Microsoft and OpenAI end their exclusive and revenue-sharing deal

people are trying, especially for inference. For training, it’s just too high risk to tank your training I think.

TPUs are at least dogfooded by Google deepmind, no team AFAIK has gotten the AMD stack to train well.

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Google is in a different position to others in that they're the only frontier lab with a cloud infra business. It obviously makes sense to sell GPUs on cloud infra as people want to rent them. In that respect Google buys a ton of GPUs to rent out.

What's unclear to me is how much Google uses GPUs for their own stuff. Yes Gemini runs on GPUs now, so that Google can sell Gemini on-prem boxes (recent release announced last week), but is any training or inference for Gemini really happening on GPUs? This is unclear to me. I'd have guessed not given that I thought TPUs were much cheaper to operate, but maybe I'm wrong.

Caveat, I work at Google, but not on anything to do with this. I'm only going on what's in the press for this stuff.

A Opus 4.7/Gpt5.5 class model is 5 trillion parameters[1].

To run a 8 bit quantized version of that you need roughly 5TB of RAM.

Today that is around 18 NVidia B300. That's around $900,000, without including the computers to run them in.

It's true that the capability of open source models is improving, but running actual frontier models on your MPB seems a way off.

[1] https://x.com/elonmusk/status/2042123561666855235?s=20 (and Elon has hired enough people out of those labs to have a fair idea)

I did this calculation a bit ago and don't think frontier models are just a few MacBook Pro generations away. Yes numbers reliably go up in tech in general but in specific semiconductors & standards have long lead-times and published roadmaps, so we can have high confidence in what we're getting even in 3-4 years in terms of both transistor density and RAM speeds.

In mid-2028 we have N2E/N2P with around 15% greater transistor density than today's N3P, and by EOY2028 we'll likely have A14 with about 35-40% density improvement.

Meanwhile, we'll be on LPDDR6 by that point, which takes M-series Pros from 307GB/s -> ~400GB/s, and Max's from 614GB/s -> ~800GB/s.

Model improvements obviously will help out, but on the raw hardware front these aren't in the ballpark for frontier model numbers. An H100 has 3TB/s memory bandwidth, fwiw

That's not "math". That's a "wild guess", or baseless extrapolation at best.

So long as you don't require deep search grounding like massive web indexes or document stores which are hard to reproduce locally. You can do local agentic things that get close or even do better depending on search strategy, but theoretically a massive cloud service with huge data stores at hand should be able to produce better results.

In practice unless you're doing some kind of deep research thing with the cloud, it'll try to optimize mostly for time and get you a good enough answer rather than spending an hour or two. An hour of cloud searching with huge data stores is not equivalent to an hour of local agentic searching, presumably.

I think that problem will improve a little in the coming years as we kind of create optimized data curation, but the information world will keep growing so the advantage will likely remain with centralized services as long as they offer their complete potential rather than a fraction.

Also, all the cloud models don't have to be the best frontier models, and you don't need to focus on hitting the benchmark of shrinking Opus 4.7 down to a single MBP to make significant improvements. If you get it so that an Opus 4.7 benchmark-compatible model can run in $250k of datacenter capex (and associated reduced opex for power+cooling) that'd be a massive cost improvement that makes the cloud models cheaper. And for most consumers that'll probably be good enough. You don't need to run on a $5k laptop to make a big difference.

Show your working / explain your math?

I think that's just how Google is, by nature. They don't intentionally degrade their services. They just aren't a customer centric company. They run on numbers. As a corporate, it doesn't really encourage support and maintenance work either.

What do TPUs do to improve on GPUs at inference?

This doesn't get talked about enough - the GPU is weak, weak, weak. And anyone who can fix them will go to a serious AI company (for 2-3x the salary).

Apple is in a much better boat than AMD or Intel. They have a gigantic warchest and can just snap up whoever looks like a leader coming out of the bubble burst.

I guess I myself have read it too many times by now so in mind it was just 5 minute read when I made this comment... sorry..

Well, I guess in that case it is hardly a 5 minute read.

Outside of California they're sparkling ai labs.

Huh, interesting. History casts a long shadow.

One (1) year after M$ bought Nokia they wrote it off for $7.6 Billion.

