1. Ars Technica Retracted a Story About AI After Its Own Reporter Fabricated Quotes With ChatGPT Scott Shambaugh spent his Friday reading quotes attributed to him that he never said.

2. AI Capital Bets on Famous Founders While Researchers See Nothing New Three signals from the same week. Ricursive Intelligence closed $335 million at a $4 billion valuation, four months after its founding.

3. AI Labs Keep Building Products Their Users Don't Want OpenAI wants to replace Slack. Anthropic tried to clean up Claude Code's interface. Both efforts landed in the same place: a wall of developer anger.

In Brief

• Alibaba Releases Qwen3.5 With Native Multimodal Agent Support Alibaba's Qwen team launched Qwen3.5, a model built for natively multimodal agent workflows. The release targets growing demand for models that handle multiple input types while executing multi-step tasks autonomously. Qwen Blog

• NVIDIA Claims Blackwell Ultra Delivers 50x Performance Gain for Agentic AI NVIDIA cited SemiAnalysis InferenceX benchmarks showing Blackwell Ultra achieves up to 50x better performance and 35x lower costs on agentic AI workloads. Inference providers Baseten, DeepInfra, Fireworks AI, and Together AI already run the current Blackwell platform, which cut cost per token by up to 10x. NVIDIA Blog

• Western Digital Says Hard Drives Are Sold Out for 2026 Western Digital reported its HDD inventory is fully allocated for the year. AI data center buildouts are driving storage demand past manufacturing capacity. Mashable

• Study Finds AI Agents' Self-Generated Skills Provide No Benefit An arXiv paper tested whether skills that AI agents generate for themselves actually improve performance. The researchers concluded these self-generated skills are effectively useless. arXiv

• MedXIAOHE Medical Vision-Language Model Beats Closed-Source Systems Researchers released MedXIAOHE, a medical vision-language model that outperforms leading closed-source multimodal systems across multiple clinical benchmarks. The model uses entity-aware continual pretraining to organize heterogeneous medical data and broaden knowledge coverage. Hugging Face

• Flapping Airplanes Pursues Alternative Approaches to AI Architecture AI startup Flapping Airplanes told TechCrunch it is exploring "radically different" methods for building AI systems outside the dominant scaling paradigm. The company described its work as investigating a different set of tradeoffs from mainstream labs. TechCrunch

• Favia Agent Automates CVE-to-Commit Matching in Large Repositories Researchers introduced Favia, an AI agent that links disclosed CVEs to their fixing commits across repositories with millions of commits. Existing methods — both traditional ML and LLM-based — struggle with precision-recall tradeoffs when the vast majority of commits are unrelated to security. Hugging Face

• Essay Argues AI Optimism Tracks With Economic Privilege Developer Josh Collinsworth published a post examining how enthusiasm for AI tools correlates with socioeconomic class. The essay argues AI's benefits and harms distribute unevenly across income levels. Josh Collinsworth

• Simon Willison Describes Claude Code Desktop Workflow Simon Willison detailed his setup using Anthropic's cloud-based Claude Code exclusively through native Mac and iPhone apps. He prefers the container-based environment over local execution, citing reduced risk to his own machines. Simon Willison

• Paper Proposes Feature Activation Coverage to Measure Training Data Diversity Researchers introduced Feature Activation Coverage (FAC), which quantifies post-training data diversity in an interpretable feature space. Standard text-based diversity metrics capture linguistic variation but provide weak signals for actual downstream task performance. Hugging Face

Read the full edition →