![[P] Cadenza: Connect Wandb logs to agents easily for autonomous research.](https://d2xsxph8kpxj0f.cloudfront.net/310419663032563854/konzwo8nGf8Z4uZsMefwMr/default-img-server-room-ecVW4zMJjpPttojVbHXZCX.webp)
[P] Cadenza: Connect Wandb logs to agents easily for autonomous research.
Wandb CLI and MCP is atrocious to use with agents for full autonomous research loops. They are slow, clunky, and result in context rot. So I built a CLI tool and a Python SDK to make it easy to connect your Wandb projects and runs to your agent (clawed or otherwise). The cli tool works by allowing you to import your wandb projects and structures your runs in a way that makes it easy for agents to get a sense of the solution space of your research project. When projects are imported, only the configs and metrics are analyzed to index and store your runs. When an agent samples from this index, only the most high performing experiments are returned which reduces context rot. You can also change the behavior of the index and your agent to trade-off exploration with exploitation. Open sourcing
Could not retrieve the full article text.
Read on Reddit r/MachineLearning →Reddit r/MachineLearning
https://www.reddit.com/r/MachineLearning/comments/1scm9do/p_cadenza_connect_wandb_logs_to_agents_easily_for/Sign in to highlight and annotate this article
Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
autonomousagentresearch
Willitrun: benchmark-backed CLI to check whether ML models fit/run on your hardware
I built willitrun, a small CLI that tries to answer a question I kept running into with local/edge ML: will this model actually fit and run on my hardware? It uses benchmark data when available and falls back to lightweight estimation otherwise. One thing I wanted from the start was support for Hugging Face model IDs directly , so you can point the tool at a model from the Hub instead of manually entering all metadata yourself. The goal right now is not to be perfect, but to be useful enough to filter out obviously bad choices before spending time downloading or testing models manually. GitHub: GitHub - smoothyy3/willitrun: CLI to tell you if an ML model will fit and run on your device, using real benchmarks + lightweight estimation. · GitHub PyPI: willitrun · PyPI It is still early, and I
![[D] AI research on small language models](https://d2xsxph8kpxj0f.cloudfront.net/310419663032563854/konzwo8nGf8Z4uZsMefwMr/default-img-ai-chip-closeup-KMZ5N5zRxP2NRiYJ8TB9TM.webp)
[D] AI research on small language models
i'm doing research on some trending fields in AI, currently working on small language models and would love to meet people who are working in similar domains and are looking to write/publish papers! submitted by /u/StoicWithSyrup [link] [comments]
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Self-Evolving AI
Wikipedia's AI agent row likely just the beginning of the bot-ocalypse
Article URL: https://www.malwarebytes.com/blog/ai/2026/04/wikipedias-ai-agent-row-likely-just-the-beginning-of-the-bot-ocalypse Comments URL: https://news.ycombinator.com/item?id=47665902 Points: 17 # Comments: 7
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!