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AI Agents Are Now Operating Enterprise Networks. Trust Sets the Limits.

AI agents already act in production networks at 51% of surveyed organizations. Cisco and Omdia’s research explores how far companies will extend that authority and which controls they expect.

Claude Opus 5.5 Broke Our GPT-6 Benchmark

We tried to benchmark Claude Opus 5.5 against GPT-6 Sol. Then Opus kept building, judging, fixing, and iterating until the benchmark itself stopped making sense.

Meta’s Big AI Bet Now Fits on Your Keychain

Meta Connect put Muse on a keychain, promised it for AI glasses, and gave its personal agent voice, email, and computer-use ambitions. Here’s why I’m excited.

True Positive Weekly #179

The most important artificial intelligence and machine learning news and articles

😺 LIVE IN 5: GPT-6 Sol vs. Claude Opus 5.5

Who Made Space Bunny? A MiniMax Clue Sharpens the Mystery

Space Bunny is the latest free mystery model on OpenCode and OpenRouter. A new fingerprint points toward MiniMax, while Big Pickle’s 11-month run shows how long an AI model can stay behind an alias.

How to Maximize Your Coding Agent Subscriptions

Get more out of your coding agent subscriptions The post How to Maximize Your Coding Agent Subscriptions appeared first on Towards Data Science.

Beyond RAGs: Building Actually Truthful AI Harnesses

Retrieval is not evidence. How to build AI that proves its own claims. The post Beyond RAGs: Building Actually Truthful AI Harnesses appeared first on Towards Data Science.

Adobe Wants Its Tools Wherever Your Next Project Starts

Adobe’s latest updates put Photoshop and other creative tools on a path to Gemini, add Acrobat and hands-on editing to Claude, and bring Premiere to Android. The common thread: Adobe wants its tools available wherever a…

Towards Spec-Driven Test Automation: Part 1

Why a green test suite can mean nothing The post Towards Spec-Driven Test Automation: Part 1 appeared first on Towards Data Science.

Jensen Huang’s AI Safety Rule: If You Can’t Evaluate It, Don’t Ship It

Jensen Huang says AI labs should treat safety like engineering: evaluate, verify, contain, and don’t ship systems they can’t control. The deeper problem may be the industry’s scale-at-all-costs feedback loop.

When the Correct Answer Is Nothing, What Does Your Pipeline Return?

The reliability mechanisms we add to LLM pipelines are often the ones that make them confidently wrong. The post When the Correct Answer Is Nothing, What Does Your Pipeline Return? appeared first on Towards Data Science.

😺 What 950 Claude agents found

Value Mirror Descent for Reinforcement Learning

arXiv:2604.06039v2 Announce Type: replace-cross Abstract: Value iteration-type methods have been extensively studied for computing a nearly optimal value function in reinforcement learning (RL). Under a generative…

Parameter Importance-Driven Continual Learning for Foundation Models

arXiv:2511.15375v2 Announce Type: replace Abstract: Domain-specific post-training often causes catastrophic forgetting, making foundation models lose their general reasoning ability and limiting their adaptability to…

Scalable Subgraph Sampling via Resistance Curvature

arXiv:2609.27209v1 Announce Type: new Abstract: Subgraph sampling reduces the training cost of large-scale graph neural networks, but sampling criteria may overlook the geometric roles of edges. We propose a…

When Post-Processing Fairness Constraints Help and When They Harm: Evidence from Eight Cross-Domain Evaluations

arXiv:2609.26955v1 Announce Type: new Abstract: Fairness audits in production ML typically occur once, at deployment, on a single domain. Both fail in practice: fairness can shift after retraining or a changing user…

hyperbolix: Hyperbolic Deep Learning in JAX

arXiv:2609.28248v1 Announce Type: new Abstract: We present hyperbolix, an open-source library for hyperbolic deep learning in JAX, built on Flax NNX. To our knowledge, it is the first comprehensive, general-purpose…

MLSkip: Data Skipping for ML Filters via Lightweight Metadata

arXiv:2606.03946v2 Announce Type: replace-cross Abstract: Database vendors recently released AI functions that can be used in filter predicates. As such functions often rely on costly, black-box ML models, they unveil…