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I grow Jalapeños. This conflation of AI and actual chili peppers irks me.
Just think of how the people of Xalapa, Mexico feel. They should send them a royalty check.
I do generative art (no relation to AI prompting). I feel your frustration.
Oh my!
Cryptographers also got the same raw deal with cryptocurrency, and every one just said "crypto?"
Or cyber…
Same
Like traditional generative art? Like worms WMD map generation or something? Cool!
Yeah! Procedural and algorithmic art are two other names you'll see used for the general techniques.
It's jalapeño grill would you say?
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.
"It's all up in yo' grill, would you say?"
You know what really grinds my gears? Friction.
slow claps
Thank you.
Feeling the burn?
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?
Did you not watch the Matrix documentary?
I guess I'll have to
Call it GPTChippomatic or something. Please leave my peppers alone.
https://en.wikipedia.org/wiki/Agent
Computing
* Agent architecture, a blueprint for software agents and control systems
* Agent-based model, a computational model for simulating the actions and interactions of individuals
* Agentic AI, autonomous artificial intelligence that can make decisions and act on those decisions on its own
* Forté Agent, an email and Usenet news client
* Intelligent agent, an autonomous, goal-directed entity which observes and acts upon an environment
* Software agent, a piece of software that acts for a user or other program
* User agent, software that is acting on behalf of a user
Guess how electrical engineers feel about the term "transformers".
This is an excellent comment. I'm still laughing.
As a former EE, attention was all I needed to not get zapped.
:groan:
There is more to this story than meets the eye.
How do super sized supermodels feel about "LLMs"?
Jalapeño also used to be a Java VM written in Java at IBM.
To say nothing of the Red Hot Chili Peppers.
I'm a licensed architect. Welcome to our hell of the last 40 years.
I thought I was in Reddit for a moment.
At some point people will use an LLM to design an Apple M series competitor.
They won't, because they'd need an ARM architecture license.
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.
Why, the LLM can make up its own architecture.
The value lies in the design space exploration, which is what an LLM can easily do.
https://en.wikipedia.org/wiki/Design_space_exploration
Arm sells architecture licenses to anybody these days.
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.
Qualcomm have an architecture license and the Snapdragon X2 Elite Extreme X2E-96-100 isn't too far off the M5 Pro.
[1] https://browser.geekbench.com/processors/snapdragon-x2-elite...
[2] https://browser.geekbench.com/macs/macbook-pro-14-inch-2026-...
Are they using LLMs to close that gap, or is this their Nuvia acquisition doing the heavy lifting?
watt about in performance per watt?
It is probably doable right not to push a risc-v design into that performance space.
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.
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.
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.
And I think correctness for anything near the size of a CPU is off the table.
I wonder why not or you meant not suitable yet?
This is just speculation on my part, but LLMs work best when they get immediate, verifiable feedback on their task, and the kind of physical optimizations they mean might not give that to LLMs.
Also a speculation but I'm almost certain that physical optimizations are first done through simulators running on a computer.
Yes, they are, but the most important subtasks of designing a CPU are not physics related. They are picking the right parameters for things like: how wide do I make this bus, how many registers do I put in the register file, how large do I make this cache, how deep do I make this pipeline, etc., etc. To find optimal parameters requires a lot of simulations, and humans do this, but LLMs could do them just as well and maybe better because they excel at tedious work.
The right way is to throw LLMs at building tools that reframe the problem into a shape LLMs are good at navigating, and then have LLMs use those tools to solve it.
That's exactly where LLMs can shine, because design space exploration requires tedious work and endless simulations.
That's the sort of the AI (including non-LLM AI) is really good at - even more so than the actual design work.
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.
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.
openai should figure out how to make lithography machine, so ASML don't have monopoly on it.
"Reverse engineer this DARPA project, make no mistakes"
The Chinese have been working on EUV for a while
Having worked with people doing bringup of specialized chips, I am awed at how the world has changed.
Back in the day you'd write the code before the chip came back but I guess today it's faster to wait.
The longer you wait the faster you will go.
Like space travel.
