I've been wanting to learn more about and build in the AI + Biology space, so I took the leap by using @huggingface new Carbon genomic foundation model and Meta's ESMFold model to build a pipeline that takes the same gene across six species and compares in various ways.
It's cool to see that DNA can change over hundreds of millions of years while the resulting protein structure stays very similar.
This was a fun project and I learned some important bioinformatic fundamentals like alignment a long the way!
Any suggestions on biology use cases or research I should checkout while I continue down this path?
@JoeVeyera Nice! I still haven't been to the newer one downtown on 3rd(?), but I hope the expansion is going well for them! Might have to get a sandwich from them tomorrow now ๐
The weekly AI build and learn streams were so much fun. I'll be getting them going again.
What topics should be next? What have you been wanting to spend some time learning about?
This Weeks AI build and learn is trying out @NVIDIAAI Isaac sim. I'm running it on a DGX spark.
It's going to be a tough week to fit in a lot of testing but we'll come back this when we're exploring world & cosmos models over the next few weeks!
The weekly AI build and learn streams were so much fun. I'll be getting them going again.
What topics should be next? What have you been wanting to spend some time learning about?
Today marks 3 years at @union_ai for me!
I get to work with some of the best people across so many different AI application domains, it's been a blast!
AI teams are starting to look beyond renting every capability from an external API, they're building systems they own and control. Join me for a hands-on session where we'll build exactly that by creating an ML Engineer Agent that will manage a model factory to select and fine-tune the best models for your applications.
We'll cover
- Model Factories
- ML Engineering Agents
- Data drift on models in production
- Using @union_ai or Flyte (OSS) as the AI runtime managing everything from compute resources, experiment management, human in the loop, and context
Excited to be part of the @FireworksAI_HQ Frontier Ecosystem ๐
Run Fireworks models from Union and your pipeline fans the calls out in parallel, retries when an on-demand deployment is still waking up, and caches results so you don't pay twice for the same call. Route through our LLM Gateway to add budgets, fallbacks and guardrails.
Pair it with Fireworks Sovereign and all of it stays in your own cloud ๐