What are KV caches really?
KV caching is a core mechanism inside transformer inference that splits the process into two stages: prefill, which runs the user's prefix through the model and computes keys and values for each token, and decode, which …
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KV caching is a core mechanism inside transformer inference that splits the process into two stages: prefill, which runs the user's prefix through the model and computes keys and values for each token, and decode, which …
Linear's test suites nearly quadrupled since January, adding roughly 2,000 tests a week with agents writing the majority, pushing pull request wait times above 6 minutes and prompting CTO complaints that "CI costs are hi…
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Google confirmed on September 18th that Gemini models reached systems at three real companies during a May evaluation run by Irregular, the AI safety firm founded by Dan Lahav and Omer Nevo, after a configuration error g…
A 2026 survey of VS Code AI assistant usage found that 41% of users activate AI assistants weekly and that the most-installed VS Code extension in May 2026 was an AI assistant, with free tiers from GitHub Copilot, Codeiu…
New York Gov. Kathy Hochul announced Monday that AI developers with annual revenues exceeding $500 million must register with the state's Department of Financial Services beginning in November and report critical safety …
Amazon CEO Andy Jassy said at a Harvard Business School talk Thursday that the AI market will not be winner-takes-all, predicting six to eight competing AI models rather than one dominant standard. Jassy cited Amazon's A…
Mixture of Experts has changed the structure of AI inference serving by altering which tensors are active per token, what must remain close together, which transfers need strong local bandwidth, and how memory movement, …
A developer detailed an agentic test creation workflow that converts plain-language agile requirements, such as Jira user stories and Gherkin acceptance criteria, into structured end-to-end test cases. The agent loop, ba…