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OpenAI unveils its first custom chip, built by Broadcom

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Re: OpenAI unveils its first custom chip, built by Broadcom

#211

Post by nickvec »

sharkjacobs wrote: post #61

> Developed from design to production in nine months, accelerated by OpenAI’s models > the use of OpenAI models to accelerate parts of the design and optimization process. I wish there was more about this. As is I kind of have to assume that this is just meaningless marketing, like saying development was accelerated by Microsoft Office or their 5k LG Ultrafine 40-inch monitors. Like, if this was as big a deal as it k…

I feel like "the use of OpenAI models to accelerate parts of the design and optimization process" just means that engineers were using ChatGPT to sanity check their designs and suggest potential optimizations, though that's just my take (and I'm quite cynical about AI marketing in general!)

Re: OpenAI unveils its first custom chip, built by Broadcom

#212

Post by sometimelurker »

londons_explore wrote: post #192

I wanna see an inference chip where the weights are part of the rom of the chip. There would be 1 multiplier per weight (and since they're constant, the whole thing turns into a bunch of simple adders), and the total pipelined system throughput would be one token per clock cycle. That means you can probably have millions of users simultaneously using a single bit of silicon, with perhaps 500 million tokens per second…

this appeared some time ago, https://taalas.com/, but I'm sure there's others thinking these same thoughts. this would be best for small models imo, nothing frontier because that changes too fast

Re: OpenAI unveils its first custom chip, built by Broadcom

#213

Post by dmitrygr »

dpe82 wrote: post #104
Aurornis wrote: post #98

Earlier quoted context omitted.

> 1) OpenAI genuinely have AI technologies that can improve chip design (bold, unlikely claim, needs evidence) Chip design languages (HDLs like Verilog or VHDL) are well understood by LLMs. They don’t need specialty tools to use GPT-5.5 or other LLMs with them. You could even try it yourself with open source chip design tooling if you wanted to see it.

I don't understand why you're getting downvoted. I've used GPT-5.5 and Opus both for FPGA design with good results. We built a lot of tooling around it to help the models, but even without that they're definitely capable of designing digital logic.

My guess: it is that those who KNOW the subject realize that LLMs suck at it, and those who do not, do not realize it, since their output is plausible, and sometimes even works.

This actually plays out across every field and is well documented. An expert can recognize the hallucinations and bullshit coming out of LLMs, while non-experts see plausible output and do not know enough to know it is BS.

Re: OpenAI unveils its first custom chip, built by Broadcom

#214

Post by cruffle_duffle »

gpm wrote: post #118
wongarsu wrote: post #99

Earlier quoted context omitted.

A hard sell right now . The rate of change will slow down

Yes, but with current architectures world knowledge is baked into the weights. We might stop figuring out how to make models better, but the world keeps changing, science is going to keep making progress at understanding the world, etc. This creates a significant minimum rate of change and I'm pretty skeptical that it's worth baking weights into silicon as a result.

I mean it just depends on the price of the chip. You might just replace the chip like you would any other component. Like a video game cartridge or something.

Re: OpenAI unveils its first custom chip, built by Broadcom

#215

Post by gaigalas »

KeplerBoy wrote: post #179
gaigalas wrote: post #154

But nvidia's moat is software support, isn't it?

You don't need a whole lot of software support if you just want to serve a single family of LLMs.

A lot of companies that serve a single family of LLMs seem to prefer nvidia though. Why is that?

It's not just good drivers, which is what moats them for games and ML. It's a multi-decade work of making chips that are nice to program for and software infrastructure around them.

Apple and Google have excelent chips, yet they needed to invest a lot in long-tail software projects to make those chips do actual premium work. Still not state of the art for serving LLMs (although Google is strong in that, mostly because it piggybacked on previous chip-related software work for phones and so on).

Re: OpenAI unveils its first custom chip, built by Broadcom

#216

Post by luqtas »

NitpickLawyer wrote: post #198
xnx wrote: post #160

Earlier quoted context omitted.

