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We Specified an AI Agent in 2016. We Called It Analytics.

In November 2016, three colleagues and I at IBM filed a patent application with a title that sounds almost quaint today: “Real-Time Analysis of a Musical Performance Using Analytics” (published as US 2018/0137425 A1 [1]). The scenario we described was a rock concert. A guitarist plays an instrument with an embedded sensor, cameras read the …

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10 Free AI Tools That Replace Expensive Software for Data Scientists

Enterprise data science stacks are expensive. A single DataRobot seat can run over $50,000 a year. Tableau Creator costs around $900 per user annually. Commercial large language model (LLM) APIs charge per token, so a team running continuous data extraction or summarization pipelines can rack up thousands of dollars in monthly inference fees with no …

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How Can AI Agents Read Untrusted Sources Safely?

AI adoption’s main villain is safety. We’ve been seeing incidents of data exfiltration and confused deputy attacks. It happens because an LLM is probably the weakest link in the system. Most attacks happen when AI agents are exposed to the lethal trifecta. If agents can read from untrusted sources, access internal knowledge, and communicate to …

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Telehealth Rules for Older Adults: What Expires When

Short answer What does Medicare telehealth actually cover? Medicare telehealth rules are mostly temporary relief from restrictions that never went away. A law signed on 3 February 2026 rewrote nine dates across eight subsections, moving most of that relief to 31 December 2027. Somewhere in a paragraph of the Social Security Act there was a …

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Build Your First MCP Server in Python (Stateless Spec Edition)

The Model Context Protocol changed in an important way this summer. With the 2026-07-28 MCP specification, the protocol core is now stateless: modern clients no longer need to establish a protocol session before making requests, and servers no longer rely on Mcp-Session-Id for ordinary requests. That makes MCP servers much easier to scale behind normal …

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AI Agents Beat PyTorch: Writing Faster CUDA Kernels

In February 2025, Sakana AI announced that its “AI CUDA Engineer” generated 17,000 CUDA kernels with speedups of up to 381× over PyTorch. This is a system built to write CUDA kernels, the small programs that tell a computer’s graphics chip (the GPU) exactly how to crunch numbers. Within a day, an X user found …

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