridiculous) monthly price.
Compared to my $3/month GLM-5.2 subscription, I have never felt like I was leaving capabilities on the table by refusing to cough up $20 for 15 minutes of Fable use per day.
where are you subbing to GLM-5.2? i've been meaning to try it out and for $3 it's a no-brainer to just load it up and give it a shot.
This is the wrong way to look at it. If you have a complicated task , you can solve it for cheaper if you used Fable. It will use fewer turns to achieve the same result.
You can solve it for cheaper if you use GLM but if you are involved in it more, but that defeats the purpose.
The point is that there aren't many complex tasks were fable delivers a significant value increase over cheaper models.
Single prompting a very complex tasks is rare even on frontier models, because it can be done successfully only for specific situations (e.g. you have a very strong verification step the model can iterate on).
Most of my everyday usage is for smaller takes, were you don't really get the benefit of the most expensive models, and my guess is that is the case for the most users
> The point is that there aren't many complex tasks were fable delivers a significant value increase over cheaper models.
Strong disagree on this. Any decently complicated task like a refactor is going to be more likely to be solved by Fable than by Gemma 3B or whatever.
I have personally tried to use Sonnet over Opus for tasks and Sonnet gets things right sometimes and at other times I wish I had just paid higher.
This is the standard pattern I keep seeing and I can have a bet with you that it would stay like this.
It's not cheaper if the price of admission is $20 for the first taste. And it's definitely not cheaper to pay per-token versus using my GLM-5.2 quota.
Again this is a resolution problem. Your tasks are small enough that fit into a nice $3 quota. If you are an enterprise or a power user, the right-sizing argument doesn't work.
I'm talking about API prices - subscription is a different game.
> And gemma downloads also can be from auto CI pipelines etc. Nothing concrete
I have always found NPM download numbers truly suspect. Is no one caching? Are they estimating true number of downloads base on some estimate of cache hits?
> And gemma downloads also can be from auto CI pipelines etc. Nothing concrete
Thank you for adding some clarity to this. When I calculated 900 million downloads divided by 8.3 billion people in the world, I came with a number that made it look like about one person in 10 were downloading this model.
Absolute download numbers are a pure vanity metric. Relative download numbers compared to other models tell you a little bit.
The first sentence is quite telling
>We’ve got amazing talent, world-class compute and products…
Products are third on the list. Google is an incubator for talent first and foremost. Products are an afterthought
My opinion is that you're reading way too much into this. Talent is obviously first. Without that you have no products worth speaking of.
Hasn't that always been the case with Google? Outside of a few that are mostly good and have stuck around, I've always seen Google has having great tech but being quite bad and making products out of it.
I was about to invest in Google, but your compelling observation has swayed me. Now it's obvious to me they are a dying company.
Guess I'm not taking out a second mortgage on my house anymore to invest in $GOOG.
It just tells you about their intended audience: Investors rather than consumers.
Nowadays, every company—even huge ones—prefers to be seen as a "growth opportunity", so they are trying to play up their ability to create new products which will somehow be so incredible that the line keeps moving up forever.
That said, there is definitely a correlation between companies chasing new products and leaving old ones to become crap.
I'd bet my mortgage that if the first sentence was "We've got amazing products, amazing talent, and world-class compute", you'd be in the comments complaining that they didn't put talent first.
A company is made up of people, and makes products. Products can come and go for many reasons (or any reason) but the company will always have people.
So then it is similarly telling that compute is second on the list? They have more talent than compute? Layoffs incoming?
This is also how Y Combinator operates.
Founders are first. Ideas are second.
If these products are the place that talent has brought us, of what use was the talent?
From https://www.ft.com/content/61d41764-f2f7-4906-a112-ff3073972...
> The moves suggest that DeepMind will be absorbed into Google’s broader business. [...] > They added that while Google DeepMind would not become purely commercial, it was integrating further into Google’s business.
I guess might be quite a change (but writing was on the wall, the Deepmind -> Google Deepmind part was the first step)
This seems bad for AI safety/risk. Does DeepMind have any checks on model alignment now? What's stopping them from using AI for military/surveillance purposes?
They already quietly agreed to "all lawful use" with the Pentagon, to no real fanfare. Gemini Slaughterbot Edition, coming soon to a DHS facility near you?
