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In this tutorial, we walk through the process of creating a fully autonomous fleet-analysis agent using SmolAgents and a local Qwen model. We generate telemetry data, load it through a custom tool, and let our agent reason, analyze, and visualize maintenance risks without any external API calls. At each step of implementation, we see how […]
Google has open sourced A2UI, an Agent to User Interface specification and set of libraries that lets agents describe rich native interfaces in a declarative JSON format while client applications render them with their own components. The project targets a clear problem, how to let remote agents present secure, interactive interfaces across trust boundaries without
Anthropic has released Bloom, an open source agentic framework that automates behavioral evaluations for frontier AI models. The system takes a researcher specified behavior and builds targeted evaluations that measure how often and how strongly that behavior appears in realistic scenarios. Why Bloom? Behavioral evaluations for safety and alignment are expensive to design and maintain.
NVIDIA has released the Nemotron 3 family of open models as part of a full stack for agentic AI, including model weights, datasets and reinforcement learning tools. The family has three sizes, Nano, Super and Ultra, and targets multi agent systems that need long context reasoning with tight control over inference cost. Nano has about
In this tutorial, we devise how to orchestrate a fully functional, tool-using medical prior-authorization agent powered by Gemini. We walk through each component step by step, from securely configuring the model to building realistic external tools and finally constructing an intelligent agent loop that reasons, acts, and responds entirely through structured JSON. As we progress,
We explore how businesses can build readiness across teams, governance, and infrastructure to scale AI agents responsibly in 2026. The post Preparing for the Next Phase of Enterprise AI Agents in 2026 appeared first on Fusemachines.
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In this tutorial, we shift from traditional prompt crafting to a more systematic, programmable approach by treating prompts as tunable parameters rather than static text. Instead of guessing which instruction or example works best, we build an optimization loop around Gemini 2.0 Flash that experiments, evaluates, and automatically selects the strongest prompt configuration. In this
Fine-tune popular AI models faster with Unsloth on NVIDIA RTX AI PCs such as GeForce RTX desktops and laptops to RTX PRO workstations and the new DGX Spark to build personalized assistants for coding, creative work, and complex agentic workflows. The landscape of modern AI is shifting. We are moving away from a total reliance
While the headlines of the ongoing AI revolution are often dominated by large language models and generative software, the silent war is being fought in the data center. The hardware required to feed, train, and infer upon these models is […] The post Plumbing the AI Revolution: Lenovo’s Strategic Pivot to Modernize the Enterprise Backbone
Meta has released SAM Audio, a prompt driven audio separation model that targets a common editing bottleneck, isolating one sound from a real world mix without building a custom model per sound class. Meta released 3 main sizes, sam-audio-small, sam-audio-base, and sam-audio-large. The model is available to download and to try in the Segment Anything
