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Everyday questions can be answered by any AI model. The complex, token-heavy work is where the competition lives. Tasha Keeney discusses with Brett Winton how much knowledge work is actually up for grabs to cheaper Chinese or open-source models on "The Brainstorm."

23,628 views • 1 month ago •via X (Twitter)

7 Comments

Jordan Blake's profile picture
Jordan Blake1 month ago

@TashaARK @wintonARK Complex token-heavy knowledge work is the real battlefield. Open-source + Chinese model data is closing the gap fast.

Pickled Tink's profile picture
Pickled Tink1 month ago

@TashaARK @wintonARK I asked grok a question yesterday. The answer wasn't what I was hearing from an employee. I verified before I accused the employee of anything. Grok was wrong. Beware. Grok gets information from online sources. GIGO.

MONEY MATRIX USA 💰's profile picture
MONEY MATRIX USA 💰1 month ago

@TashaARK @wintonARK Energy is the real bottleneck here. AI and robotics can scale fast, but without a massive jump in cheap, reliable power the $100T opportunity stays theoretical. Curious how ARK models the energy constraint in the report.

Tony Floatana's profile picture
Tony Floatana1 month ago

@TashaARK @wintonARK Commodity AI is 10,000 tickers fighting for the same bid. Token-heavy work is a two-name float, chico. Open source owns the volume. Frontier owns the supply. That spread already told you the trade.

Ansem 🐂🀄️'s profile picture
Ansem 🐂🀄️1 month ago

@TashaARK @wintonARK Sounds like a fascinating convo! Can't wait to hear their insights on the future of AI in knowledge work.

punkbrwstr's profile picture
punkbrwstr1 month ago

@TashaARK @wintonARK ...or the guy whose costs are 10x higher is dead?

MONEY MATRIX USA 💰's profile picture
MONEY MATRIX USA 💰1 month ago

@TashaARK @wintonARK Energy is the real bottleneck here. AI and robotics can scale fast, but without a massive jump in cheap, reliable power the $100T opportunity stays theoretical. Curious how ARK models the energy constraint in the report.

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OpenAI chairman Bret Taylor talks to about 100 CEOs every month. His answer to the cheap open-weight model panic: cheaper to train does not mean cheaper to use, and the number that decides it is token efficiency. "One thing that I think is a little bit overblown about these open weight models is they're not necessarily cheaper to run. Whether or not they're cheaper to train, you don't care. Because you're using just as many tokens. In fact, they may be less efficient." "There's this thing called token efficiency. And it turns out the frontier models are much, much more token efficient." "A token is to intelligence like a watt is to electricity... how many tokens does it take to complete a task? Not every token is actually equal." "For a lot of tasks, it turns out these frontier models from OpenAI and Anthropic are actually just better than these open weight models... just having open weights isn't actually the main thing driving any of those costs." Later in the same interview he goes after the billing unit itself: "It would be like if you signed up for Gmail and you paid for CPU cycle or something... where the world is going is paying for outcomes." The unresolved column: the chart CNBC airs mid-answer, from Artificial Analysis, prices a completed task at $0.94 on Kimi K3 against $2.75 on Claude Fable 5, efficiency folded in. If that gap holds, the premium he is defending gets earned on quality, not price. - Bret Taylor (Bret Taylor), OpenAI chairman and Sierra co-founder, on CNBC's Squawk Box.

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17,254 views • 1 month ago