Rubric-Based LLM Judging on SageMaker AI: Actionable Evaluations, YAML Outputs, and CI/CD Playbook

Rubric-based LLM judging: a practical upgrade for model evaluation on Amazon SageMaker AI TL;DR Nova’s rubric-based LLM judge on Amazon SageMaker AI replaces blunt A/B wins with prompt-specific, weighted rubrics that explain why one answer is preferred—and where it failed. This approach produces per-criterion scores, natural‑language justifications, calibrated confidence, and a machine-readable YAML/Parquet output you […]

Big Tech’s $660B AI Capex Wave: Investors Demand Faster ROI and Measurable Payback

Big Tech’s $660B AI Bet — Why Investors Want Faster ROI TL;DR Big Tech plans roughly $660 billion in AI-related capital expenditures (capex) this year; investors responded by wiping about $900 billion from market value across major firms. Spending aims to buy AI infrastructure—data centers, chips, models—but markets now demand nearer-term revenue, not just scale. […]

How ZDNET Tests Headphones in 2026 — Real‑World Trials, Not Just Lab Charts

How ZDNET Tests Headphones in 2026: Real‑World Runs, Not Just Lab Charts Headphone lab charts matter — but they don’t tell you how a pair behaves on a cross‑country flight or during a sweaty run. ZDNET’s headphone testing pairs objective measurement with weeks of everyday use to answer that practical question: how will this gear […]

Claude Opus 4.6: 1M-Token Agentic AI Unlocking Enterprise Automation & Long-Context Workflows

Claude Opus 4.6: Building Agentic AI with a 1M‑Token Memory TL;DR — Key takeaways What it is: Claude Opus 4.6 (model ID: claude-opus-4-6) is Anthropic’s push toward agentic AI and long‑horizon automation with beta support for a 1,000,000‑token context and up to 128,000 output tokens. What’s new: a massive context window, four configurable effort levels, […]

Claude Opus 4.6: 1M‑Token Context and AI Agents Transform Enterprise Workflows

Claude Opus 4.6: How new AI agents and a 1M‑token context change AI for business TL;DR: Anthropic’s Claude Opus 4.6 pushes LLMs toward autonomous, end‑to‑end work on high‑value enterprise tasks. Key advances: stronger agentic planning (parallel subagents), a beta 1M‑token long‑context window, and productivity integrations like PowerPoint that respect templates. Early vendor tests report measurable […]

GPT-5.3-Codex: Agentic AI for Long-Running Dev Workflows – Pilot Plan for CTOs

GPT-5.3-Codex: When code assistants become long-running AI agents TL;DR: GPT-5.3-Codex is a faster, more agentic Codex release from OpenAI that can run extended, multi-step software workflows—think triaging failing tests overnight, proposing patches, and opening PRs automatically. It’s reported to be ~25% faster than prior Codex versions and was even used by OpenAI to help debug […]

Best Business Messaging Apps of 2026: AI Features, Pricing and Top Picks for Teams

The best business messaging apps of 2026: AI features, pricing, and picks for teams TL;DR Slack — Best for integration-heavy teams and neutral ecosystems; excels at AI-powered summaries and workflow automation. (Estimate: paid tiers from ~$8.75/user/month — verify with vendor.) Microsoft Teams — Best for organizations committed to Microsoft 365; strong compliance, meetings, and single-vendor […]

Local AI Agents: Qwen3-coder, Ollama & Goose — Cut Cloud Costs, Keep Code In-House

Local agentic coding: replace cloud coding agents with Qwen3‑coder, Ollama and Goose TL;DR: For teams wrestling with recurring cloud bills, IP exposure or compliance rules, a practical local agentic coding stack exists today: Qwen3‑coder (a downloadable coding LLM), Ollama (a local LLM runtime), and Goose (an orchestration agent). It trades subscription and data egress for […]

VIBETENSOR: LLM Agents Built a CUDA-First Deep-Learning Runtime — Kernel Gains, System Tradeoffs

VIBETENSOR: How LLM Agents Built a CUDA‑First Deep Learning Runtime TL;DR: VIBETENSOR is an open-source, CUDA‑first deep‑learning runtime where LLM‑powered coding agents wrote most of the implementation under human high‑level direction. It demonstrates that agents can assemble a multi‑language runtime and validate it with automated tests, but kernel‑level speedups (≈5–6× in microbenchmarks) did not translate […]