Oh, sure, I can “code.” That is, I can flail my way through a block of (relatively simple) pseudocode and follow the flow. I ...

Say goodbye to source maps and compilation delays. By treating types as whitespace, modern runtimes are unlocking a “no-build” TypeScript that keeps stack traces accurate and workflows clean.

A recursive vibe journalism experiment in which Microsoft 365 Copilot's 'Prompt Coach' agent is used to wholly create an ...

Learn how to implement Single Sign-On with External Security Token Services (STS). A deep dive into SAML, OIDC, and token exchange for CTOs and VP Engineering.

点击上方“Deephub Imba”,关注公众号,好文章不错过 !这篇文章从头实现 LLM-JEPA: Large Language Models Meet Joint Embedding Predictive Architectures。需要说明的是，这里写的是一个简洁的最小化训练脚本，目标是了解 JEPA 的本质：对同一文本创建两个视图，预测被遮蔽片段的嵌入，用表示对齐损失来训练。本文的目标是 ...

Practice smart by starting with easier problems to build confidence, recognizing common coding patterns, and managing your ...

Weekly cybersecurity recap covering emerging threats, fast-moving attacks, critical flaws, and key security developments you need to track this week.

自2025年初DeepSeek R1模型发布以来，强化学习（RL）在大型语言模型（LLM）的后训练范式中受到越来越多的关注，R1的突破性在于引入了可验证奖励强化学习（RLVR），通过构建数学题、代码谜题等自动验证环境，使模型在客观奖励信号的驱动下，自发地演化出与人类推理策略高度相似的思维方式。