AI Research | Uncertainty, Reliability & Evals | PhD (Yale)
New York
Joined April 2026
- Tweets28
- Following119
- Followers42
- Likes43
Tal Zeevi retweeted
Round two next week... more intimate and casual this time :) Talks, food and drinks
dm me or @NeuroLuebbert if you are interested in coming!
Best dinner with some of the GREATS across AI x life science here in NYC
While Alfredo may object, NY (plus Boston + London) is cooking👨🍳
SVPs who've run drug development at big pharma, ML researchers, founders building vertically integrated manufacturing infra - all at one table
In typical fashion, we went around the table for intros - everyone shared their name and their Roman Empire (h/t Collin) / latest obsession
A real privilege to host and get these minds in one room! More NY events to come (runs, science talks, poker nights, and dinners)🥳stay tuned
@MattStergiou @tzeevis @mingyu_ma @constable_todd @mpcadosch @gruver_nate @MichaelRetchin @patrickmineault @Collin_Spencer_ @max_strome @marcosrortiz4 @Killianhmmm @ZahraKhwaja
Tal Zeevi retweeted
more fearless female leaders going all in on Bio!! the most important frontier
While AI gives me a lot of hope to find cures for complex chronic conditions like mine, this potential will only be realized if we get enough biological data to understand the mechanisms of these conditions. That’s what we’re trying to do at @ChronicleBioAI:
fortune.com/2026/08/03/fidji…
Tal Zeevi retweeted
@JMRothberg (whose team sequenced the first individual human genome) once spoke to my Yale BME class. I nearly joined the many friends he recruited across New Haven
What he built at @4Catalyzer feels like a modern Bell Labs for biotech: bring exceptional scientists and engineers together, give them funding to attack impossibly ambitious problems, and turn the results into companies
That model produced @ButterflyNetInc (ultrasound-on-a-chip), @Hyperfine (portable MRI), IsoPlexis (single-cell proteomics), Detect (at-home molecular diagnostics), Quantum-Si (next-generation protein sequencing), and more
But the most impressive output may be the people who left to build again:
Eric Kauderer-Abrams → Head of @AnthropicAI Life Sciences
@dalvabaird → CEO Crownlands (human neuroscience neolab)
Matt de Jonge → CEO Fortell (AI hearing aids)
Gregory Charvat → CEO TeraDAR (advanced sensing)
Jonathan Naccache → CEO Brink Therapeutics (programmable gene integration)
Gino Korolev →CEO Fertu (digital-health engagement)
@nicodjimenez → founder Mathpix (AI document conversion)
@marcosrortiz4 → Cofounder stealth (AI x bio)
Kam Firouzi → CEO Althea Health (AI voice agents for healthcare)
@ayodaiken → CTO Stealth AI native financial services
Michael Bellos + Faisal Razi Ahmad→ cofounders Arcsecond Labs (optical engineering)
and the flywheel is still spinning: Butterfly’s ultrasound chips power @midjourney Medical’s full-body scanner
The best founders don’t just create companies. They create ecosystems that produce the next generation of founders
(and, remarkably, most of this group is barely on Twitter and maintains a low profile. they’ve been too busy building.... maybe that says everything)
Tal Zeevi retweeted
No one has cracked the nut on how to properly run evals on agents, the lack of standardization and transparency combined with the extreme variance, arguably infinite number of variables, and cost makes this a difficult problem. Evaluations have major economic, scientific and political implications, and right now it’s a complete shit show
GPT-5.6 Sol has been used to solve open problems in mathematics. So why was it struggling with ARC-AGI-3, a benchmark of 2D puzzle games?
We investigated. The harness was not letting it remember what it had learned.
We found that enabling two API settings tripled our scores with 6x fewer output tokens.
Tal Zeevi retweeted
We Built the Agents Faster Than We Built the Rulers
I spent a decade doing research in theoretical astrophysics and cosmology. Compared to that field, AI benchmarks have been more vibes than science...(rant incoming)
Tal Zeevi retweeted
Best dinner with some of the GREATS across AI x life science here in NYC
While Alfredo may object, NY (plus Boston + London) is cooking👨🍳
SVPs who've run drug development at big pharma, ML researchers, founders building vertically integrated manufacturing infra - all at one table
In typical fashion, we went around the table for intros - everyone shared their name and their Roman Empire (h/t Collin) / latest obsession
A real privilege to host and get these minds in one room! More NY events to come (runs, science talks, poker nights, and dinners)🥳stay tuned
@MattStergiou @tzeevis @mingyu_ma @constable_todd @mpcadosch @gruver_nate @MichaelRetchin @patrickmineault @Collin_Spencer_ @max_strome @marcosrortiz4 @Killianhmmm @ZahraKhwaja
A single run is often a poor estimate of a long-horizon agentic pipeline’s typical behavior. Small perturbations can compound into very different outcomes, but running enough trials to characterize the outcome distribution is expensive. We need sample-efficient evaluation methods with finite-sample guarantees on estimation error.
7/ Modern AI benchmarks often score the final answer. Whetstone reminds us to also inspect the path. Only then can we tell whether we measured the capability we cared about, or an unintended shortcut through the evaluation.
8/ Source: Curnow & Wichmann, 'A Synthetic Benchmark,' Computer Journal, 1976 academic.oup.com/comjnl/arti…
