August ML & GenAI Announcements

Get up to speed with the latest GenAI and ML Databricks announcements for August 2024! In this video, we discuss:

Main Announcements:
Lakehouse Monitoring in GA (00:14): Lakehouse Monitoring allows you to easily profile, diagnose, and enforce quality, with automated profiling for any Delta Table in Unity Catalog out-of-the-box.

Fine-Grained Access Control on Single-User Clusters (01:00): Fine-grained access control is available on single-user compute (public preview): you can take advantage of Unity Catalog's fine-grained access control features (views, row filters, column masks) as well as materialized views and streaming tables when using single user clusters.

Platform updates (01:42):
Mosaic AI Vector Search is now HIPAA-compliant in all regions except us-west-2
Meta Llama 3.1 405B models are now supported in Mosaic AI Model Training.
You can now specify a subset of columns in a table to use in a vector search index.
Foundation Model APIs pay-per-token is now GA: Pay-per-tokens models are accessible in your Databricks workspace

Featured Blog Posts (02:47):
Multi-Model Forecasting: A recent blog introduced the Many Model Forecasting (MMF) framework for the comparative evaluation of forecasting models on Databricks. MMF enables users to train and predict using multiple forecasting models at scale on hundreds of thousands to many millions of time series at their finest granularity.
LLMs Long Context RAG Performance: With the availability of LLMs with longer context lengths, LLM app developers are able to feed more documents into their RAG applications. The Mosaic AI Research team explored the impact of increased context length on the quality of RAG applications.
Unpacking Function Calling Evaluation: This blog post deep dives into function calling, what it is and how to evaluate it. It outlines strategies for improving an LLM's function calling and tool use abilities

Видео August ML & GenAI Announcements канала VectorLab