Very delayed news, but back in November @tensorstax was acquired by @Snowflake.
Since then our team has been hard at work building Cortex Code, the current SOTA data agent.
I'll be sharing more of our work/research going forward around harness engineering, cloud sandboxes, eval environments, RL and much more.
Another example from the Snowflake earnings call of customers building workflows and applications directly on top of their data
Customer essentially rebuilt Gainsight in 5 hours
What if Snowflake isn’t a victim of the SaaSpocalypse but rather the assailant…
This is what we have been working on for the last 6 months or so at the AI Snowflake Research:
Zero Redundancy Rollouts (ZoRRo):
https://t.co/OqiEPscuRL
If you do RL and you want it to be much faster make sure to have a look.
If this is true, using the best public estimates we have of LLM resource use, solving this Erdos problem took 0.6–6.3 kWh of electricity and about 3–31 liters of water.
So that is less than three almonds worth of water and the electricity equivalent of 2-20 miles of EV driving.
Very delayed news, but back in November @tensorstax was acquired by @Snowflake.
Since then our team has been hard at work building Cortex Code, the current SOTA data agent.
I'll be sharing more of our work/research going forward around harness engineering, cloud sandboxes, eval environments, RL and much more.
I trained models across MacBooks using Apple's AirDrop protocol.
grove is a distributed training library for Apple Silicon. Devices discover each other over AWDL, a direct radio link. If there's a shared WiFi network it upgrades to that for speed, otherwise everything goes over the direct link. No router, no cloud, no setup.
grove start <script> -n 4
grove join
Today we're launching Glaze 💠
Create any desktop app in minutes by chatting with AI.
Beautiful, powerful, and truly personal.
Learn more on https://t.co/tTL644I574
Follow @glazeapp for updates.
Transforming natural-language requests into reliable, production-ready data transformations remains challenging. Today, we're excited to announce Thinkquel, our most advanced 32B model for text-to-dbt tasks. Read the full paper below⬇️