Impossible to know. Could be fake/aspirational roles to impress investors with their grand vision.

Jesus. This is tinfoil hat territory now. Why would they fake something like that? ANY company in this field would try to become free from nvda. Goog has done it already, amazon has their own thing, so it can be done. Not saying they'll 0shot this vertical, but ffs, they don't need to fake anything. They are making an effort, and it would be insane to think they aren't. Might work, might not work, but to even think t…

https://antoniocortes.com/en/2026/03/10/ghost-jobs-the-econo...

Re: OpenAI unveils its first custom chip, built by Broadcom

#217

Post by CrzyLngPwd »

smallmancontrov wrote: post #110
CrzyLngPwd wrote: post #66

Earlier quoted context omitted.

Too many Rs.

Too many? But there are only two Rs in strawberry, how can that be too many?

You are correct. I don't know why I thought there were 5 Rs in strawberry, and now I look properly I can count them correctly, there are indeed 6 Rs in strawberry.

I am sorry for initially giving an incorrect answer.

Re: OpenAI unveils its first custom chip, built by Broadcom

#218

Post by nemonemo »

NitpickLawyer wrote: post #144
Catloafdev wrote: post #96

Earlier quoted context omitted.

It'd be cool to see more of this type of thing, but I have to imagine the ability for it to be updated to a brand-new model as new models come out is limited. If that is the case, it's going to be an extremely hard sell.

> extremely hard sell. It really depends on the pricepoint at which they can get a board. If they can do a ~32B model for 1k$ and a size of an external HDD, I'd buy one now, even knowing that it won't be upgradeable / the model remains fixed. The speeds they've shown are a quality of its own, and there's plenty you can do with such a model and faster than instant responses.

Maybe in 10 years when the tech matures, but IMO now seems a bit too early to have a tech like this. It is like intelligence without evolution or progress.. yes it can be used in some niche markets, but difficult to be generic.

Re: OpenAI unveils its first custom chip, built by Broadcom

#219

Post by Lukas_Skywalker »

knicholes wrote: post #206
baq wrote: post #199

Earlier quoted context omitted.

I didn’t downvote, but the OP is either a troll or someone who doesn’t want to notice he doesn’t know what he’s talking about. Either way we want less of that on HN.

I'll acknowledge that I don't know what I'm talking about. I really appreciated the clarity! Surely you find value in knowing that creating your own custom chips is almost doable by someone who doesn't know what they're talking about! (also, I am a troll, but in this case, just clueless)

Maybe the confusion stems from the word "chip". Creating a chip usually means designing and producing a microcontroller or a processor, not a printed circuit board that you populate with existing chips.

Re: OpenAI unveils its first custom chip, built by Broadcom

#220

Post by WASDx »

dcchambers wrote: post #188
nickpinkston wrote: post #86

This is very cool to see - seems like soooo much efficiency waiting to be unlocked at the chip level. What's everyone think of Taalas? They're actually burning the LLM model into the silicon, with some onboard memory for fine-tuning. They claim huge cost / latency wins. Super fast demo live at: https://chatjimmy.ai/ https://taalas.com/ https://www.reddit.com/r/singularity/comments/1r9frzk/taalas...

I think hardware like this is the future for LLM-providers once we reach a point where the models aren't advancing much any more. You could argue we're close now. The hyperscalers like AWS will made great use of these to serve up models that will be relevant for several years. But right now, we're still seeing significant bumps in model quality every couple of months - especially with open-weight models like Deepseek…

I see only these two possibilities:

1. If LLMs keep improving, burning models onto silicon becomes obsolete too fast and is not worth doing. Outcome: We keep getting better LLMs. 2. If LLM improvements slow down, they will be burned onto silicon. Outcome: We get faster, cheaper and energy-efficient LLMs.

Either way sounds great to me. It will certainly be a mix so we can even get both.

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