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Eric Zelikman

CEO & Co-founder, humans& · 1 appearance on the record.

computed by AI from the episodes · how this works → · full disclaimer →

founderscientistexecutive@ericzelikman ↗zelikman.me ↗

Eric Zelikman is the co-founder and CEO of humans&, an AI startup focused on human-centric models with long-term memory and emotional intelligence. Previously an early technical staff member at xAI and a Stanford Ph.D. researcher, he is known for pioneering language model self-taught reasoning methods including STaR and Quiet-STaR.

7statements → 2claims → 2claims resolved → 3.71/5average certainty → 2/5average debate potential → ≈4.0/5argument clarity, estimated →

2 supported 0 partly supported 0 contradicted how the 2 claims stand · each chip opens the sources

2 assertions · 2 opinions · 3 insights · every statement was checked. The predictions and assertions are the 2 claims: statements the public record can support or contradict. 2 are resolved. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Eric argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

Their most notable supported claim

Assertion Supported
Zelikman: Frontier AI models solve questions that stump actual PhD researchers
“Some of the HLE questions that these models are able to solve are genuinely things that are, like, non-trivial for, like, actual, like, PhD researchers.”
Eric Zelikman Oct 9, 2025 ▶ 8:53 No Priors Ep. 135 | With Humans& Founder Eric Zelikman

How they sound: not measured why? →

We measure speaking style by listening to the audio itself, and a fair number needs at least 2,000 words from one person on tape we have measured. There is too little of Eric Zelikman on measured tape to publish a rate. This says nothing about how they speak.

Everything Eric Zelikman said on No Priors that made the record, most notable first. Filter by type, assessment or year in the ledger →

Opinion
Zelikman: Most AI labs treat humans as mere intermediates to full automation
“And maybe this is a strong statement, but I say for most labs, like the human is kind of, you know, the intermediate until you have like this fully automated, like, you know, system. And so spending a lot of time optimizing things for being really good at unde…”
Eric Zelikman Oct 9, 2025 ▶ 29:26 No Priors Ep. 135 | With Humans& Founder Eric Zelikman
Insight
Zelikman: AI field underinvests in memory due to task-centric training regimes
“I would say that memory is definitely like a feature that has been under, under-invested in by the field. But I would say that it is kind of difficult to invest in memory in this very, like, task-centric regime. Because if you have, like, A bunch of these, lik…”
Eric Zelikman Oct 9, 2025 ▶ 32:13 No Priors Ep. 135 | With Humans& Founder Eric Zelikman
Insight
Zelikman: Training reasoning models on just positive examples causes a plateau
“So if you only train on like the positive examples, then you end up in this kind of like potential minimum where there's just no more data that it can actually solve.”
Eric Zelikman Oct 9, 2025 ▶ 5:44 No Priors Ep. 135 | With Humans& Founder Eric Zelikman
Assertion Supported
Zelikman: Frontier AI models solve questions that stump actual PhD researchers
“Some of the HLE questions that these models are able to solve are genuinely things that are, like, non-trivial for, like, actual, like, PhD researchers.”
Eric Zelikman Oct 9, 2025 ▶ 8:53 No Priors Ep. 135 | With Humans& Founder Eric Zelikman
Opinion
Zelikman: Current frontier AI models fundamentally lack emotional intelligence
“One of the core things is that they're not smart Like, emotionally, or, like, they're not smart on the level of, like, actually understanding kind of what people care about, or kind of, like, how to actually, like, help people accomplish the things that they c…”
Eric Zelikman Oct 9, 2025 ▶ 10:04 No Priors Ep. 135 | With Humans& Founder Eric Zelikman
Insight
Zelikman: AI performance gap persists between verifiable and non-verifiable tasks
“There's still a gap between how well these models perform on verifiable tasks versus not verifiable tasks.”
Eric Zelikman Oct 9, 2025 ▶ 14:40 No Priors Ep. 135 | With Humans& Founder Eric Zelikman
Assertion Supported
Zelikman: Language models can be trained to simulate students for test design
“Like, even back in my PhD, I think one of my, I guess, less well-known works was actually about, we showed that you can train language models to simulate different kinds of students. For tests. Yeah, yeah. And by simulating students, you can actually design be…”
Eric Zelikman Oct 9, 2025 ▶ 22:54 No Priors Ep. 135 | With Humans& Founder Eric Zelikman

Appearances (1)

EpisodeDateSpeaking time
No Priors Ep. 135 | With Humans& Founder Eric Zelikman Oct 9, 2025 25m
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