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- Hacker News
- 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.
by delusional - Aw, I was expecting more details but this just seems to be a rehash of what they unveiled a month ago.by xpct
- 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.by 9cb14c1ec0
- I grow Jalapeños. This conflation of AI and actual chili peppers irks me.by karim79
- With a few handy tips and tricks from apple insiders. But sure, I guess the LLMs helped too.by program_whiz
- 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.by muchdoubt
- > "Ho also confirmed that the team had access to internal LLMs fine-tuned for chip design that are not available to the public. He declined to detail the models used."
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.
by peri-cl - 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.
by pama