Want to use Gaussian processes for your problem but sometimes find it too costly to afford? Our #NeurIPS2020 paper introduces an amortized inference method as a lightweight alternative to the conventional MLL-opt for training GPs. w/ Xingyuan Sun, Peter Ramadge, Ryan Adams

We are hiring PhD interns for my team at Google Research: research.google/teams/applied-… We use computational methods (especially ML) to advance research in a variety of scientific fields. For full consideration, please apply by January 15: careers.google.com/jobs/results/1…

Why are random walks recurrent in 1 & 2D, but transient in 3D? Let's try to get some intuition for this 1921 result by mathematician George Pólya. Video: youtu.be/byvEzyFgv44

Unlike GPT-3 or PaLM, ChatGPT is not just a raw language model trained with maximum likelihood. It's fine-tuned with a combination of additional supervised and reinforcement learning signals based on human preferences. Video covering the training recipe: youtu.be/VPRSBzXzavo

Super excited to introduce Neuromechanical Autoencoders! We build "artificial mechanical intelligence" by coupling parametric neural networks with parametric mechanical metamaterials, accepted to ICLR 2023 as a Spotlight! arxiv.org/abs/2302.00032

Wrote a blogpost on selling AI products + services to big pharma! Check it out below!

I'm incredibly excited to announce our new company, DatologyAI! Training models is hard and identifying the right data is the most important and difficult part -- our goal DatologyAI to make optimizing training data at scale easy and automatic across modalities.

20 trillion dollars to axi.om

Announcing Axiom: Eliminating drug toxicity, without using animals! Alex Beatson and I founded Axiom a little over over a year ago with the mission of eliminating drug toxicity by replacing traditional experiments, such as animal testing, with AI models. We are excited to

Axiom is one of the few techbio startups that I'm bullish on. They're focused on a simple problem (liver toxicity prediction) for which ML is a likely value-add, as opposed to chasing a vague, sprawling, unfocused scaling story. So refreshing!

Humanity discovers new drugs painfully slowly. Why? Most clinical trials fail due to (1) drug toxicity or due to (2) selecting the wrong protein target. The bottleneck isn't protein structure prediction, or binding prediction, or molecule generation. It's toxicity and target

Exclusive: Amplify Partners has raised $200 million for its first biotech-specific fund Targeting ~20 investments of $1.5m-$10m in pre-seed/seed/Series A-stage startups. The Silicon Valley VC has also hired Elliot Hershberg as a partner: endpoints.news/amplify-raises…

To replace animal testing with AI, we need MASSIVE human datasets. Today, we're thrilled to share Axiom's new data exploration tool, providing the ability to visually explore the world's largest primary human liver toxicity dataset. Built with Axiom's proprietary wetlab

everybody wants to do fun experiments nobody wants to write core infrastructure code

nobody wants to look at the data, either

btw by far the most interesting new pattern we are seeing in Latent.Space (upcoming with @olivierddr and Saoud Rizwan and pash) is that people are using Claude Code Community and @Cline for non-coding tasks and this is becoming surprisingly effective for things like sales/BI

The new "100 chrome tabs" is 15 open cursor windows each with multiple terminals running claude code