Daily AI Recap: Jul 13, 2026

Welcome to today's curated briefing of the most important AI developments.

• What Anthropic’s latest AI discovery does—and doesn’t—show: This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Anthropic—currently the world’s most valuable AI company, with...
• Sam Altman’s space data center trash talk is what most experts already believe: "homeboy you're the one sellling [sic] public market investors on short-term space datacenters."...
• Should AI help you get away with killing your spouse?: What does a world of total user-aligned AI actually look like?...
• Verifying Rust cryptography in SymCrypt, from standards to code: Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemente...
• Anthropic starts localizing Claude pricing for India, its biggest market after the US: Claude users in India are starting to see Indian rupee-denominated subscription plans....
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• Context Rot: Why Claude Code Sessions Decay, and How to Govern Them: Long sessions rot quietly, well before any token limit is reached. Here’s why, and how to govern your context in Claude Code. The post Context Rot: Why Claude Code Sessions Decay, and How to Govern Th...
• How to Measure Video Similarity: 6 Techniques I Tested (and the One I Shipped): Two short clips. One question: how alike do they look? Sounds trivial, it isn’t, and I learned that the slow way.  My setup: one reference clip, eight others to rank against it, all waterfalls (more o...
• iLENS: Interpretable LLM-Guided Mixture-of-Experts for Neuroimaging Survival Analysis: arXiv:2607.08778v1 Announce Type: new Abstract: Alzheimer's Disease (AD) is a complex neurodegenerative disorder that continues to impact millions of people worldwide. Predicting AD conversion during...
• Signed Symmetric Quantization for Few-Bit Integers: arXiv:2607.08779v1 Announce Type: new Abstract: The signed integer alphabet contains one more negative representable value than positive. Yet, by convention, the standard symmetric integer quantizer ...
• Reward Transport: Property Control in Flow Matching via Noise-Space Alignment: arXiv:2607.08781v1 Announce Type: new Abstract: The coupling in flow matching -- the rule pairing noise vectors with data points -- is typically treated as a computational choice. We show that this c...
• Stanford Study Exposes Major Flaw in AI Mental Health Safety Testing: With increased use of chatbots in mental health contexts, AI developers now rely on human experts to evaluate AI’s responses for “safety” – but experts rarely agree on what’s safe....

• Meet NeuroVFM: A New Neuroimaging Foundation Model Trained With Vol-JEPA on Uncurated Clinical MRI and CT Volumes: NeuroVFM is a generalist neuroimaging foundation model from the University of Michigan, trained on 5.24M clinical MRI and CT volumes. Its Vol-JEPA bas...
• A Unified Approach to Interpreting Knowledge Distillation for Large Language Models via Interactions: arXiv:2607.08776v1 Announce Type: new Abstract: Despite the success of knowledge distillation (KD) in Large Language Models (LLMs), the underlying me...
• Sticky Routing: Training MoE Models for Memory-Efficient Inference: arXiv:2607.08780v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models activate only a sparse subset of experts per token, yet consecutive t...
• New method aims to keep kids safe from illegal AI-generated content: Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs....
• Interval Certifications for Multilayered Perceptrons via Lattice Traversal: arXiv:2607.08773v1 Announce Type: new Abstract: In this work we present a rigorous theoretical framework to a foundational problem of AI safety, name...
• CogniConsole: Externalizing Inference-Time Control as a Formal Abstraction for Reliable LLM Interactions: arXiv:2607.08774v1 Announce Type: new Abstract: Reliability in large language model (LLM) systems is typically framed as a function of model capabili...
• GATS: Graph-Augmented Tree Search with Layered World Models for Efficient Agent Planning: arXiv:2607.08894v1 Announce Type: new Abstract: Large Language Model (LLM) agents have shown promise in multi-step planning tasks, but existing appro...

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