Akshat Singh

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Akshat Singh

Akshat Singh

@Akshxat

Founding @Origin_bio Prev @nvidia, @rivian

San Francisco, CA Katılım Haziran 2022
622 Takip Edilen109 Takipçiler
Akshat Singh
Akshat Singh@Akshxat·
Even minimal comp arch knowledge goes a long way!
Dwarkesh Patel@dwarkesh_sp

New blackboard lecture w @reinerpope How do chips actually work – starting with basic logic gates, and working up to why GPUs, TPUs, FPGAs, and the human brain each look the way they do. 0:00:00 – Building a multiply-accumulate from logic gates 0:16:20 – Muxes and the cost of data movement 0:25:59 – How systolic arrays work 0:39:00 – Clock cycles and pipeline registers 0:51:40 – FPGAs vs ASICs 1:03:14 – Cache vs scratchpad 1:07:16 – Why CPU cores are much bigger than GPU cores 1:11:49 – Brains vs chips 1:15:22 – A GPU is just a bunch of tiny TPUs Look up Dwarkesh Podcast on YouTube/Spotify/etc to watch. Enjoy!

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Han Guo
Han Guo@HanGuo97·
LLM training is built on fast MatMuls. But many surrounding ops still run as memory-bound kernels. CODA reparameterizes them to hide in the matmul’s shadow, fused into its epilogue before results leave the chip. Bonus: LLMs can write fast CODA kernels too (approaching SoLs).
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ishaan
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
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Scott Wu
Scott Wu@ScottWu46·
Craziest part is we all knew each other already in high school! Along with @randomjohnnyh (Perplexity cofounder), @demi_guo_ (Pika CEO), @stevenkplus1 and Andrew (Cognition), and many others. We all grew up in different states but met thru the olympiad scene. Vividly remember this line from @alexandr_wang when we were around 19: "I hear people saying they want to find the next Paypal mafia. Why shouldn't it just be us?" Glad to see @chameleon_jeff get the recognition he deserves :)
Tanay Jaipuria@tanayj

HRT’s first ever intern class of 10 included: • Jesse Zhang, cofounder/CEO of Decagon • Alexandr Wang, cofounder/CEO of Scale AI • Scott Wu, cofounder/CEO of Cognition • Jeffrey Yan, founder/CEO of Hyperliquid Insane!⁠

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Cory Levy
Cory Levy@cory·
UT or UIUC?
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ani
ani@anirudhbv_ce·
I implemented @GoogleResearch's TurboQuant as a CUDA-native compression engine on Blackwell B200. 5x KV cache compression on Qwen 2.5-1.5B, near-loseless attention scores, generating live from compressed memory. 5 custom cuTile CUDA kernels ft: - fused attention (with QJL corrections) - online softmax -on-chip cache decompression - pipelined TMA loads Try it out: devtechjr.github.io/turboquant_cut… s/o @blelbach and the cuTile team at @nvidia for lending me Blackwell GPU access :) cc @sundeep @GavinSherry
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chuyi shang
chuyi shang@chuyishang·
Wrote a deep dive on implementing a language model from scratch in JAX and scaling it with distributed training! If you’re coming from PyTorch and want to see how the same ideas look in JAX, or just want a hands-on intro to distributed training, check out this blog post: chuyishang.com/blog/2026/jax-… Comes with code + an assignment and test cases so you can follow along!
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Garry Tan
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.
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.

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Yash Rathod
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.
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Anne Ouyang
Anne Ouyang@anneouyang·
Excited to share @Standard_Kernel's seed round and some reflections on what we’ve learned about kernel generation and what we believe is next. Grateful to our amazing team, supporters, and the broader community pushing this space forward.
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Brian Armstrong
Brian Armstrong@brian_armstrong·
One of my favorite lessons I’ve learnt from working with smart people: Action produces information. If you’re unsure of what to do, just do anything, even if it’s the wrong thing. This will give you information about what you should actually be doing. Sounds simple on the surface - the hard part is making it part of your every day working process.
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Origin
Origin@origin_bio·
Interested in knowing more about how we beat Google DeepMind? We shared some insights on @tbpn
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Origin
Origin@origin_bio·
On TBPN live, our co-founder and CEO shares more on how we plan to use Axis to develop new age gene therapies👇
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Yash Rathod
Yash Rathod@yrraadi·
Going on TBPN at 1:45 pm PT to launch @origin_bio and our model, Axis. Axis is the first model that generates regulatory DNA sequences and predicts its function. Axis already outperforms DeepMind's AlphaGenome on various benchmarks!
TBPN@tbpn

Morning. On today’s show: – @karimatiyeh (Ramp) – @alexkshieh (The Antifraud Co) – @dteare (1Password) – @gilbert & @djrosent (Acquired) – @sergiynest (Quilter) – @jlopas (Base Power Co) – @ryanjdaniels (Crosby) – @zganieany (MeritFirst) – @yashrathod_75 (Origin) See you there.

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Akshat Singh
Akshat Singh@Akshxat·
From bits to biology. It's been an incredible journey working on the core compute infra for a new AI model. We spent countless hours maximizing GPU utilization with custom kernels, turning raw hardware power into a tool that understands DNA. 💻 -> 🧬 Today, we are thrilled to announce Axis. It’s the first AI model to unify generative design with predictive validation for regulatory DNA. In short, it can both design novel DNA sequences and predict their functional properties. The result? Axis already outperforms Google DeepMind’s AlphaGenome on benchmarks. This is a huge first step towards building unified AI models for Biology, and I'm so proud of what our team at Origin has built. Learn more on our blog: origin.bio/introducing-ax… Sign up for early access: tinyurl.com/origin-axis-ac…
Origin@origin_bio

Introducing Axis: the first AI model that generates regulatory DNA elements and predicts their function. Gene therapies suffer from poor efficacy, toxicity & specificity. Models like Axis can help overcome such risks. Axis beats Google DeepMind's AlphaGenome at predicting regulatory element binding activity by 6.7%.

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Keşfet

@ishaans22 @randomjohnnyh @demi_guo_ @stevenkplus1 @alexandr_wang @chameleon_jeff @cory @anirudhbv_ce