Nathaniel Whittemore
speaker
51,694 appearances
202 recordings
3 series
first heard Oct 2025
last heard yesterday
Nathaniel Whittemore’s voice in public audio — every appearance, attributed to the second.
Trend
recordings per month · last 12 monthsRecordings per month over the last 12 months — 202 in all, peaking in Jun 2026 with 31.
Appearances
Ops agent chases the paperwork and tracks the budget.
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Every agent has access to
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shared context and follows your rules about scope and approvals.
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It's time you add agents that feel like teammates.
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Hire yours at HyperAngent.
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Get $100 in credits at hyperagent.com slash AI Daily Brief.
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Welcome back to the AI Daily Brief.
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On today's main episode, we are looking at something really different and quite rare, which is in short, a totally different approach to AI that is not just another LLM.
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Now, in the nearly four years since ChatGPT was released and the three and a half that this show has been around, the vast majority of the things that we and the rest of the industry have focused on have been in some ways related to large language models.
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And yet, as some have pointed out, although often in a way that didn't get much traction and was more or less screaming into the void, LLMs are not, in fact, the totality of artificial intelligence.
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Yesterday, Diogo Almeida posted on X, After co-inventing ChatGPT, I kept asking myself, why have superhuman chat models not led to AGI?
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I've spent the last two years in stealth building a new way to train models, RLCD, or reinforcement learning for calibrated decisions, and a new type of frontier AI model that we are releasing today.
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Jeff.
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JEV is 20-200 times faster, 40-400 times cheaper, with output tokens free, frontier composable intelligence optimized for decisions.
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As far as I can tell, the shortest path to AI-based economic revolution.
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Now, one could absolutely be forgiven for seeing numbers like 20 to 200 times faster and 40 to 400 times cheaper, and being a bit skeptical of the claims to say the least.
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And were this just another LLM, that skepticism would be entirely warranted.
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However, with Jev and this new strategy, we're dealing with something that is quite different.
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The company behind Jev is called TypeSafe, and in the announcement blog post, they talk a little bit more about what makes their approach different.
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Right, we built a new stack entirely focused on automation, with a new model architecture, parallel sampler for maximum efficiency, and training method we call reinforcement learning for calibrated decisions.
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Showing 2361–2380 of 51,694 · page 119 of 2585
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