ClippyGPT: OpenAI Doc Search for Supabase

ClippyGPT - How I Built Supabase’s OpenAI Doc Search (Embeddings) - YouTube

ask our old friend Clippy anything you want about Supabase, and it will answer it using natural language. Powered by OpenAI + prompt engineering. 

- Prompt engineering and best practices 

- Working with a custom knowledge base via context injection + OpenAI embeddings 

- How to store embeddings in Postgres using pgvector 

Supabase blog post: https://supabase.com/blog/chatgpt-sup... 

pgvector extension: https://github.com/pgvector/pgvector 

source code

Generate embeddings implementation: https://github.com/supabase/supabase/... 

Clippy edge function implementation: https://github.com/supabase/supabase/... 

Clippy frontend implementation: https://github.com/supabase/supabase/... 

Prompt engineering: https://prmpts.ai/blog/what-is-prompt...

X.AI: the most powerful AI cluster: 100,000 Nvidia H100 GPUs

 Elon Musk fires up ‘the most powerful AI cluster in the world’ to create the 'world's most powerful AI' by December — system uses 100,000 Nvidia H100 GPUs on a single fabric | Tom's Hardware

xAI’s Memphis Supercluster began AI training using 100,000 liquid-cooled Nvidia H100 GPUs connected with a single RDMA (remote direct memory access) fabric.

Supermicro provided much of the hardware, and the company's CEO, Charles Liang, also commented on Musk's thread, touting the team's execution. This follows Liang's recent glowing words for Musk's liquid-cooled AI data centers.

Elon Musk reveals photos of Dojo D1 Supercomputer cluster — roughly equivalent to 8,000 Nvidia H100 GPUs for AI training | Tom's Hardware