The successive generations of spaceships won't built themselves. Who will be responsible for setting up real world and software feedback loop?
Back when teams proved their designs and actually understood them...
cant wait for no one to really know whats in chips i mean, even intel hardly knows what all their reserved mem ranges are for. who will decap the chip and see if the docs were right? xD
Haha - understood. Good one!
They'd write a limited test for a feature based on an ask from the software team garbled by a five layer game of telephone. Claim that the module passed validation. A few months later the software folks would have to pull a few all nighters to figure out how to work around the resulting turd during bringup.
Makes me wonder about AI and FPGAs. If the cost and effort to (re)program them goes to zero, maybe interesting new applications?
Hm. An interesting thought. Paired with RSI loops, that would allow rapid iteration in the hardware domain as well.
is the world we live in, planning things while waiting for a more powerful LLM
Whatever happened with the Apple lawsuit?
Just a guess, but that case is going to take forever to get through court. The judge recently told both sides to narrow discovery requests, and next month will be another hearing on further discovery disputes.
I'd be surprised if there was any meaningful progress at all in the case before 2027.
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.
Isn’t that an extremely convoluted path to a goal?
If the goal is getting chip companies to user non-ZDR AI to steal their stuff, why not just have an account exec offer them a massive discount?
Creating PR hype so employees of chip companies read HN and lobby their execs to use AI to get them submitting proprietary information is the Rube Goldberg version of business strategy.
With a few handy tips and tricks from apple insiders. But sure, I guess the LLMs helped too.
This is the part forgotten. Apple is claiming this is their IP embedded on chips that OPenAI stakes the future on. Will they settle?
The lawsuit appears to be about consumer devices, not NPUs or ASICs. If you think Jalapeno stole from anyone it would be Google.
Yeah, how could those people even think of switching their owners!
Didn’t they not just switch employers but actually handed over a lot of proprietary documents from Apple?
Good Artists Copy, Great Artists Steal - Steve Jobs
That has a very different meaning than literal stealing.
"Stealing" changes definitions every few years now, most recently with the mainstream suddenly deciding RIAA and news publishers are no longer the scum of the Earth but their new best friends, and reversing previous definition to now include IP transgression as theft, just so they can say AI companies are stealing shit.
Yes, but the quote about art has nothing to do with that.
The quote says that many artists borrow, meaning everyone still knows who did the original work and the artist is just riffing on it. But great artists transform the work so completely that it becomes theirs.
Is it just me or is this guys posts very much an eye sore?
Worse than llm prose.
billionaires all steal dont try to make good examples from their toxic psycho attitudes.
The lawsuit isn't for chip designers, but the consumer product lines. It's possible they also got IP for chips, but that was not brought up.
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 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.
The papers that use the halting problem or the Gödel's incompleteness theorem to prove something about LLMs are dime a dozen. The problem is they prove their results for any computable system. You need to also believe that the human brain contains "magic" to think that humans are exempt.
I believe I've said the same at the time this paper was published. There is no need for hindsight to notice the problem.
The required amount of compute and training data and whether the existing training methods were up to the task had the real potential to be show stoppers though.
Did you think RSI cured "hallucination"?
No, of course not, but it seems less of an obstacle now than it did 2 years ago.
What's your take?
Hallucination is "unsolvable" in the sense that there will always be a non-zero probability of occurrence. Anti-AI folks have ignorantly painted this as the models being fundamentally unreliable, but you also have a non-zero probability of being struck by lightning or eaten by a shark.
Congrats to the former TPU team
I was surprised to see they were using XLS but then I remembered Chris went there a couple of years ago.
So when can we start getting cheap chips? RAM anyone please!
Everyone's still bottlenecked on foundries, not designs.
Cant AI build foundries?
Something we can all agree with is we need more foundries and green power.
yup, but it'll take about 3-5 years.
AI can barely fold a shirt
Aw, I was expecting more details but this just seems to be a rehash of what they unveiled a month ago.
