"you only have like 15% of the chip being utilized." - @AnjneyMidha
Getting more out of the GPU is exactly what we're working on at @GraphsignalAI, particularly with auto-flags: https://t.co/p0EPPsTUZI
(Our founder @dmitrimelikyan in the background at the @tbpn podcast recording for additional validation 😄)
autodebug: an autonomous loop that deploys an inference service, benchmarks it, reads profiling telemetry, and redeploys with a better config. Then repeats.
Uses @GraphsignalAI for inference profiling, @dstackai for GPU provisioning, Claude Code as the agent.
https://t.co/HHdHa6TcaM https://t.co/IsIBt9hbel
Now @GraphsignalAI integrates with dstack — add @sgl_project profiling, tracing, and GPU metrics to your inference services.
pip install 'graphsignal[cu12]' + wrap with graphsignal-run. That's it.
https://t.co/TEFptiG1ak
Exciting news today! @GraphsignalAI can now automatically trace and monitor 🦙 LlamaIndex @gpt_index applications in production and development.
Details here: https://t.co/c6qbckDovy
Did an experiment with prompting #ChatGPT to generate #Prolog program to solve a simple logical problem (instead of hallucinating an answer) and then running it in Prolog interpreter. Kind of works, except too much creativity😀. Works better with low temperature in Playground.