If all the other AI companies are promising AGI by Q4 of next year, what else can you do to satisfy shareholders than also jump on that same bandwagon?
My read: managing bureaucracy is a boring job esp. if you’re financially in a good spot.
Some think Gemini is falling behind in benchmarks so there was a shakeup at the top. I don’t agree with it.
That said, winning this LLM race is difficult given the number of talented people working on it across the world.
It's chuckle-worthy that Axios webiste reads:
> ... independent publicity [sic] benefit corporation in which Google ...
A Freudian slip? https://archive.is/SxFjr.
Woah, Jeff and Sanjay are big losses. The hits keep coming for google ai
If you lost your only 2 Senior Fellows, you deserve to be replaced yesterday
can anyone with corporate background decipher if that is good for demis or not?
It is good for Demis and Google overall.
This is a promotion for Demis and this could be a path for Demis to be CEO of Alphabet in the future in the AI era.
Google already invested in Discovery Loop (Jeff Dean, Orol Vinyals, Quoc Le and Sanjay Ghemawat's company), so what is happening is still a win in investment terms.
The question is about Sundar's future at Google, he is a mobile era CEO at Alphabet and I would hazard a guess he will probably step down in less than 3 years.
I don't see Demis becoming CEO. He's a scientist and researcher. He wouldn't want to be bogged down by minutiae of corporate politics, org structure, government relations, mobile hardware, etc. Chair lets him have authority to explore any path of interest without overhead of operations.
I agree sundar will step down but I’m not sure if this means they’re grooming Demis to takeover. I suspect not, and someone else might take over.
Similar to how Sundar was promoted, isn't it more likely to be a promotion from existing leadership (one of the product leads/SVP).
> this could be a path for Demis to be CEO in the future in the AI era
His current title is CEO of Google DeepMind. Becoming Chief Scientist of Alphabet seems to be a step away from the path to replacing Sundar, no?
P.S. I think his real interest is Isomorphic, and his new role will offer fewer distractions.
My impression, inside and out of G, was that Sundar (and Ruth) were about scaling down R&D expenses (as a fraction of revenue), and focusing on exploiting the monopolies.
Perhaps now there could be a shift back to investing in R&D to get fresh monopolies.
You're crazy of you think Demis is CEO of alphabet material. He's an accomplished AI researcher, Google does about 10000 other things than AI.
Demis is CEO of Alphabet material. He would be exceptional in that role, and Google would be wise to put him there
> mobile era CEO
He was the guy branding Google an AI-first company back when they invented the transformer.
ty!
Google loves to kick senior execs upstairs.
Whatever happened to Prabhakar Raghavan? Got kicked upstairs and we barely hear from him nowadays.
It's only a matter of time before Demis leaves and joins Anthropic or OpenAI.
He is probably itching to get to Anthropic. After all he is one of the early investors too.
As what? CEO? Demis will not take up the MTS role.
The labs are all very interested in bio right now. Demis is working on Isomorphic rn (Google's version of that) but I could imagine a lab tempting him away to work on their equivalent if it had stronger momentum
He was a protected entity (tambram)
miss me with the AGI nonsense
Lots of talk of us being at the cusp of AGI, but how will we even know when we get there? When AGI develops a religion for itself?
We'll know that we've reached AGI when a key conservative political belief in the US is that AIs are not people and do not deserve rights.
We'll know that we've reached the singularity when there's a mysterious and superintelligent AI entity with technology and motivations that we as humanity do not understand and have no control over. Not sure why we want that, exactly, but that'll be the big sign.
That's the fun part. We don't. Could have happened 10 years ago without us noticing. I don't expect my skin cells to be able to recognize "me" anymore than I expect we will be able to recognize a superintelligent AGI. If it arrived 10 years ago, then the last 10 years could simply be its PR campaign. We wouldn't even be able to tell if it was successfully achieving its "goals" or not, assuming an AGI even has "goals"
Science fiction.
Real next chapters:
1) Repair search that had been broken by AI initiatives.
2) Include less invasive AI with ads for those that need to be spoon fed.
3) Pretend to work on AGI and data centers in space.
4) Sell shovels and TPUs to the gold diggers.
