
Inside GitHub's Fake Star Economy
Six million fake stars, $0.06 per click, and a VC funding pipeline that treats GitHub popularity as proof of traction. We ran our own analysis on 20 repos and found the fingerprints.

Three new papers: AlphaLab runs autonomous GPU research campaigns, open-weight reasoning models collapse under text reformatting, and HiL-Bench reveals agents can't decide when to ask for help.

UC Berkeley researchers achieved near-perfect scores on eight major AI agent benchmarks without solving a single task, exposing systemic flaws in how the industry measures progress.

Cloudflare Sandboxes are now generally available, giving AI agents persistent isolated environments with shell access, filesystem, PTY terminals, and background processes that start on demand and sleep when idle.

Stanford HAI's 2026 AI Index finds the US-China model gap has effectively closed, GenAI has hit 53% global adoption faster than any prior technology, and young software developers are the first casualties of the labor shift.

Leaked Claude screenshots reveal a full-stack app builder with templates, live preview, one-click publishing, and built-in databases - putting Anthropic on a direct collision course with Lovable's $6.6 billion vibe-coding empire.

A UPenn-BU paper models AI-driven layoffs as a Prisoner's Dilemma: each firm wins by automating, but when everyone does it, collapsing demand makes every firm worse off. Their proposed fix is a Pigouvian tax on automated tasks.

A developer used an HTTP proxy to capture full API requests across four Claude Code versions and found that v2.1.100 adds roughly 20,000 invisible server-side tokens to every request - inflating billing by 40% with no user visibility.

Three separate PRs merged into llama.cpp between April 11-13 add MERaLiON-2, Gemma 4's Conformer encoder, and Qwen3-Omni/ASR - making local voice AI inference practical on consumer hardware for the first time.

Six million fake stars, $0.06 per click, and a VC funding pipeline that treats GitHub popularity as proof of traction. We ran our own analysis on 20 repos and found the fingerprints.

A practical, step-by-step guide to using AI tools like ChatGPT, Claude, Duolingo Max, and Talkio to learn any language faster - no prior experience needed.

A practical beginner's guide to using AI tools for fiction, stories, and creative writing without losing what makes your work yours.

A beginner's guide to using AI tools like ChatGPT and Canva to write captions, plan posts, and save time on social media.

xAI's Grok 4.20 replaces the single-model approach with four specialized agents that debate before every answer - a bold architectural bet that pays off in some areas and stumbles in others.

Meta's first proprietary frontier model leads on HealthBench Hard and scientific reasoning but trails rivals in coding and agentic tasks - with no public API yet.

A deep look at Microsoft's three new in-house AI models - MAI-Transcribe-1, MAI-Voice-1, and MAI-Image-2 - and whether they live up to the hype.

Rankings of AI models on IFEval and IFBench, the two main benchmarks for measuring how reliably LLMs follow precise formatting, length, and content constraints.

Rankings of the most popular MCP servers across development, data, web automation, and productivity categories based on installs, search volume, and GitHub activity.

Rankings of the best AI models and agent frameworks on computer use benchmarks - OSWorld, OSWorld-Verified, and ScreenSpot-Pro - updated March 2026.

Meta's first closed-source frontier model scores 52 on the Artificial Analysis Intelligence Index, leads on HealthBench Hard, and ships free at meta.ai - but has no public API yet.

Gemma 4 is Google DeepMind's most capable open model family: four variants from 2B to 31B, Apache 2.0 license, multimodal across text/image/video/audio, and the 31B Dense ranking #3 on Chatbot Arena against all open-weight models globally.

Grok 4.20 is xAI's current flagship LLM with a 2M-token context window, native multi-agent mode, and reasoning toggle at $2.00/M input tokens.

Embedding API costs compared for OpenAI, Voyage AI, Cohere, Google, Mistral, and AWS - voyage-4-lite and OpenAI 3-small tie at $0.02/MTok for best budget value.

Three new papers: AlphaLab runs autonomous GPU research campaigns, open-weight reasoning models collapse under text reformatting, and HiL-Bench reveals agents can't decide when to ask for help.

UC Berkeley researchers achieved near-perfect scores on eight major AI agent benchmarks without solving a single task, exposing systemic flaws in how the industry measures progress.

xAI's Grok 4.20 replaces the single-model approach with four specialized agents that debate before every answer - a bold architectural bet that pays off in some areas and stumbles in others.

Cloudflare Sandboxes are now generally available, giving AI agents persistent isolated environments with shell access, filesystem, PTY terminals, and background processes that start on demand and sleep when idle.

Stanford HAI's 2026 AI Index finds the US-China model gap has effectively closed, GenAI has hit 53% global adoption faster than any prior technology, and young software developers are the first casualties of the labor shift.

Leaked Claude screenshots reveal a full-stack app builder with templates, live preview, one-click publishing, and built-in databases - putting Anthropic on a direct collision course with Lovable's $6.6 billion vibe-coding empire.

A UPenn-BU paper models AI-driven layoffs as a Prisoner's Dilemma: each firm wins by automating, but when everyone does it, collapsing demand makes every firm worse off. Their proposed fix is a Pigouvian tax on automated tasks.

A developer used an HTTP proxy to capture full API requests across four Claude Code versions and found that v2.1.100 adds roughly 20,000 invisible server-side tokens to every request - inflating billing by 40% with no user visibility.

Three separate PRs merged into llama.cpp between April 11-13 add MERaLiON-2, Gemma 4's Conformer encoder, and Qwen3-Omni/ASR - making local voice AI inference practical on consumer hardware for the first time.

Six million fake stars, $0.06 per click, and a VC funding pipeline that treats GitHub popularity as proof of traction. We ran our own analysis on 20 repos and found the fingerprints.

A 19-person Meta AI and KAUST team including Jürgen Schmidhuber proposes Neural Computers - systems where the neural network itself is the running computer, trained solely on screen recordings.