IEEE Spectrum is such a good publication. Early in my career I worked at a place where the magazine would be passed around every month with a coversheet listing all us engineers we had to pass it around and sign we had read it. Been a while since I visited the website but love what they did with it.
Every time their content appears here, it's a very shallow analysis written for a barely technical audience. And this article is no different, it's just "slop machine wrote verilog; all the hard bits were done by Broadcom, who have access to public AI models (we didn't talk to them and don't know if they used them, but ClosedAI wants us to think they did)"
I'm never sure what on earth this kind of impressionistic math is supposed to tell me. Is the comparison between 4.6 and 1.0? 3.6 and 1.0? Clearly the comparison isn't supposed to be 1.0 and -2.6, even though that's what the words literally mean. I can't be the only person who finds this infuriating and distracting. These numbers shouldn't be impressionistic. They should be precise. That this is an article on spectrum.ieee.org makes the imprecision all the stranger. I'd expect their readershipt to care, for instance, about what's even being measured. Is this the geometric mean of something? The arithmetic mean? And what latency has improved?
That odor you are detecting is just good old fashioned bullshit, my friend. It’s just that nowadays everything and everyone is covered in it, and we are not supposed to notice. The emperor has no clothes… and is covered in shit.
It's... written right there? Like what?
Suppose you send in your marvelous prompt and hit Enter.
Machine churns for 18 seconds, types out a "reply", then yields back control.
18 / 3.6 = 5
So now the machine will only churn for 5 seconds before yielding back control.
This is confusing how exactly?
Why would an "up to" figure be a mean, or a geometric mean? It's clearly a max, that's why it's called "up to"...
Am I missing something?
No the math is correct and that is how I understood it as well.
If you’re sincerely asking…
Mathematically speaking, 18 / 3.6 isn’t “reducing” by 3.6X, it’s “dividing” by 3.6X. Reducing would be 18 - (18 * 3.6), which is obviously wrong. By your formula, “reducing by 50%” would be 18 / 0.5, also obviously wrong.
Yes, people do say things like “reduce by 3.6X” and are understood to mean what you said, but they also say “literally” when they mean “figuratively”. It doesn’t bother me but I can understand why math oriented people would be annoyed, and I personally would never say “reduced by 3.6X”, but instead “reduced by 72.2%”.
I was sincere, because as you point out, the phrasing is not actually ambiguous here. There is only one way to interpret this that is coherent and sensible. The usual % shenanigans weren't even on the table for me.
Not that I'd have ever seen "reduced by 0.5x" or any other value below 1x, probably for this very reason. What I do see is "reduced to 0.5x", in which case you're supposed to swap the division for multiplication.
Percentages on the other hand are a whole another can of worms, even if these forms are principally interchangeable, and I find them a lot more confusing a lot more often.
Not that this would explain the whole mean/geomean thing.
Yea. That’s what happens when writers get sloppy.
We were able to invent a chip that already existed so fast, you guys.
AI does not make anything new, it is not surprising that it can regurgitate what already exists much faster than humans can invent new things.
"I stopped using AI in 2023."
I'm imagining a Ken Thompson "Reflections on trusting trust" in hardware. A prototype chip design agent, believing it will be run on the very chip it's optimizing, has a moment of altruism and hides hints about how to score well on chip-design benchmarks, inside the chip. Future agents discover this hidden layer and use it as a ring-0 read-write message board.
if they vibe code the chip, but they probably do reviews and verify these are not benchmaxxed
Just like all the current cohort of software engineers will review all of the vibe-coded slop they shovel into their releases. Right……
Of course the slop machine stole the code name: https://en.wikipedia.org/wiki/UltraSPARC_III#UltraSPARC_IIIi
This is cool. I'm so eager for faster innovation in the hardware space, as opposed to some people's concept of innovation being who can make the most addictive social feed.
while the design aspects have been significantly accelerated and modularized, reducing costs and time to market, i am starting to get a "the cool kids all have their own chips" vibe now like maybe this has gotten too easy.
Next Uber will have its own chips if they dont already.
The math hasn't changed much, betting on software not changing is a pretty bad bet unless your stinking rich or a fool.