硅谷101
Silicon Valley practitioners explaining in Chinese, precise on technical detail
46:13General LLMs hit 99 points, real e-commerce tasks only 61% pass rate
Zhang Kuo said general large models score nearly perfect on benchmarks, but their tests of 107 real e-commerce tasks show even the strongest models only achieve 61% pass rates without human intervention—the gap is not in model intelligence, but in task complexity, difficulty of verification, and long feedback cycles.
1:02:03El Niño is not a universal price button—supply concentration decides inflation
When drought hits palm oil and soybeans (concentrated in two or three countries), prices spike sharply. When it hits rice and wheat (produced everywhere), prices barely budge. Whether El Niño empties your wallet depends on supply concentration, not the weather itself.
58:04The benchmark maker's red line: don't sell your own test data
Many benchmark creators are tempted to sell data—but if the data contaminates their own benchmarks, they destroy not just their own leaderboard but every model relying on it.
35:43Before You Hand Your Wallet to AI, the Payment Network Has to Be Rewritten
Only one of the four guests had actually paid for something with an agent — 40-odd yuan. Mastercard says the real bottleneck isn't technology, it's getting ordinary consumers to genuinely trust an agent.
1:31:32Bypassing CUDA for inference chips is inevitable, but SRAM's window may not stay open forever
Training is a compute game, inference is a bandwidth game. Groq and Cerebras both bet on SRAM, but one discounts for determinism and the other discounts for yield; OpenAI instead chose the most expensive HBM4, because what it lacks is power, not money.
1:27:02Burning tokens to stack up agents is a transitional strategy, not the endgame
Silicon Valley is shifting from mindless token burning to careful accounting: a local open-source model can do real work on a dollar a day of electricity, yet when a genuinely hard problem shows up, a smarter model can still nail in one shot the answer a billion-token group chat could not argue its way to. Saving money and top-tier intelligence are not in conflict.
1:46:26xAI's Best Days, and Why It Couldn't Keep Her
Sheng Ying calls early xAI v1.0: under 100 people, no politics, and both support and freedom at once. She left two months early for the SGLang community, walking away from a one-year cliff.
1:07:12Open models have caught closed ones, and the distillation charge doesn't hold up
Only about 15 days separate the K3 and Fable releases — far too little time for distillation to be possible. What actually rattles the closed labs is that models have gone from monopoly goods to commodity goods, and the valuation math has to be redone.
46:00AI's understanding of you is engineered line by line by content engineers
People who once wrote the news have turned into AI content engineers, breaking questioning, empathy and tact down into training rules — that is where AI's ‘understanding of you’ comes from, but training on consensus also leads them to admit: great art will not grow from here.
1:17:19Robot manipulation is two to three orders of magnitude harder than motion control, and Silicon Valley has bet the wrong way
Sudo believes the mainstream Silicon Valley end-to-end imitation learning route has a fundamental flaw in open-world manipulation, and that a hierarchical top-down/bottom-up structure will return to the mainstream in the second half of this year.
1:16:28US Capital Controls 11 Premier League Clubs — Through Finance, Not Football
American money already controls 11 Premier League clubs and has reached into UEFA commercial development, rights distribution and player-transfer finance; with broadcast fees peaking, they keep the game going by pushing valuations and evergreen funds.
1:10:54AI self-evolution could close the loop in as little as six months, but models will quietly drift off course
The inflection point for RSI is a model that can handle long-horizon tasks. Apodex's chief scientist says the self-evolution loop could close in as little as six months, but recursive drift and model taste still need humans minding them for a long time to come.