How to Orchestrate 100+ Agents With Claude Code
, I’ll discuss how to orchestrate a lot of different agents using Claude Code or any other coding agents When you work with coding agents, you want to run as…
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Why Specialization Is Inevitable
— Those who follow Dharma AI already know that we view specialization as one of the defining principles of effective AI systems, shaping everything from cost and performance to reliability…
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Lyria 3 expands to more Google products, adds more features
Providing new places to generate music High-quality music generation should be accessible wherever creativity happens. Whether you are an app developer, a business or music professional, or a creator, these…
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How NVIDIA’s Inference Software Stack Powers the Lowest Token Cost
As organizations move from AI pilots to production AI factories, infrastructure decisions have shifted from peak chip specifications to cost per token: how many useful tokens they can deliver per…
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Why Doesn’t My Model Work?
Have you ever trained a model you thought was good, but then it failed miserably when applied to real world data? If so, you’re in good company. Machine learning processes…
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Why Your Best People Can’t Save a Broken Delivery System
When delivery falls apart, the reflex is to blame the team. Missed dates, quality slips, a burned-out squad — leadership tends to reach for a personnel fix and quietly move…
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A Coding Guide to NVIDIA’s Tile-Based GPU Programming: From cuTile and Triton Kernels to Flash Attention
if BACKEND == “triton”: @triton.jit def _vadd_kernel(a_ptr, b_ptr, c_ptr, n, BLOCK: tl.constexpr): pid = tl.program_id(0) offs = pid * BLOCK + tl.arange(0, BLOCK) mask = offs < n a =…
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RAG vs Fine-Tuning Explained: What They Actually Do and When to Use Each
, I have written quite a lot about RAG, starting with the Hitchhiker’s Guide to RAG with ChatGPT API and LangChain, and then exploring various topics related to RAG and…
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🤗 Kernels: Major Updates
In our previous post (From Zero to GPU), we introduced the 🤗 Kernels project, which aims at standardizing how custom kernels are packaged, distributed, and consumed. We want the project…
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Our most capable open models to date
At the edge, our E2B and E4B models redefine on-device utility, prioritizing multimodal capabilities, low-latency processing and seamless ecosystem integration over raw parameter count. Powerful, accessible, open To power the…
