Yash Rathod

co-founder @origin_bio, prev cs @UofIllinois

[Skyroot Aerospace @SkyrootA]

It’s official. 🚀
July 18. 11:30 AM IST.
Vikram-1. Test Flight-1. Mission Aagaman.

India’s first private orbital launch from the historic First Launch Pad at SDSC-SHAR, Sriharikota.

The countdown begins. 🇮🇳

#Vikram1 #MissionAagaman #SkyrootAerospace #OpeningSpaceForAll

[Intology @intology]

Can coding agents do research?

We release NanoGPT-Bench, an internal eval we’ve used to test agents on an AI R&D problem with months of human progress

Codex, Claude Code, Autoresearch recover only 9.3% of human progress, mostly tuning hyperparams & ignoring algorithmic research

NanoGPT-Bench is built on the NanoGPT Speedrun, a popular LLM pretraining competition to minimize the training time of a GPT-2 style model. Existing human submissions constitute nearly 2 years of work. To control for dependencies and contamination in frontier models, we standardize evaluation to a 5-month window of world records. Evaluation is fully autonomous and end-to-end, with no human intervention or internet access. 🧵

[Yash Rathod @yrraadi]

@ishaans22 very cool!

[ishaan @ishaans22]

I built differentially private fine-tuning for MLX so you can train local models on your private data. The full stack fits in ~600 lines and drops attacker recovery of training data from 90% to 50% 1/6

[owl @owl_posting]

How do you make a 250x better vaccine at 1/10 the cost? Develop it in India.

(Soham Sankaran, Ep #2)

There's a lot of discussion these days on how China's biotech market is on track to bypass the US's. I wondered: shouldn't we have observed the exact same phenomenon with India? It has seemingly all the same ingredients: low cost of labor, smart people, and a massive internal market.

Yet, the Indian biotech research scene is nearly nonexistent. Why is that?

To figure it out, I had a two-hour discussion with @sohamsankaran, the CEO of @PopVaxIndia, an mRNA vaccine development startup based in Hyderabad. Amongst those in the know, @sohamsankaran is well understood as one of the most talented biotech founders in India, and his company has had a genuinely incredible underdog success story. This story is still being written, but there's good reason to be bullish.

We discuss so many things. Including policy prescriptions for Indian R&D, why PopVax's vaccines are so good, how machine-learning is changing vaccine development, and much more. Transcript below, and links in thread (including a jargon explanation).

Timestamps:
01:31 Introduction
02:38 Why is there such little biotech research in India?
17:38 Advantages of building a company in India
26:03 Policy prescriptions for India
30:13 Questions on vaccine design
45:28 What does PopVax do?
56:20 The role of machine learning in vaccine design
01:06:29 The (conservative) culture of vaccinology
01:21:12 Hiring in India
01:40:44 How fundraising for an Indian vaccine design startup is coming along
01:55:15 How is PopVax so good at designing vaccines?
01:59:45 Pet theories on immune mechanisms
02:06:24 mRNA beyond infectious diseases
02:09:56 What would you do with $100 million dollars?

[Yash Rathod @yrraadi]

@sethbannon my favorite book!

[Soham Sankaran @sohamsankaran]

Today, I’m excited to announce that the clinical batch of PVX-001, our open-source broadly-protective COVID-19 vaccine candidate built on our own RNA platform, has been manufactured at our RNA Foundry in Hyderabad, and it will enter clinical trials in Australia in a few months.

[Runtime @RuntimeBRT]

🚨 Bengaluru-based @Airbound_Aero has conducted 700 flights for Narayana Health since January 2026 with a zero failure rate.

[Yash Rathod @yrraadi]

@malhar317 @viraj9451 @Akshxat @AdiyaSivahuma is the awesome team behind the work we’re putting out - from model training, experiments, systems (training / inference), data and lab work!

lot more to come!

[Yash Rathod @yrraadi]

Today, we're excited to release 10,000 fully AI-designed enhancer sequences for the research community. Axis was prompted to design sequences with targeted activity in one of three widely used cell-lines.

AI allows us to explore a vast design space, going beyond the natural genome.

[Yash Rathod @yrraadi]

@MrHonkster We used Malinois as an independent predictor of MPRA activity. We’ll keep sharing results as we complete lab work!

[Yash Rathod @yrraadi]

@garrytan Thanks Garry!

[Garry Tan @garrytan]

AI x Bio teams like Origin have coding agents, scaling laws, and a wave of big biotech deals all at their backs. This is barely touched territory. Crazy what this small team can do now.

[Dr. Muk🇿🇼 @steamulater]

Bookmarked

[Jeff Lewis @jefflewis]

Acceleration- this is the future we were promised

[Yash Rathod @yrraadi]

Today, we're excited to release 10,000 fully AI-designed enhancer sequences for the research community. Axis was prompted to design sequences with targeted activity in one of three widely used cell-lines.

AI allows us to explore a vast design space, going beyond the natural genome.

[Yash Rathod @yrraadi]

Why are we generating and testing these libraries at scale? Learn more: https://t.co/v28S0bCkwe

View the sequences at - https://t.co/lic8KWiqlJ

[Yash Rathod @yrraadi]

Today, we're excited to release 10,000 fully AI-designed enhancer sequences for the research community. Axis was prompted to design sequences with targeted activity in one of three widely used cell-lines.

AI allows us to explore a vast design space, going beyond the natural genome.

[Yash Rathod @yrraadi]

We're beginning to run functional assays - MPRAs, ATAC-seq and ChIP-seq - on over 50,000 Axis designed regulatory elements. But we're opening them up early for the research community to use in its own experiments.

We'll contribute these results to the platform and soon release additional sequences for primary cells and tissues.

[Yash Rathod @yrraadi]

@david_van_dijk huge congrats!