Researchers trained an open source AI search agent, Harness-1, that outperforms GPT-5.4 on recalling relevant information

Harness-1 suggests that the future of agentic AI lies in building better environments for models to work within, rather than ...
InfoQ

Why Vector Search Alone Isn't Enough: Hybrid Retrieval for RAG

In this article, author Aaditya Chauhan discusses the limitations of RAG pipelines based purely on vector search and how an ...
IEEE

Differentiable Architecture Search Algorithm Based on Global Comparison

Abstract: Manually building neural network models is a great test of researchers’ knowledge reserves, so using Neural Architecture Search (NAS) to automatically construct neural networks is becoming ...
winbuzzer.com

Perplexity Lets AI Agents Write Their Own Search Code

Perplexity introduced Search as Code as a reference architecture for AI-written Python search workflows, following its 2025 real-time Search API. The new approach shifts the pitch from repeatedly ...