Having worked with people doing bringup of specialized chips, I am awed at how the world has changed.
> When the first chips came back from the foundry in May, the team pointed its internal AI models at designing software to run benchmarks such as SemiAnalysis’s InferenceX. On DeepSeek’s multi-head latent attention kernel benchmark, performance climbed from 0.31 percent of the theoretical ceiling (set by the chip’s compute and memory bandwidth) to 88.94 percent in roughly 40 hours. Ho says this result is repeatable, so the time between when foundries deliver the first chips and when production ramps up can be reduced. “All our schedule assumptions are going to be based on the fact we have this capability now,” he says.
wmf 2 hours ago [-]
Back in the day you'd write the code before the chip came back but I guess today it's faster to wait.
threatripper 46 minutes ago [-]
The longer you wait the faster you will go.
Mistletoe 19 minutes ago [-]
Like space travel.
program_whiz 3 hours ago [-]
With a few handy tips and tricks from apple insiders. But sure, I guess the LLMs helped too.
2 hours ago [-]
stogot 2 hours ago [-]
This is the part forgotten. Apple is claiming this is their IP embedded on chips that OPenAI stakes the future on. Will they settle?
wmf 2 hours ago [-]
The lawsuit appears to be about consumer devices, not NPUs or ASICs. If you think Jalapeno stole from anyone it would be Google.
2 hours ago [-]
mathisfun123 2 hours ago [-]
You people are so weird - gossiping on a site that literally reported the news as it broke smh. It's like sitting in the back of class gossiping about the popular kids.
Newsflash that lawsuit is about product designs not accelerator ASICs. And there wouldn't be anything to steal because Apple doesn't have any DC class accelerators.
muchdoubt 3 hours ago [-]
Seems pretty obvious now that OpenAI is just hyping their models in order to get companies (in this case, chip developers) to use their products in order to learn from their (exfiltrated) IP. Any corporation would be foolish to use any of their or Microsoft’s products, particularly those with valuable IP. There’s nothing in the article that says AI did anything creative but rather that it was used for software development within the overall project. Clear misleading title. Suggest to mark this as clickbait.
karim79 5 hours ago [-]
I grow Jalapeños. This conflation of AI and actual chili peppers irks me.
amelius 4 hours ago [-]
Guess how electrical engineers feel about the term "transformers".
frangonf 4 hours ago [-]
As a former EE, attention was all I needed to not get zapped.
cyberax 4 hours ago [-]
:groan:
karim79 4 hours ago [-]
This is an excellent comment. I'm still laughing.
Lalabadie 5 hours ago [-]
I do generative art (no relation to AI prompting). I feel your frustration.
fragmede 4 hours ago [-]
Cryptographers also got the same raw deal with cryptocurrency,
and every one just said "crypto?"
monkpit 3 hours ago [-]
Or cyber…
karim79 2 hours ago [-]
Like traditional generative art? Like worms WMD map generation or something? Cool!
TomGarden 4 hours ago [-]
Oh my!
DrewADesign 3 hours ago [-]
Same
asveikau 5 hours ago [-]
Just think of how the people of Xalapa, Mexico feel. They should send them a royalty check.
damowangcy 2 hours ago [-]
I thought I was in Reddit for a moment.
Duanemclemore 2 hours ago [-]
I'm a licensed architect. Welcome to our hell of the last 40 years.
seanmcdirmid 4 hours ago [-]
Jalapeño also used to be a Java VM written in Java at IBM.
glitchc 4 hours ago [-]
Feeling the burn?
smitty1e 3 hours ago [-]
To say nothing of the Red Hot Chili Peppers.
Razengan 5 hours ago [-]
> irks me
It's jalapeño grill would you say?
karim79 4 hours ago [-]
Not sure what you're talking about. But I'll tell you, home grown Jalapeño peppers, fermented with 3% salt is the stuff of dreams.
wiml 4 hours ago [-]
"It's all up in yo' grill, would you say?"
Razengan 4 hours ago [-]
You know what really grinds my gears? Friction.
chrismarlow9 3 hours ago [-]
slow claps
honeycrispy 4 hours ago [-]
I'm annoyed that the meaning of the word "Agent" has been obliterated.
Like, why couldn't they invent a new word and not hijack an existing word?
karim79 4 hours ago [-]
Call it GPTChippomatic or something. Please leave my peppers alone.
Razengan 4 hours ago [-]
Did you not watch the Matrix documentary?
MadrasTh0rn 4 hours ago [-]
I guess I'll have to
xpct 3 hours ago [-]
Aw, I was expecting more details but this just seems to be a rehash of what they unveiled a month ago.
gozucito 3 hours ago [-]
It is surprising to me that recursive self-improvement seems more plausible now than it did in 2023. Am I the only one to be surprised?
I also remember the hang-wringing about running out of new datasets to train on. Now it appears humans are always generating more data. It's just not as cheap to acquire as legacy data? Meta has to give a deep discount on their API prices to entice people.
I thought back then that humans had a few more breakthroughs in them as meaningful as the seminal Attention is all you need paper. Enough to 100x the capabilities of LLMs back then (10x the smarts and 10x the speed simultaneously).
RSI with a 20 month turnaround for a chip to be made is not exactly breakneck speed though. Physical manufacturing and logistical constraints are going to be and remain a hard obstacle to that process for the foreseeable future.
amelius 5 hours ago [-]
At some point people will use an LLM to design an Apple M series competitor.
Lramseyer 4 hours ago [-]
Production grade CPU design is more than just the RTL (the source code.) To achieve the performance numbers that these companies get, you have to do a ton of optimization in your physical design to achieve the power/performance/area (PPA) metrics that make these products competitive. LLMs are not suitable for that kind of work.
