You’ve no doubt heard about the major AI story dominating global news coverage this week — DeepSeek R1.
From all accounts, it seems there’s a new Chinese AI model built for a total cost of $16.95 that’s as good as OpenAI’s trillion-dollar models even though it was put together by teenagers who tied six Intel Pentium processors together, powered them with a potato battery, and told it to refuse to answer questions about Tiananmen Square.
As a result of this tall tale — which relates to a genuinely impressive achievement despite the exaggerations — investors rushed to sell overvalued US AI stocks along with every token in my entire portfolio of unrelated cryptocurrencies.
You’ve probably read a million articles about it already, so here’s a collection of the more interesting tidbits about DeepSeek we’ve come across:
1. DeepSeek’s costs are misunderstood
Whatever DeepSeek cost, it’s widely agreed it was a lot more than the $5.6 million training cost for v3 that the media keeps highlighting. (R1 refers to the reasoning version that was built atop v3).
$10M AI startups (Arnaud Bertrand)
It also emerged in recent days that training costs for US AI companies are considerably less than previously believed. Anthropic’s CEO Dario Amodei said in a blog post: “DeepSeek does not ‘do for $6M what cost US AI companies billions.’ I can only speak for Anthropic but Claude 3.5 Sonnet is a midsized model that cost a few $10Ms to train.”
He says the real news story should be that “DeepSeek produced a model close to the performance of US models 7-10 months older, for a good deal less cost (but not anywhere near the ratios suggested).”
There is confirmation however that DeepSeek likely spent almost nothing on cybersecurity, given security researchers from Wiz found more than 1 million of its records, including user data, prompt submissions and API keys, in an open database on the web.
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