Google AI Releases Auto-Diagnose: An Large Language Model LLM-Based System to Diagnose Integration Test Failures at Scale
If you have ever stared at thousands of lines of integration test logs wondering which of the sixteen log files actually contains your bug, you are not alone — and Google now has data to prove it. A team of Google researchers introduced Auto-Diagnose, an LLM-powered tool that automatically reads the...
Top 19 AI Red Teaming Tools (2026): Secure Your ML Models
As Generative AI matures, so do the threats against it. AI Red Teaming has evolved from a niche security practice into a regulatory requirement. Our 2026 guide breaks down the top 19 tools—including Mindgard, Garak, and Microsoft’s PyRIT—to help security teams identify vulnerabilities like data leak...
Beyond Prompting: Using Agent Skills in Data Science
How I turned my eight-year weekly visualization habit into a reusable AI workflow
The post Beyond Prompting: Using Agent Skills in Data Science appeared first on Towards Data Science.
Oceania’s Quantum Horizon: How AI Innovation Is Quietly Rewriting the Future Across the Pacific
This article supports AI Quantum Intelligence's representation of regional interests and diversity around AI and advanced technology topics. AI and quantum innovation are accelerating across Oceania—from climate resilience to sovereign tech and Pacific-driven research shaping the region’s future.
The Human Infrastructure: How Netflix Built the Operations Layer Behind Live at Scale
By: Brett Axler, Casper Choffat, and Alo LowryIn the three years since our first Live show, Chris Rock: Selective Outrage, we have witnessed an incredible expansion of our live content slate and the live operations that support it. From modest beginnings of streaming just one show per month, we are ...
Anthropic launches Claude Design, a new product for creating quick visuals
The company says Claude Design is intended to help people like founders and product managers without a design background share their ideas more easily.
What if an unsupervised model could become a strong classifier with only a handful of labels?
The post You Don’t Need Many Labels to Learn appeared first on Towards Data Science.
Anthropic Launches Claude Opus 4.7 For “Most Difficult Tasks”
Artificial intelligence is rapidly developing. The minute we become accustomed to one breakthrough, another comes to shift our expectations. The new model, Claude Opus 4.7, that Anthropic introduced recently, is one such shift. The release tends to go beyond mere AI chatbots and makes AI a trusted, ...
Roboticists used to dream big but build small. They’d hope to match or exceed the extraordinary complexity of the human body, and then they’d spend their career refining robotic arms for auto plants. Aim for C-3P0; end up with the Roomba. The real ambition for many of these researchers was the robo...
Qwen Team Open-Sources Qwen3.6-35B-A3B: A Sparse MoE Vision-Language Model with 3B Active Parameters and Agentic Coding Capabilities
Qwen Team Open-Sources Qwen3.6-35B-A3B: A Sparse MoE Vision-Language Model with 3B Active Parameters and Agentic Coding Capabilities
The post Qwen Team Open-Sources Qwen3.6-35B-A3B: A Sparse MoE Vision-Language Model with 3B Active Parameters and Agentic Coding Capabilities appeared first on MarkTec...
Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making
arXiv:2604.14240v1 Announce Type: new
Abstract: The simulation of complex systems increasingly relies on sophisticated but fundamentally opaque computational black-box simulators. Surrogate models play a central role in reducing the computational cost of complex systems simulations across a wide ra...
Portfolio Optimization Proxies under Label Scarcity and Regime Shifts via Bayesian and Deterministic Students under Semi-Supervised Sandwich Training
arXiv:2604.14206v1 Announce Type: new
Abstract: This paper proposes a machine learning assisted portfolio optimization framework designed for low data environments and regime uncertainty. We construct a teacher student learning pipeline in which a Conditional Value at Risk (CVaR) optimizer generate...
Bringing AI-driven protein-design tools to biologists everywhere
Founded by Tristan Bepler PhD ’20 and former MIT professor Tim Lu PhD ’07, OpenProtein.AI offers researchers open-source models and other tools for protein engineering.
NuHF Claw: A Risk Constrained Cognitive Agent Framework for Human Centered Procedure Support in Digital Nuclear Control Rooms
arXiv:2604.14160v1 Announce Type: new
Abstract: The rapid digitization of nuclear power plant main control rooms has fundamentally reshaped operator interaction patterns, introducing complex soft-control behaviors and elevated cognitive risks that are not adequately addressed by existing human reli...
Simulating Human Cognition: Heartbeat-Driven Autonomous Thinking Activity Scheduling for LLM-based AI systems
arXiv:2604.14178v1 Announce Type: new
Abstract: Large Language Model (LLM) agents have demonstrated remarkable capabilities in reasoning and tool use, yet they often suffer from rigid, reactive control flows that limit their adaptability and efficiency. Most existing frameworks rely on fixed pipeli...
Fun-TSG: A Function-Driven Multivariate Time Series Generator with Variable-Level Anomaly Labeling
arXiv:2604.14221v1 Announce Type: new
Abstract: Reliable evaluation of anomaly detection methods in multivariate time series remains an open challenge, largely due to the limitations of existing benchmark datasets. Current resources often lack fine-grained anomaly annotations, do not provide explic...
Formalizing Kantian Ethics: Formula of the Universal Law Logic (FULL)
arXiv:2604.14254v1 Announce Type: new
Abstract: The field of machine ethics aims to build Artificial Moral Agents (AMAs) to better understand morality and make AI agents safer. To do so, many approaches encode human moral intuition as a set of axioms on actions e.g., do not harm, you must help othe...