Do curated, tool-grounded demonstrations construct stronger software program brokers than broad piles of generic instruction information? A workforce of researchers from Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) proposes LIMI (“Less Is More for Agency”), a supervised fine-tuning technique that turns a base mannequin right into a succesful software program/analysis agent…
Building strong AI brokers differs essentially from conventional software program improvement, because it facilities on probabilistic mannequin habits slightly than deterministic code execution. This information supplies a impartial overview of methodologies for designing AI brokers which might be each dependable and adaptable, with an emphasis on creating clear boundaries, efficient behaviors, and protected interactions. What…
Table of contents Why WER Isn’t Enough ? What to Measure (and How) ? Benchmark Landscape: What Each Covers Filling the Gaps: What You Still Need to Add A Concrete, Reproducible Evaluation Plan References Optimizing just for Automatic Speech Recognition (ASR) and Word Error Rate (WER) is inadequate for contemporary, interactive voice brokers. Robust analysis…
What if, as an alternative of re-sampling one agent, you may push Gemini-2.5 Pro to 34.1% on HLE by mixing 12–15 tool-using brokers that share notes and cease early? Google Cloud AI Research, with collaborators from MIT, Harvard, and Google DeepMind, launched TUMIX (Tool-Use Mixture)—a test-time framework that ensembles heterogeneous agent types (text-only, code, search,…
In this tutorial, we construct an superior agentic AI system that autonomously handles time collection forecasting utilizing the Darts library mixed with a light-weight HuggingFace mannequin for reasoning. We design the agent to function in a notion–reasoning–motion cycle, the place it first analyzes patterns within the knowledge, then selects an acceptable forecasting mannequin, generates predictions,…
Microsoft launched the Microsoft Agent Framework (public preview), an open-source SDK and runtime that unifies core concepts from AutoGen (agent runtime and multi-agent patterns) with Semantic Kernel (enterprise controls, state, plugins) to assist groups construct, deploy, and observe production-grade AI brokers and multi-agent workflows. The framework is on the market for Python and .NET and…
How do you make an LLM agent truly study from its personal runs—successes and failures—with out retraining? Google Research proposes ReasoningBank, an AI agent reminiscence framework that converts an agent’s personal interplay traces—each successes and failures—into reusable, high-level reasoning methods. These methods are retrieved to information future choices, and the loop repeats so the agent…
In this tutorial, we stroll by the implementation of an Agentic Retrieval-Augmented Generation (RAG) system. We design it in order that the agent does extra than simply retrieve paperwork; it actively decides when retrieval is required, selects the perfect retrieval technique, and synthesizes responses with contextual consciousness. By combining embeddings, FAISS indexing, and a mock…
In this tutorial, we stroll you thru the design and implementation of a complicated Supervisor Agent Framework utilizing CrewAI with Google Gemini mannequin. We arrange specialised brokers, together with researchers, analysts, writers, and reviewers, and deliver them beneath a supervisor agent who coordinates and displays their work. By combining structured activity configurations, hierarchical workflows, and…
Anthropic launched Claude Sonnet 4.5 and units a brand new benchmark for end-to-end software program engineering and real-world pc use. The replace additionally ships concrete product floor modifications (Claude Code checkpoints, a local VS Code extension, API reminiscence/context instruments) and an Agent SDK that exposes the identical scaffolding Anthropic makes use of internally. Pricing stays…