RJ Honicky

BioTech - AI - Host of Latent Space AI for Science podcast

[RJ Honicky @honicky]

Noetik’s AI value proposition: “cohort selection”

“When I do my drug’s clinical trials, who should participate?”

Obviously, if you get that wrong, then your drug won’t “work,” even if it actually works!

Ron Alfa explained to us how they do this using cheap imaging

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[RJ Honicky @honicky]

So much exciting news coming out of Axiom! So glad we got to sit down with you! @axiommathai @CarinaLHong

[Latent.Space @latentspacepod]

🆕Scaling Past Informal AI
https://t.co/eZz4ziS9yh

@axiommathai founder & CEO @CarinaLHong explains why math may be the missing path from code agents to AGI, why verified AI is about scaling brilliance not just fixing hallucinations, how Lean and formal proofs turn reasoning into a stronger reward signal, why Axiom sees the TAM as all AI-generated code, what it means to prove research conjectures in a self-verified way, and why the next bottleneck for AI may be not generation but verification.

[RJ Honicky @honicky]

@alexrives @THayes427 @proteinrosh @biohub @latentspacepod

[RJ Honicky @honicky]

ESMC/ESMFold2 authors to present at Latent Space Paper Club tomorrow!

Links in the comments. @alexrives @THayes427 @proteinrosh @biohub

[RJ Honicky @honicky]

event: https://t.co/sCsHgBeCfw
paper: https://t.co/NmR2M4um99

[RJ Honicky @honicky]

I love it when a plan comes together! Congrats Ron, this is a huge milestone.

[Ron Alfa @Ronalfa]

This weekend at ASCO, we shared first results using @NOETIK_ai TARIO-2 foundation models to predict patients likely to benefit using pre-treatment H&E alone (from actual clinical trial data with @Agenus_Bio!).

Some highlights below!

[RJ Honicky @honicky]

@andremillet @biohub I guess I left out genes: maybe like low level functions, or even single instructures.

I explained my thinking a bit more here:

https://t.co/7dnGJNaFLU

[RJ Honicky @honicky]

"genes are code" is always vague

I like:
cell nucleus → storage device / storage controller
ribosome → JIT-compiler and runtime
features from a world model (use a SAE) → functions
Proteins → processes
signaling pathways → workflows
Phenotypes → behaviors / outputs
@biohub

[RJ Honicky @honicky]

The ESMC/ESMFold2 release also includes ESM Atlas, which makes me very happy :). @biohub team delivers the data!

[Latent.Space @latentspacepod]

🆕Biohub’s Protein World Model: ESMC-6B, ESMFold2, 6.8B proteins, 1.1B structures, antibody design, SAEs, & the bitter lesson for biology https://t.co/2BkTzLGqvW

@biohub Head of Science @alexrives explains why biology may scale like language modeling, how metagenomics unlocked the next ESM scaling curve, why protein LMs can learn structure/function from sequence alone, how sparse autoencoders reveal biology inside the model, why ESMFold2 can beat specialized systems on antibody-antigen prediction, and how Biohub’s $500M Virtual Biology Initiative aims to build predictive models of cells, disease, and eventually physiology.

[RJ Honicky @honicky]

@KexinHuang5 Fantastic!

[RJ Honicky @honicky]

@alexrives Alex, loved sitting down together, and look forward to what you all have in store for us next!

[RJ Honicky @honicky]

@proteinrosh The paper is a tour-de-force! Well done to you and the whole team!

[RJ Honicky @honicky]

Love this summary of the paper. The paper is definitely worth the read!

[Zeming Lin @ebetica]

I'm so excited to show the world what we've been working on the for the past months!! I'm going to highlight some of the fun results from this paper that I find particularly exciting.

[RJ Honicky @honicky]

@alexrives What a huge contribution to science!

[RJ Honicky @honicky]

@latentspacepod @biohub @alexrives Really enjoyed the paper, and really enjoyed sitting down with @alexrives !

[RJ Honicky @honicky]

@andrewwhite01 Yeah, paper's really good. Hopefully good guidance for fast iteration with automated labs! Keep it coming sir!

[RJ Honicky @honicky]

@Ronalfa Right place, right time :)

[RJ Honicky @honicky]

@SGRodriques Fantastic news sir

[RJ Honicky @honicky]

@ALupsasca @latentspacepod Really enjoyed having you on, sir!

[Latent.Space @latentspacepod]

🔬Doing Vibe Physics

The full story of how GPT‑5.x derived new results in theoretical physics and quantum gravity, live on our Science pod today!

https://t.co/WHnPyH7K7K

our conversation with @ALupsasca, an award winning theoretical physicist on his AGI-pilling journey applying GPT5 to physics problems (with a nudge from @markchen90)!

Timestamps
0:00 Introduction to Al's impact on physics research
0:43 Guest introduction: Alex Luposka
2:49 Alex joining OpenAl and the shift in physics research
4:08 The release of GPT-5 and the shift in capabilities
10:05 Explaining Quantum Field Theory and amplitude calculations
14:20 Overview of gluons and the strong force
14:38 Discussing the first research paper on single-minus gluon tree amplitudes
20:56 How ChatGPT helped solve a year-long physics puzzle
23:02 Complexity of manual calculations in physics
26:12 The history and mechanics of Feynman diagrams
27:44 The Parke-Taylor formula and the quest for simplification
31:26 Using ChatGPT to find the simplification in the special phase space region
38:07 Proving the formula from scratch to ensure validity
41:00 Determining the scientific impact and future research
42:27 Introduction to the second paper on graviton amplitudes
45:41 |
Defining particles, irreducible representations, and symmetry
47:46 How GPT Pro generalized the research to gravity
53:57 The epistemological shift: Is this a new way of doing physics?
59:27 The use of Al as a 'scout' for research directions
1:01:44 The role of 'taste' and collaboration with Al
1:10:23 Personal evolution from Al skeptic to resident scientist
1:12:46 Solving a black hole perturbation problem with GPT-5
1:16:34 Discussing whether Al can make original, conceptual leaps
1:20:09 Challenges of 'Al slop' and the future of academic publishing
1:23:13 The bottleneck of writing academic papers
1:30:19 Final takeaways and looking ahead to the next year

[RJ Honicky @honicky]

SubStack: https://t.co/ahxGfh4aou
YouTube: https://t.co/sPt5gtjglq
Spotify: https://t.co/wfvphMDWpC
Apple: https://t.co/D15DGywOKE

[RJ Honicky @honicky]

Noetik’s AI value proposition: “cohort selection”

“When I do my drug’s clinical trials, who should participate?”

Obviously, if you get that wrong, then your drug won’t “work,” even if it actually works!

Ron Alfa explained to us how they do this using cheap imaging

1/