Agents of Chaos: what a live-lab red team found when AI agents ran loose
A two-week red-team study gave autonomous LLM agents real shells, email and memory. Ten of eleven scenarios produced a security or safety failure.
How Nous Research cut LLM pretraining time by 2.5x without changing the model
Nous Research's Token Superposition Training reduces LLM pretraining time by 2.5x at matched compute using a two-phase approach that requires no changes to model architecture, optimizer, or tokenizer.

the top affordable vector databases in 2025 for handling 1,000-5,000 high-dimensional embeddings without breaking the bank. Explore free tiers, performance insights, and expert tips to build efficient RAG systems – start your prototype today!

Why the new VSC (Values Separated by Comma) format for AI prompts isn't the breakthrough it claims to be. Learn when token optimization actually matters and when JSON is still your best choice with real examples and code.

Cut LLM API costs by 54% with TOON format. Replace JSON to save 62% tokens, reduce latency 12%, and save $336K annually. Python implementation guide included

Compare top RAG frameworks for 2025: LangChain, LlamaIndex, Haystack with performance data, adoption stats & cost analysis. Choose the best for your needs
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