Running a 70B model on a laptop with AirLLM: what it costs in time and where Microsoft Foundry fits
AirLLM lets you run a 70 billion parameter model on a 64 GB MacBook by loading one layer at a time from disk. It works. It is also about 900 times slower than the same model in Microsoft Foundry. An answer with 200 tokens takes more than an…
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From Edge to Enterprise Cloud: Part 4 — GenAIOps, Automated Evaluations and Observability with Microsoft Foundry
In our previous posts, From Edge to Enterprise-Cloud: Part 1: Building a Cost-Free Local Loop with Foundry Local, From Edge to Enterprise Cloud: Part 2: Tool Orchestration with the Model Context Protocol and From Edge to Enterprise Cloud:…
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From Edge to Enterprise Cloud: Part 2 — Tool Orchestration with the Model Context Protocol
In our first installment, From Edge to Enterprise-Cloud: Part 1: Building a Cost-Free Local Loop with Foundry Local, we established a completely offline, hardware-accelerated local loop using Microsoft Foundry Local. By embedding Small…
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From Edge to Enterprise-Cloud: Part 1 — Building a Cost-Free Local Loop with Foundry Local
In the fast-evolving landscape of Generative AI, developers are facing a silent productivity killer: feedback loop latency and unbudgeted cloud API costs. When building AI-driven agents, every tweak to a prompt, every revision of a system…
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Exploring Microsoft Foundry Local
With the Public Preview of Microsoft Foundry Local, Microsoft is taking a serious step toward bringing production-grade AI inference onto local hardware. After spending several days working with the preview, it became clear that Foundry…
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