There are people working on PPA optimization and trying to shake up how things are done, just not with LLMs.
btown 4 hours ago [-]
Something that I think is fascinating, though, is that labs are no longer beholden to the limitations of commercial design software. Want to replace your simulator and optimizer with a fully custom verifiable stack of Lean proofs of optimality and correctness? Just throw your unlimited token budget at it.
xpct 3 hours ago [-]
I don't work in the business, but my understanding was that even with these companies' budgets, it's still too expensive to do any kind of verified performance optimality.
thfuran 2 hours ago [-]
And I think correctness for anything near the size of a CPU is off the table.
xpct 3 hours ago [-]
Isn't that weird? The full knowledge of how to make such chips may one day be accessible to anyone, yet only the entrenched companies will remain the makers.
If we imagine machines being able to do the full process end-to-end, and the quality of that process only dependent on capital spent on tokens, I don't see how new companies could ever enter the market.
bhouston 4 hours ago [-]
It is probably doable right not to push a risc-v design into that performance space.
nullc 2 hours ago [-]
And be super-bankrupted by patent litigation from Apple. I don't think they're worried.
After all, they successfully threatened Adobe with spurious patent litigation unless they joined w/ apple in illegally fixing wages.
You don't think a criminal like apple would absolutely decimate any competition given the opportunity? They didn't hold back when it was a unambiguous crime, they surely wouldn't if it was merely bad for the world.
bigyabai 5 hours ago [-]
They won't, because they'd need an ARM architecture license.
nr378 3 hours ago [-]
Qualcomm have an architecture license and the Snapdragon X2 Elite Extreme X2E-96-100 isn't too far off the M5 Pro.
Arm sells architecture licenses to anybody these days.
pixl97 5 hours ago [-]
I mean you can design anything without a license. Selling it is where the problems come up. Even then there are likely places in China that would still make it for you.
cmrdporcupine 4 hours ago [-]
Or they'll just build a competitor in RISC-V instead and that's fine.
Except the problem is not restricted to the actual ISA or its HDL implementation, etc.
It's even just getting space / time in a fab at that advanced of a process node.
ramshanker 3 hours ago [-]
So when can we start getting cheap chips? RAM anyone please!
faitswulff 3 hours ago [-]
Everyone's still bottlenecked on foundries, not designs.
jeffybefffy519 3 hours ago [-]
Cant AI build foundries?
altcognito 3 hours ago [-]
Something we can all agree with is we need more foundries and green power.
senectus1 3 hours ago [-]
yup, but it'll take about 3-5 years.
geraneum 4 hours ago [-]
Whatever happened with the Apple lawsuit?
4 hours ago [-]
google234123 3 hours ago [-]
Congrats to the former TPU team
mathisfun123 2 hours ago [-]
I was surprised to see they were using XLS but then I remembered Chris went there a couple of years ago.
cute_boi 4 hours ago [-]
openai should figure out how to make lithography machine, so ASML don't have monopoly on it.
TomGarden 4 hours ago [-]
The Chinese have been working on EUV for a while
bigyabai 4 hours ago [-]
"Reverse engineer this DARPA project, make no mistakes"
Rendered at 04:11:07 GMT+0000 (Coordinated Universal Time) with Vercel.
> When the first chips came back from the foundry in May, the team pointed its internal AI models at designing software to run benchmarks such as SemiAnalysis’s InferenceX. On DeepSeek’s multi-head latent attention kernel benchmark, performance climbed from 0.31 percent of the theoretical ceiling (set by the chip’s compute and memory bandwidth) to 88.94 percent in roughly 40 hours. Ho says this result is repeatable, so the time between when foundries deliver the first chips and when production ramps up can be reduced. “All our schedule assumptions are going to be based on the fact we have this capability now,” he says.
Newsflash that lawsuit is about product designs not accelerator ASICs. And there wouldn't be anything to steal because Apple doesn't have any DC class accelerators.
It's jalapeño grill would you say?
Like, why couldn't they invent a new word and not hijack an existing word?
I remember the paper proving that hallucinations could never be fully solved back in 2024: https://arxiv.org/abs/2409.05746
I also remember the hang-wringing about running out of new datasets to train on. Now it appears humans are always generating more data. It's just not as cheap to acquire as legacy data? Meta has to give a deep discount on their API prices to entice people.
I thought back then that humans had a few more breakthroughs in them as meaningful as the seminal Attention is all you need paper. Enough to 100x the capabilities of LLMs back then (10x the smarts and 10x the speed simultaneously).
RSI with a 20 month turnaround for a chip to be made is not exactly breakneck speed though. Physical manufacturing and logistical constraints are going to be and remain a hard obstacle to that process for the foreseeable future.
There are people working on PPA optimization and trying to shake up how things are done, just not with LLMs.
If we imagine machines being able to do the full process end-to-end, and the quality of that process only dependent on capital spent on tokens, I don't see how new companies could ever enter the market.
After all, they successfully threatened Adobe with spurious patent litigation unless they joined w/ apple in illegally fixing wages.
You don't think a criminal like apple would absolutely decimate any competition given the opportunity? They didn't hold back when it was a unambiguous crime, they surely wouldn't if it was merely bad for the world.
[1] https://browser.geekbench.com/processors/snapdragon-x2-elite...
[2] https://browser.geekbench.com/macs/macbook-pro-14-inch-2026-...
The value lies in the design space exploration, which is what an LLM can easily do.
https://en.wikipedia.org/wiki/Design_space_exploration
Except the problem is not restricted to the actual ISA or its HDL implementation, etc.
It's even just getting space / time in a fab at that advanced of a process node.