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Articles about AI chips from podcasts, articles and papers, with links to the original sources.
On The Diary of a CEO, Professor Jiang held up a semiconductor to argue that technology is "specialization times globalization" — chips designed in California, printed by Dutch machines, made in Taiwan, assembled in China. If that trade fractures, he says, AI will not leap to general intelligence; it will be repurposed to watch people instead. The host offered a different reason to expect the same surveillance.
Asked what comes after large language models, Alex told a caller on Moonshots with Peter Diamandis to separate two things people usually merge: the job of predicting the next piece of text, which he thinks has "effectively infinite longevity," and the transformer machinery doing it, which he says is already being swapped out part by part. Dave added his own forecast that the chips underneath will move to photonics within 18 months to two years.
On Moonshots, the panel picked apart a rental index showing H100 prices rising 22% in a single month to $3.28 per GPU-hour. Dave called it a reversal of a lifetime of chip depreciation; Emad Mostaque explained why better models make the same old Hopper worth more; and the warning for companies was that the compute they assume will be there later is already sold out.
On Moonshots #288, a 4 a.m. chart about DeepSeek's new V4.1-Flash model sent the panel from cache statistics to the shopping list for an AI data center. DeepSeek says the model's lookup memory needs a quarter of the expensive high-bandwidth memory and an eighth of the SSD cache storage of its previous generation. The panel's argument was about what that does to a buildout in which, by one panelist's estimate, 40% of American capital spending goes to that one component.
On September 3, Senator Bernie Sanders and Representative Greg Casar announced legislation to permanently prohibit superintelligent AI and pause advanced development; a day earlier the White House reported unanimous G20 agreement on a non-binding, innovation-first framework. The Moonshots panel rejected the bill's single human-level threshold, then spent the rest of the segment arguing over what a credible middle position would be: universal chip logging, open weights, and a right to compute.
On Moonshots, the panel played a launch video for Redwood, an accelerator that Palo Alto startup Architect Labs says its AI designed end to end from a specification written by two architects. The company's paper reports two weeks to verified design and FPGA deployment, with a small language model running in a third week — while the headline 3.4-times efficiency figure comes from a projected Samsung 8-nanometer chip that has not been built. The panel, who disclosed they are investors and an advisor, argued the real story is a "designless" company and recursive self-improvement at the chip layer.
On Moonshots, Peter Diamandis reported back from meetings with SK hynix and Solidigm leadership with a claim that memory, not compute, now limits AI. The panel argued that a changed workload and a supplier industry scarred by past busts are pushing prices up faster than factories can respond — and that the fix may be new chip designs, including etching model weights into silicon, rather than simply paying more.
On Moonshots with Peter Diamandis, Salim Ismail argued that a Mac Studio with 512GB of unified memory changes AI spending from a perpetual per-token bill into a capital asset, with law firms and mid-sized healthcare organizations as the likely buyers. Two other panelists agreed the machine was worth having and still called Apple's AI record a long-running software failure.
On Moonshots EP #284, the panel read out the performance figures OpenAI published for Jalapeño, the inference chip it built with Broadcom, and argued that inference is moving off NVIDIA. One panelist went further, imagining an "OpenAI Compute" cloud that rents capacity to competitors — possibly even hosting an Anthropic model. Dave Blundin explained why CUDA no longer locks buyers in at inference time, and why NVIDIA's next defense is the networking between chips.
NVIDIA reported $96.2 billion in quarterly revenue and guided to $108 billion for the current quarter. On Moonshots with Peter Diamandis, the panel split over what the number proves: Dave Blundin sees a company nobody can avoid, Alex wants to know how much of the demand NVIDIA itself financed, and Salim Ismail would prefer slower growth that markets have time to correct.
On Moonshots with Peter Diamandis, the panel walked through Waymo's sixth-generation driver: a purpose-built 5-nanometer chip, fewer but sharper cameras, and an autonomous-hardware estimate falling from $115,000 to $20,000. Peter had ridden in the new vehicle; Alex objected that the West is now white-labeling Chinese hardware, and argued Waymo is heading for full vertical integration.
On Moonshots with Peter Diamandis, the panel read out a new leaderboard result: Google's Gemini 3.7 Flash on top of the AA-AnalystAgent benchmark with 60%, ahead of Claude Opus 5 at 54%. Diamandis called it proof that Google is back; Alex argued the score measures repeated reliability on spreadsheet analysis rather than frontier capability, and blamed Google Search for pushing Gemini toward speed and determinism. Emad Mostaque agreed the model was decent but said Google's problem is institutional, not a shortage of chips.