Microsoft Research Releases Webwright: A Terminal-Native Web Agent Framework That Scores 60.1% on Odysseys, Up from Base GPT-5.4’s 33.5%

A hands-on walkthrough of a hybrid local-cloud workflow using Gemma 4 and GPT-5.4, with reasoning and structured outputs The post Stop Choosing Between Local and Cloud LLMs: A Field Guide to Hybrid Patterns appeared first on Towards Data Science.

With AI agents increasingly expected to remember conversations, preferences, and decisions over extended periods, Microsoft Research has developed Memora, a memory system designed to provide more scalable and reliable long-term recall than existing approaches. AI agents are increasingly expected to retain context across weeks or months rather than individual chat sessions. Memory can become fragmented, leading to duplicate information and slower retrieval as knowledge grows. According to Microsoft, Memora can solve this problem by decoupling what the AI remembers from how it looks up that information, ultimately reducing context token usage by up to 98% while matching or exceeding full-context accuracy, Microsoft Research claimed in a blog post. Limitations of today’s memory architectures As AI assistants and autonomous agents move into long-horizon deployments, the absence of a principled memory system has become a critical bottleneck. While modern LLMs are powerful reasoners, they st

With AI agents increasingly expected to remember conversations, preferences, and decisions over extended periods, Microsoft Research has developed Memora, a memory system designed to provide more scalable and reliable long-term recall than existing approaches. AI agents are increasingly expected to retain context across weeks or months rather than individual chat sessions. Memory can become fragmented, leading to duplicate information and slower retrieval as knowledge grows. According to Microsoft, Memora can solve this problem by decoupling what the AI remembers from how it looks up that information, ultimately reducing context token usage by up to 98% while matching or exceeding full-context accuracy, Microsoft Research claimed in a blog post. Limitations of today’s memory architectures As AI assistants and autonomous agents move into long-horizon deployments, the absence of a principled memory system has become a critical bottleneck. While modern LLMs are powerful reasoners, they s

Most search agents try to handle too many jobs at once. They generate new queries, remember what they have already explored, collect evidence, and decide what is relevant as the search keeps expanding. That can make the whole process messy, expensive, and hard to control. Harness-1 takes a simpler approach. Built with researchers from UIUC, […] The post Harness-1: The 20B Retrieval Subagent That Beats GPT-5.4 at Search appeared first on Analytics Vidhya.

AI coding agents can tend to isolate research, running experiments and generating ideas that are then forgotten when context windows reset. This can waste tokens, as models then repeat the same mistakes and hit the same dead ends. But new research argues that it’s not the model itself, but the overarching ‘tree,’ that needs tweaking. To that end, data scientists from the Gaoling School of Artificial Intelligence, Renmin University of China, and Microsoft Research have introduced Arbor, a “persistent hypothesis tree” that helps agents remember and refine learnings over long research sessions. A long-lived coordinator manages research strategy across the tree, while short-lived executors spin up isolated worktrees to test different hypotheses. As results come back, the tree updates, narrowing and refining throughout experimentation. In practical tests, this technique delivered more than two-fold performance gains over standard AI coding agents across real-world engineering tasks, for the

AI-driven optimization in drug synthesis accelerates R&D timelines, potentially reducing costs and expediting market entry for pharmaceuticals. The post GPT-5.4 improves Chan-Lam coupling yields in drug discovery appeared first on Crypto Briefing.

OpenAI and Molecule.one show how a near-autonomous AI chemist using GPT-5.4 improved a key drug-making reaction, advancing medicinal chemistry research.

OpenAI frontier models GPT-5.5 and GPT-5.4, and Codex, the OpenAI coding agent, are now generally available on Amazon Bedrock. Deploy frontier models on Bedrock's high performance inference engine with built-in security, governance, and pay-per-token pricing.