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a16z 播客：AI 是最高 stakes 的企业棋局
a16z 的 Gavin Baker 和 David George 讨论 AI 竞争，认为 Meta 重回牌局，Gemini 落后，未来可能是多模型混合。他们还探讨了算力短缺、数据中心争议等话题，但均为观点表达。
AI推荐理由 a16z 播客片段，Gavin Baker 讨论 AI 竞争格局，观点有见地但属于评论性质。包含对 Meta、Gemini 等评价，但无具体数据，信息密度中等。
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Gavin Baker谈为什么AI是史上最高风险的企业棋局：“你必须给Meta很多赞誉。他们曾出局，然后又重新入局。这真是令人惊叹。”“一年前，当Gemini如日中天时，谁能想到Gemini甚至不会在讨论中，而Muse和Meta在能力上会明显领先于他们。”“有些人走错了棋，有些人走对了。你看到有些人出局，有些人又回来。”“我不知道我们是否会称之为多模型或混合模型。我不知道世界会采用什么术语，但我认为这就是未来。”@GavinSBaker@DavidGeorge83 您的浏览器不支持视频标签。🔗 在Twitter上查看 a16z@a16z Gavin Baker和a16z的David George谈AI繁荣的现状：未来不一定是赢家通吃。实验室、开源、应用和云都可以获取价值。对智能的需求仍被严重低估。今天的重度用户有数百万，将增长到数亿。Gavin和David认为，算力短缺比AI泡沫更真实的风险，而通过建设算力是重新工业化美国的机会。在本集中，他们深入探讨了为什么算力投资回报如此之快，数据中心反弹错在哪里，将算力送入轨道的理由，为什么企业会同时运行多个模型，以及英伟达如何最终处于整个供应链的中心。00:00 引言 01:06 Gavin找不到的看跌理由 05:50 为什么实验室会削减自己收入的75% 08:05 LP对崩盘的误解 10:50 微软放缓资本支出并后悔 14:33 花费中位数100倍的工程师 17:35 为什么23岁的人比Gavin更会用AI 21:45 5亿AI用户需要多少铜 23:00 停止承诺治愈癌症 26:00 美国最富有的县满是数据中心 30:48 谁被算力价格挤出 33:05 埃隆和詹森的时代 34:25 轨道数据中心 44:40 小行星采矿 48:12 为什么微软不需要前沿模型 54:02 谁成为抽象层 55:40 每个人都想要神，Cursor想要产品 1:00:25 永远不要对詹森开火 1:07:40 当芯片不工作时会发生什么 1:12:10 芯片交易揭示了客户需求的什么 YouTube: youtube.com/watch?v=FGC4of…@GavinSBaker@DavidGeorge83 您的浏览器不支持视频标签。🔗 在Twitter上查看 🔗 查看引用推文 💬10🔄9❤️127👀34868📊19 ⚡ 由xgo.ing提供支持
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Gavin Baker on why AI is the highest-stakes game of corporate chess ever played: "You've got to give Meta a lot of credit. They were out of the game, and they got back in the game. It's just kind of amazing." "Who could have imagined a year ago, when Gemini was ascendant, that Gemini wouldn't even be in the conversation, and Muse and Meta would be significantly ahead of them from a capability perspective." "Some people have made bad moves, they've made good moves. You've seen some people come out of the game, others come back in." "I don't know if we're going to call it multi-model, a hybrid model. I don't know what terminology the world is going to settle on but I think that's the future." @GavinSBaker@DavidGeorge83 Your browser does not support the video tag. 🔗 View on Twitter a16z@a16z Gavin Baker and a16z's David George on the state of the AI boom: The future doesn't have to be winner-take-all. Labs, open-source, applications, and the clouds can all capture value. Demand for intelligence is still dramatically underestimated. Today's power users number in the millions and will grow to hundreds of millions. Gavin and David argue a compute shortage is a more real risk than an AI bubble, and building through it is an opportunity to reindustrialize America. In this episode, they get into why compute investments pay back so fast, what the data center backlash gets wrong, the case for putting compute in orbit, why enterprises will run several models at once, and how Nvidia ended up at the center of the entire supply chain. 00:00 Intro 01:06 The bear case Gavin couldn't find 05:50 Why a lab would cut its own revenue 75% 08:05 What LPs get wrong about a crash 10:50 Microsoft slowed its capex and regrets it 14:33 The engineers spending 100x the median 17:35 Why 23-year-olds use AI better than Gavin 21:45 How much copper 500M AI users need 23:00 Stop promising to cure cancer 26:00 America's richest county is full of data centers 30:48 Who gets priced out of compute 33:05 The age of Elon and Jensen 34:25 Orbital data centers 44:40 Asteroid mining 48:12 Why Microsoft doesn't need a frontier model 54:02 Who becomes the abstraction layer 55:40 Everyone wanted a deity, Cursor wanted a product 1:00:25 Never take shots at Jensen 1:07:40 What happens when the chip doesn't work 1:12:10 What chip deals reveal about customer demand YouTube: youtube.com/watch?v=FGC4of…@GavinSBaker@DavidGeorge83 Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬10🔄9❤️127👀34868📊19 ⚡ Powered by xgo.ing