There’s no upper limit to their financial stupidity.

Pot? Meet Kettle.

own 27%. but are entitled to OpenAI profits of 49% for eternity (if OpenAI is profitable or government steps in)

No and at this point tying yourself to azure is a strategic passive and anyone making such decisions should be held responsible for any service outage or degradation.

MS incentivizes feature quantity, and the leadership are employees like any other. Product improvements are not on the table unless the company starts promoting people based on it. Doesn't look this will start happening any time soon.

Don’t worry I’m sure there’s a few products without copilot integration still. They’ll get to them before too long.

> OpenAI is worth many multiples of that

valued at --which I'd say is a reasonable distinction to make right about now

When they put 10B in, they got weird tiered revenue shares and other rights. That has been simplified to 27% of OpenAI today. I don't know what that meant their 10B would be worth before dilution in later rounds.

> OpenAI is worth many multiples of that.

How?

Some food for thought:

  If GitHub flipped a switch and enabled IPv6 it would instantly break many of their customers who have configured IP based access controls [1]. If the customer's network supports IPv6, the traffic would switch, and if they haven't added their IPv6 addresses to the policy ... boom everything breaks.

  This is a tricky problem; providers don't have an easy way to correlate addresses or update policies pro-actively. And customers hate it when things suddenly break no matter how well you go about it.

Now they can use Claude Code.

Supports IPv6 just fine? Absolutely not, they have the worst IPv6 implementation of the 3 large clouds, where many of their products don't support it, such as their Postgres offering. See https://news.ycombinator.com/item?id=44881803 for more.

Github CEO threatened the entire stack was in the process of migrating to Azure.

https://thenewstack.io/github-will-prioritize-migrating-to-a...

I talked to github devs last week in person, when a lot of the AzDo team was brought over years ago the migration started happening.

I see more businesses on the office + Team stack then Google workspace. So far more.

I think the differentiator is Team, which Google for some mysterious reason can't build or doesn't want to.

It is the one thing that makes me wonder about Microsoft's future. It had seemed like they were willing to throw Windows and Xbox under the bus so long as the server cash cow continued. But it that starts to fade, they could be in some real trouble a decade from now.

Sharepoint has never not been terrible.

> They don't need to "hedge their bets" it's already a humongous win.

That's a flawed argument. Why wouldn't you want to hedge a risky bet, and one that's even quite highly correlated to Microsoft's own industry sector?

do we know whether Microsoft could have been selling secondary shares as part of various funding rounds?

my impression is that many of these "investments" are structured IOUs for circular deals based on compute resources in exchange for LLM usage

About the same as they wasted on Nokia.

I think people are looking for excuses to declare OpenAI and Anthropic teetering on the brink of failure when the actual reality is… they are wildly successful by absolutely any measure. This deal is proof. If Microsoft didn’t believe in OpenAI they wouldn’t have restructured it this way. They’d have tightened their reins and brought in “adult supervision”

If I buy oranges for $1 and sell them for $0.50 and I sell a lot of oranges, can I reasonably say that I've found a market?

Hrm..

The short answer is: it's the secretary problem.

The longer answer is; you never know whats coming next, bitcoin could have doubled the day after, and doubled the day after that, and so on, for weeks. And by selling half you've effectively sacrificed huge sums of money.

The truth is that by retaining half you have minimised potential losses and sacrificed potential gains, you've chosen a middle position which is more stable.

So, if bitcoin 1000 bitcoing which was word $5 one day, and $7 the next, but suddenly it hits $30. Well, we'd sell half.

If the day after it hit $60, then our 500 remaining bitcoins is worth the same as what we sold, so in theory all we lost was potential gains, we didn't lose any actual value.

Of course, we wouldn't sell we'd hold, and it would probably fall down to $15 or something instead.. then the cycle begins again..

A company can dilute just like that?

> It’s not more hype than product, it has found a market (making many billions in revenue)

Speculation based on selling at below cost.

> it’s not valued at trillions

Fair, it's only $852 billion. Nowhere near trillions.. you got me.

Subconsciously?!?

I feel the industry moving away from the automated slop machine, and back to conscious design. Is that only my filter bubble? Dex, dax, the CEO of sentry, Mario (pi.dev) - strong voices, all declaring the last half year a fever dream we must wake up from.

