Tool Use
Tool Use on Beyond Market Intelligence: a running collection of 4 stories we have gathered and hand-picked because they are worth your time. Every post here touches on tool use in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around tool use, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
OpenAI Details GPT-Live’s Architecture for Continuous Stateful Voice Interaction
OpenAI has unveiled the architecture behind GPT-Live, a system designed for seamless, continuous voice interaction. This engineering account details a crucial separation: real-time media processing and inference operate within a low-latency "live path," while broader application logic, including tool use and persistence, functions asynchronously. This design empowers more responsive and adaptable AI conversations. For further insight into related AI model development challenges, explore our analysis of "First A submission (AAMAS)," available on our site.
How to Add Skills in Agents using LangChain
Ever questioned how chat interfaces like ChatGPT and Gemini effortlessly generate diverse outputs—PDFs, presentations, and more—despite relying on a core LLM? The secret lies in "skills," modular instructions loaded only when needed, not a fundamentally smarter model. This post explores how to implement skills within LangChain agents, unlocking a powerful approach to agentic workflows. Discover how this technique simplifies complex tasks and expands agent capabilities. For deeper insight into agent scaling challenges, see "Three Generations of Autoscaling."
Graph Engineering for AI Agents: Beyond the Single-Agent Loop
AI agent development is evolving beyond autonomous loops, with graph engineering emerging as a critical next step. This approach reframes AI applications as explicitly designed workflows, orchestrating agents, tools, and data sources for optimal coordination. Graph engineering defines these interactions, offering a more structured and predictable path toward complex AI solutions. Explore how this paradigm shift moves beyond the single-agent perspective—a concept further detailed in "MCP Explained: How Modern AI Agents Connect to the Real World"—and unlocks new possibilities for intelligent automation.
Complete Guide to Thinking Machines Inkling
Thinking Machines Lab’s Inkling represents a significant advancement in AI foundation models. This open-weights model, boasting 975B parameters and a 1M-token context window, prioritizes adaptability over benchmark scores. Designed as a customizable base for diverse applications—from multimodal reasoning and agentic AI to coding and audio-visual tasks—Inkling empowers developers to build specialized solutions. Explore the complete guide to understand Inkling's architecture and potential. For broader context on the evolving AI landscape, consider "What to watch for after Jensen Huang’s Japan visit."