1) I think about this a lot. The AI overview has already destroyed the need to even look further down the page for a lot of people. And if you look further down the page, there is often a whole page of AI generated blog spam, which is in turn being regurgitated by the AI overview up-top. The AI overview often regurgitates a completely false reddit comment from two days ago as well. That AI generated blog spam is probably reading the AI overview.
Where do real results live?
Can we please stop saying anything about "AGI"? I remember when people would be like "AGI in 3 months" / "AGI in 2024" / "AGI is confirmed in 2025" like stop, you don't know if it's even a thing, let alone if it's coming/imminent.
"Onwards!"
These guys...
The momentum is not being conserved here.
Let's see... they ruined their core search product. What's next after that bold move?
No AGI on the horizon and that ROI horizon approaching fast is going to make Ed Zitron a superstar.
If Demis Hassabis got a Nobel prize for being a Project Manager, is Zitron up for the Nobel on Economy for excellence in economic forecast?
I don't understand any of the praise for Zitron. He is saying very obvious things and gets timelines wrong all the time. What's special about that?
> If Demis Hassabis got a Nobel prize for being a Project Manager
His accomplishments are far beyond project manager. https://en.wikipedia.org/wiki/Demis_Hassabis
Nobel was awarded due to project management work. There are many thousands of scientists with work much much better than what Demis has done.
Public warning: please don't trade on Ed's idiotic analyses. Or if you do, look at his track record so far, and apply the Kelley Criterion to your bet sizing.
Ed Zitron has predicted 16 of the last 0 AI bubble bursts...
But more seriously, this has to do with DeepMind falling way behind the frontier in intelligence and cost per task. There's basically no reason to use a Gemini model today.
Tbf, he only has to get it right once.
Being right at the wrong time is indistinguishable from being wrong.
A stopped clock is also right twice a day.
Superstar? This Ed Zitron?
"Based on estimates of their burn rate and historic analyses, I hypothesize that OpenAI will collapse in the next 12-24 months unless it raises more funding than in the history of the valley and creates an entirely new form of AI."
-July 29, 2024
https://x.com/edzitron/status/1817955630784917548
And they did raise new funding as he predicted...Since July 2024, OpenAI has raised or secured roughly $170 billion in new capital. Numbers never see before. So yes its the one, and remarkably right so far.
Notice how he didn't say "I predict they will raise new funding", he predicted collapse, with the implicit retort that there's no way they will raise more funding than has ever been done before and invent a whole new AI. He was mocking the supposed things that would need to happen. He strongly assumed collapse.
2 years these charlatans have had their "imminent collapse" predictions repeatedly wrong, meanwhile all valuations, AGI progress in unsolved problems, and frontier leadership have been repeatedly vindicated that we are beginning ASI / the singularity.
Oh, come on. He's not perfect, but compared to CEOs and researchers predicting AGI and complete economic upheaval every 3 months, he's looking very good. He's no more a charlatan than Altman is.
His predictions (while often wrong) are at least somewhat justified and backed up by genuine scoops and original research. Altman goes on podcasts and talks about building Dyson spheres for energy.
You can't imagine OpenAI being a multi-trillion dollar company?
Open weights will drop costs, but distribution matters. OpenAI has that.
Costs will come down. Deep entrenchment will not.
How will costs come down?
Each generation of model is more expensive to train and run than the last.
More efficient hardware? That means throwing out billions of dollars worth of existing hardware and buying billions more in hardware. The cheapest hardware is the stuff they already have because spending $70B in hardware to halve a $2-4B electricity bill just doesn’t make financial sense (and that’s if doubling hardware efficiency can happen before they go under).
If they cut costs by using smaller models, they are then racing to the bottom vs China which seems hard to do (especially with China’s cheap solar energy).
As it stands, the leaked financials prove him correct. Given their losses (not counting restructuring) they are going to need enough funding to buy any of the bottom 300-400 of the F500 companies outright just to keep the lights on for the next year.
To say that’s an outrageous amount isn’t overstating in the slightest.
Given they are already being forced to drop inference prices in an attempt to compete with Chinese providers, I don’t know if billionaire investors will be willing to hand out that much money this time around if they can’t generate enough value to break even despite the hype.
AI is for retards.