Right, but this electron box led to one of the largest (if not the largest) media revolution that has transformed the course of humanity in a frightening way we're still trying to grapple with.

Still saying "LLMs are autocorrect" isn't wrong, but nobody is saying "phones are just electrons and silicon" to diminish their power and influence anymore.

What happens when it's indistinguishable from a human speaker (in any conceivable test that makes sense)? It's like a philosophical zombie - imagine that you can't distinguish it from a human mind, there's no test you can make to say that it is NOT conscious/intelligent. So at some point, I think, it makes no sense to say that it's not intelligent.

Many people struggle to differentiate between illusion and reality, these days.

There's a sucker born every minute, after all.

> It's an illusion of intelligence.

A simulation, not an illusion. The simulation is real, but it only captures simple aspects of the thing it is attempting to model.

The lost jobs and the decrease in the demand for software engineers doesn't seem like an illusion. It might come back eventually but I wouldn't bet on it.

I've had to adjust my priors about LLMs. Have you?

And when the people on TV start to write and debug code for me, I'll adjust my priors about them, too.

In order To be confident in your claim one would think that the word intelligence must first be defined.

There is no general consensus in the scientific community, engineering community, psychology community, or any other group of humans as to what exactly counts as intelligence.

Seems like you’ve nailed the definition. Care to share your brilliance with the rest of the planet? We’re all waiting…

A recent one is the RCA of a hang during PostgreSQL installation because of an unimplemented syscall (I work at a lab that deals with secure OS and sandboxes). If the search of the RCA was left to me, I would have spent 2-3 weeks sifting through the shared memory implementation within PostgeSQL but it only took me a night with the help of Opus 4.5.

To me, that's intelligence and a measurable direct benefit of the tool.

> Curious about your definition of these terms.

Likewise - I think sometimes we ascribe a mythical aura to the concept of “intelligence” because we don’t fully understand it. We should limit that aura to the concept of sentience, because if you can’t call something that can solve complex mathematical and programming problems (amongst many other things) intelligent, the word feels a bit useless.

> definition of these terms

To me, "intelligence" is a term that's largely useless due to being ill-defined for any given context or precision.

I feel like these examples are all where human categorical thinking doesn’t quite map to the real world. Like the “is a hotdog a sandwich” question. “hotdog” and “sandwich” are concepts, like “intelligence”. Oftentimes we get so preoccupied with concepts that we forget that they’re all made-up structures that we put over the world, so they aren’t necessarily going to fit perfectly into place.

I think it’s a waste of time to try and categorize AI as “intelligent” or “not intelligent” personally. We’re arguing over a label, but I think it’s more important to understand what it can and can’t do.

Superficially? Looks like an orange, feels like an orange, tastes like an orange. Basically it passes something like the Turing test.

Scientifically? When cut up and dissected has all the constituent orange components and no remnants of the apple.

Neat, dumb question - are the tokens you prepay for good forever, or do they expire? And do they provide any assurances or SLA's about speed? (i.e. that in a year they won't decide to dole out response tokens to you at a snail's pace)

> You make your own subscription.

I'm asking because with most providers (most egregiously, with Anthropic) it doesn't work that way because the API pricing is way higher than any subscription and seemingly product/company oriented, whereas individual users can enjoy subsidized tokens in the form of the subscription. If DeepSeek only offers API pricing for everyone, I guess that makes sense and also is okay!

This account is clearly astroturfing.

One of the first things I did when openAI came out was asking it "which active politican is a spy?" - and it was blocked from the start.

I asked early, at the time people were posting various jailbreaks, never worked.

On a side note, any self hosted model I can get for my PC? I have 96 GB of RAM.

It's fun to pretend the US models have no censorship constraints.

Looks like they changed the post link to a Bloomberg article instead but kept the comments thread. So I guess he’s already aware.

> No idea if it's possible to call in @dang via at-name?

No. Email hn@ycombinator.com

https://news.ycombinator.com/newsfaq.html

Do we have proof that it's cheaper in terms of $/token/intelligence?

It isn't. That's why I said "might not be good for Gemini".