Topics

Evaluation and benchmarks (what to trust)

Evergreen topic pages updated with new evidence

Answer

This topic page provides a direct answer, key points, and a source-backed evidence timeline. It is updated as the ecosystem changes.

Key points

  • Start from primary sources (official blog / repo / changelog) before citing or deciding.
  • Track by themes (topics/entities) so evidence accumulates on evergreen pages.
  • Use a weekly routine (shortlist → one action) to avoid doomscrolling.

What changed recently

  • New evidence and links are added as relevant updates appear for: benchmarks, evals, evaluation.

Explanation

This page is maintained as an evergreen knowledge page. It prioritizes clarity, trade-offs, and verifiable sources.

Tools / Examples

  • Use the evidence timeline to verify claims quickly.
  • Follow the sources section for primary-source citation.

Evidence timeline

AI Briefing, March 31 — Issue #161

Qwen3.5-Omni outperforms Gemini-3.1 Pro in multimodal benchmarks; PaddleOCR tops GitHub's global OCR list; InCoder-32B pioneers chip-design–focused code generation; Insilico Medicine and Eli Lilly ink a $2.75B AI drug di

March 30 AI Briefing · Issue #159

A critical gap in maintainability evaluation for AI programming tools is being exposed by SlopCodeBench, while Replit users achieve $8M ARR via Vibecoding—highlighting the commercial breakout potential of low-code + AI w

Sources

FAQ

How is this page maintained?

It is updated when new evidence appears, rather than creating thin pages for every headline.

How should I cite this page?

Use the primary source links for any citation or decision; cite this page as a summary layer if needed.

Last updated: 2026-03-31 · Policy: Editorial standards · Methodology