🔬Beyond AlphaFold: How Boltz is Open-Sourcing the Future of Drug Discovery Inside Boltz, AlphaFold’s Legacy, and the Tools Powering Next-Gen Molecular Discovery

Quick blog post with links: latent.space/p/boltz

Or wherever you listen to podcasts!

DeepMind closed AlphaFold, so
@gcorso.bsky.social + Jeremy Wohlwend
built Boltz. Now its the preferred solution for many scientists.

They have succeeded with open weights because they focused on community. Now they're launching a new PBC.

What do you use Boltz for?

Links 👇

Introducing the AnnData DuckDB extension At MiraOmics we look at a lot of H5AD files. We have a database of over a thousand of them, not to mention several of the public data sources. Pretty much every time I have a new file, the first thin...

Just do:

INSTALL anndata FROM community; -- first time only
ATTACH "anndata:your_file.h5ad" AS ad;
SELECT * from ad.obs;

Blog post: learning-exhaust.hashnode.dev/introducing-...
GitHub: github.com/honicky/annd...

Tired of creating a new notebook and writing AnnData/pandas/numpy/??? just to peek at a H5AD file?

Me too! So I created a DuckDB extension that can read AnnData files.

Spending cuts + tax cuts = more debt

@scverse.bsky.social

GitHub - honicky/anndata-metadata: A Python library and CLI tool for extracting metadata from AnnData .h5ad files, both locally and on S3 A Python library and CLI tool for extracting metadata from AnnData .h5ad files, both locally and on S3 - honicky/anndata-metadata

Working with a large set of AnnData files on S3 is tough if you don't have the metadata indexed, so I created a tool to help.

github.com/honicky/annd...

It uses partial downloads to dramatically speed up extracting the metadata without downloading the whole file.

`pip install anndata-metadata`

Gene Embeddings, LLMs, and a $6.83 Experiment That Might Matter Better Gene Embeddings Through Prompt Engineering (Or, at Least, We Tried)

I promised to explain how you can build your very own, custom GenePT embeddings. Here's another Lab Note:

learning-exhaust.hashnode.dev/lab-notes-cu...

Enjoy!

GenePT vs scGPT - what I learned in a few days In the spirit of “Learning in Public,” and “learning exhaust,” I’m going to start adding “Lab Notes” blog posts that chronicle little discoveries or failures that I have along the way to a larger goal...

Bio data is amazing!!! Don't be intimidated!

learning-exhaust.hashnode.dev/lab-notes-co...

@eugeneyan.com @swyx.io @latentspacepod.bsky.social

Data Products are Different Why you have to manage data products differently than software and hardware.

Data products often scale cost like hardware, iterate like software, and scale performance like... data products.

learning-exhaust.hashnode.dev/data-product...

Weight streaming might work well on GPUs! I wonder why it isn't a thing...

Oh man, writing up the Cerebras paper on Weight Streaming was a rabbit hole filled with parallel algorithms.

learning-exhaust.hashnode.dev/one-thing-i-...

@picocreator.bsky.social @eugeneyan.com @swyx.io @latentspacepod.bsky.social

Embeddings are task specific Modern training techniques for embedding models mean that we should probably include a prompt or fine tune to a specific type of task.

First post to bsky:

I've been trying to post a bit more frequently and in smaller bites, so I'm going to try to pick one interesting thing I've learned from papers I read, and then write a quick post about them.

Here's my first one:

learning-exhaust.hashnode.dev/one-thing-i-...