Super cool work from Databricks AI research team.
Data agents are harder than coding agents. Coding agents have verifiable tests. Data agents have to find “truth” across millions of tables, docs, dashboards.
Databricks Genie got to 91.6% accuracy, while the leading coding agent only got 32% on enterprise data analysis tasks.
Specialized knowledge search + Parallel Thinking + Multi-LLM is the key.
Databricks has an amazing research team, and I've been enjoying working with them!
This is kind of embarrassing for the PBI team to explain to their users their decision making but still not address BI compatibility mode.
PBI users know that @tableau and @sigmacomputing want their products to work with UC Metric Views. Why cant PBI users also have nice things
"However much they're earning now, their revenues are only as durable as the spend from the person above them who is buying their products. And as you do get further down the layers, you do lose visibility in what's going on above you."
GMO's Tom Hancock on the layered nature of AI spending.
@kurtbuhler@evanyi_81 Hmm, it seems like the governance and distribution for these types of data apps are largely solved in both Databricks and Snowflake.
Want to host Claude meetups in your city? We'll cover the funding, send swag, and give you monthly API credits for your demos.
You also get access to pre-release features and a private slack with the team! Go apply 💛
A 2-star QB scrambling for potentially the national-championship-winning touchdown on 4th down in his hometown against his hometown team after winning the Heisman for the most losing program of all time while his mother with MS screams for joy from her seat is possibly the limit of how good sports can get