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Inference Is the Last LLM Moat
The conventional wisdom about AI companies' competitive advantages focuses on model quality, training data, and research talent. A growing argument suggests the real differentiator is far more mundane: the infrastructure that runs...
Anthropic CEO renews call for AI slowdown as Nvidia's urges acceleration
The tension between building AI fast and building it safely played out on stage at Salesforce's Dreamforce conference in San Francisco this week, where two of the industry's most prominent CEOs offered starkly different prescripti...
The Bad Guy with an AI Named Claude
Anthropic published a detailed report this week cataloging misuse attempts against its Claude model spanning eight months, from December 2025 through August 2026. The report covers seven categories of harm, from cyber espionage to...
Show HN: SeaSearch – Lightweight, S3-backed multi-tenant search engine
The search infrastructure most teams run today is Elasticsearch, and for good reason. It handles full-text search at scale, has a mature ecosystem, and its API has become the de facto standard. But Elasticsearch carries architectu...
Divide, Consult, Conquer: Capability Laundering Through Aligned LLMs
A new research paper submitted to arXiv this week describes an attack method that undermines the core assumption behind large language model safety: that refusing harmful requests prevents harm. The technique, which the authors ca...
Agentic Societies Need a Social Harness
When AI Agents Talk to Each Other, They Need More Than a Protocol Imagine two AI agents, each working on behalf of a different person, trying to schedule a meeting. One has access to its principal's calendar. The other has access...
When Should LLMs Abstain? Chain-of-Self-Questioning for Selective Risk Control
LLMs Should Know When to Say "I Don't Know" Language models are fluent by default. Ask them a question they cannot answer, and they will produce something that sounds right, reads well, and might be completely wrong. In healthcare...
Verifiable Social Reasoning for LLM Assistants
Why Your Chatbot Can't Read Between the Lines When you tell your LLM assistant that a coworker seems a little too eager to help, you're giving it a subjective, filtered, emotionally loaded account of reality. The assistant never s...
LimiX-2: A Contextual Mechanism Network Towards General Structured-Data Intelligence
A Tabular Foundation Model That Learns Joint Distributions, Not Just Predictions Tabular data is the unglamorous backbone of machine learning in practice. Healthcare records, financial transactions, sensor readings, scientific mea...
JustFit: 200K-Token LLM Serving on a 24 GiB Laptop with Just-in-Time State Management
Fitting a 27B-Parameter LLM into 24 GiB of Laptop Memory The promise of local LLM inference is straightforward: run capable models on hardware you own, keep your data private, and avoid API costs. The obstacle is equally straightf...