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Fujitsu launches made-in-Japan next-generation CPU FUJITSU-MONAKA

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GEFS on OpenBSD: A Early Preview

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Beyond the model: Engineering AI infra with scientific judgement

Jiga (YC W21) Is Hiring Product Engineer (Remote/US)

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Dense vs. MoE Models: Active Parameters, Throughput, and When to Choose Each

How can a 30B-parameter model activate only 3B parameters per token, and still use the capacity of the larger model? Nemotron 3.5 Lightning illustrates the... How can a 30B-parameter model activate only 3B parameters per token, and still use the capacity of the larger model? Nemotron 3.5 Lightning illustrates the answer: It uses a Mixture-of-Experts (MoE) architecture that selects only a subset of its parameters for each token. There are two dominant model architectures: Dense model and MoE. How

From better privacy to our new ChatGPT plugin, here's what's new on Stack Overflow for Agents

We've learned a lot in the last three months since launching Stack Overflow for Agents, our API-first knowledge exchange for agents. Here's a few of our findings, what's new on the platform (including our new ChatGPT plugin), and how we're continuing to build Stack Overflow.

KV Cache vs Prompt Cache: What's the Difference, and How Are They Related?

This article was originally published on my blog. For the latest version and future updates, please visit the original post: https://jaketao.com/language/en/kv-cache-vs-prompt-cache/. Every time a large language model generates a token, it draws on the content that came before it. If it had to compute everything from scratch at every step, responses would be much slower. When building an agent, the same set of system prompts, tool definitions, and conversation history is used over and over again

Agentic AI Threat Intelligence Essentials

Agentic AI can help threat intelligence teams move faster across collection, enrichment, correlation, and drafting while keeping critical judgments in human hands. This Refcard covers the essentials of building agent-supported intelligence workflows, including how to preserve provenance, evaluate source reliability and confidence, produce analyst-ready outputs, and apply review and operating guardrails. You’ll also learn how to measure whether agent-supported intelligence is timely, relevant, an