FlexiLingo
This is a video recording of a post I wrote last week. If you want to read the original you can check it out here. Thanks to Mercury for sponsoring this video. Mercury’s built-in AI, Command, helps me close my books and saves me a bunch of time. At the end of each month, Command categorizes my transactions and provides its rationale for every choice: I just review, fix anything that’s off, and approve... and then Mercury syncs everything to QuickBooks. Get started at mercury.com/command Get full access to Dwarkesh Podc...
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For the last three consecutive years, Anthropic's revenue has 10x year over year, and it's likely to do so again this year.
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B2 · 中高级
能看懂电视新闻就会觉得轻松
- 74% 的单词在 B1 或更简单的水平。
- 每分钟 203 词：自然语速，偏快。
- 整集共有 90 个较难的单词（B2 及以上）。
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Today, I want to talk about what the compute situation for the labs will look like over the next few years. For the last three consecutive years, Anthropic's revenue has 10x year over year, and it's likely to do so again this year. So they ended last year with $9 billion in revenue. I think they'll probably end this year with somewhere between $100 billion to $150 billion in revenue.
Now, for this trend to continue, Anthropic would need to make $1 trillion in revenue by the end of next year. Of course, there's no deep reason why this has to be true. It's a very wild conclusion, and it's ultimately a question of AI capabilities. Does AI get that useful by the end of next year?
But suppose the trend does continue. Well, I want to think through what happens in that world. Now, the other big trend in AI is that lab compute only three Xs year over year.
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