This post introduces high-level trends at the intersection of biology and AI, discusses new (and old) technical challenges in building reproducible and scalable systems for AI-driven computational biology, and how frameworks like Metaflow can help address them.
Reactive, configurable, cheaper LLM fine-tuning with Metaflow
Learn how to use Retrieval Augmented Generation to control hallucinations and get more relevant responses from LLMs.
A workflow template built with Metaflow for fine-tuning LLMs for custom use cases.
An overview of instruction tuning for large language models using the LLaMA family of models.
We use Metaflow to train Dolly, to show an example of fine-tuning LLMs and what it takes to use these models in practice.
A peek into how Outerbounds views the ongoing evolution of the machine learning stack, in the wake of recent LLM waves.