Agentic AI

A crew of Salesforce AI researchers launched WALT (Web Agents that Learn Tools), a framework that reverse-engineers latent web site performance into reusable invocable instruments. It reframes browser automation round callable instruments quite than lengthy chains of clicks. Agents then name operations equivalent to search, filter, type, post_comment, and create_listing. This reduces dependence on giant…

Computer-use brokers have been restricted to primitives. They click on, they kind, they scroll. Long motion chains amplify grounding errors and waste steps. Apple Researchers introduce UltraCUA, a basis mannequin that builds an hybrid motion area that lets an agent interleave low degree GUI actions with excessive degree programmatic device calls. The mannequin chooses the…

In this tutorial, we discover how to construct a small but useful multi-agent system utilizing the uAgents framework. We arrange three brokers — Directory, Seller, and Buyer — that talk through well-defined message protocols to simulate a real-world market interplay. We design message schemas, outline agent behaviors, and implement request-response cycles to reveal discovery, negotiation,…

Pokee AI has open sourced PokeeResearch-7B, a 7B parameter deep analysis agent that executes full analysis loops, decomposes a question, points search and learn calls, verifies candidate solutions, then synthesizes a number of analysis threads into a ultimate response. The agent runs a analysis and verification loop. In analysis, it calls exterior instruments for internet…

In this tutorial, we discover how we will construct a compact but highly effective Enterprise AI assistant that runs effortlessly on Colab. We begin by integrating retrieval-augmented era (RAG) utilizing FAISS for doc retrieval and FLAN-T5 for textual content era, each absolutely open-source and free. As we progress, we embed enterprise insurance policies similar to…