Industry
Anthropic releases 'safe' version of Claude Mythos AI model to public
Anthropic, the maker of the Claude artificial intelligence ( AI) models, made a new version of its technology available to the general public on Tuesday while restricting its use in sensitive areas. Dubbed Fable 5, the model is the first to be made widely available from the company's new Mythos class - its most advanced lineup of AI technology, unveiled in April but restricted to a small set of partner institutions for months over cybersecurity concerns. Anthropic promoted Fable 5 as useful for writing and debugging software code, answering complex research questions and analyzing images. Anthropic says the world should have option to'pause' on AI In parallel, Anthropic is offering an unrestricted version, Claude Mythos 5, to companies and organizations that already have access to this model family - including cybersecurity partners enrolled in its Project Glasswing program. That select group was expanded in early June to about 200 organizations in more than 15 countries and is expected to grow further.
DCcluster-Opt: Benchmarking Dynamic Multi-Objective Optimization for Geo-Distributed Data Center Workloads
The increasing energy demands and carbon footprint of large-scale AI require intelligent workload management in globally distributed data centers. Yet progress is limited by the absence of benchmarks that realistically capture the interplay of time-varying environmental factors (grid carbon intensity, electricity prices, weather), detailed data center physics (CPUs, GPUs, memory, HVAC energy), and geo-distributed network dynamics (latency and transmission costs). To bridge this gap, we present DCcluster-Opt: an open-source, high-fidelity simulation benchmark for sustainable, geo-temporal task scheduling. DCcluster-Opt combines curated real-world datasets, including AI workload traces, grid carbon intensity, electricity markets, weather across 20 global regions, cloud transmission costs, and empirical network delay parameters with physics-informed models of data center operations, enabling rigorous and reproducible research in sustainable computing. It presents a challenging scheduling problem where a top-level coordinating agent must dynamically reassign or defer tasks that arrive with resource and service-level agreement requirements across a configurable cluster of data centers to optimize multiple objectives. The environment also models advanced components such as heat recovery. A modular reward system enables an explicit study of trade-offs among carbon emissions, energy costs, service level agreements, and water use. It provides a Gymnasium API with baseline controllers, including reinforcement learning and rule-based strategies, to support reproducible ML research and a fair comparison of diverse algorithms. By offering a realistic, configurable, and accessible testbed, DCcluster-Opt accelerates the development and validation of next-generation sustainable computing solutions for geo-distributed data centers.
World's largest chipmaker does not rule out price rises as costs increase
World's largest chipmaker does not rule out price rises as costs increase The world's largest chipmaker has told the BBC that inflation is pushing up the cost of doing business, and did not rule out price rises. Taiwan Semiconductor Manufacturing Company (TSMC) makes the most advanced chips designed by companies such as Nvidia, AMD and Apple, so any increase in pricing could ripple through to the cost of AI infrastructure, and potentially over time, the prices customers pay for their electronic devices. However, the firm's chief financial officer, Wendell Huang, said it would not introduce sudden fourfold, fivefold price rises. We reflect our value, he said, pointing to its technology leadership and manufacturing excellence. In an exclusive and wide-ranging interview, Huang also denied that the AI boom was a bubble and that the firm's global expansion was due to geopolitical pressure.
Gwyneth Paltrow Just Goopified Drone Warfare
To meet this moment, we need YOU. For five decades, has been exposing the corruption that the powerful would rather keep buried. That fight for the truth is at a pivotal point, and it takes readers like you to make it possible. To meet this moment, we need YOU. That fight for the truth is at a pivotal point, and it takes readers like you to make it possible.
The rebels at the front line of Myanmar's civil war
In the five years since Myanmar's military chief led a coup to overthrow the democratically elected government, civil war has torn the country apart. Thousands have been killed and millions displaced by the conflict between the military and an alliance of ethnic and rebel groups. More than two years ago, the rebels made a series of sweeping gains, but things have taken a turn for the worse for them. Forced conscription and increased drone power has put the military on the offensive in most parts of the country. The BBC's Quentin Sommerville travelled to Myanmar without the permission of the authorities - the only way to report from rebel-held territory.
GM Wants Your Electric Car to Power Your House--and Your Neighborhood
The automaker today is turning on vehicle-to-grid charging for its GM Energy customers. Will people actually use it? Some 250,000 electric vehicles manufactured by General Motors are driving around the US today--right now!--with an oft-secret capability: Their big, powerful batteries can charge other things. Potentially appliances, homes, and now, thanks to a software update pushed by the automaker this week, an electrical grid . Twelve of GM's EVs have this "bidirectional charging" capability, way more than US competitors' battery-electrics.
Jacobian-Based Interpretation of Nonlinear Neural Encoding Model
In recent years, the alignment between artificial neural network (ANN) embeddings and blood oxygenation level dependent (BOLD) responses in functional magnetic resonance imaging (fMRI) via neural encoding models has significantly advanced research on neural representation mechanisms and interpretability in the brain. However, these approaches remain limited in characterizing the brain's inherently nonlinear response properties. To address this, we propose the Jacobian-based Nonlinearity Evaluation (JNE), an interpretability metric for nonlinear neural encoding models. JNE quantifies nonlinearity by statistically measuring the dispersion of local linear mappings (Jacobians) from model representations to predicted BOLD responses, thereby approximating the nonlinearity of BOLD signals. Centered on proposing JNE as a novel interpretability metric, we validated its effectiveness through controlled simulation experiments on various activation functions and network architectures, and further verified it on real fMRI data, demonstrating a hierarchical progression of nonlinear characteristics from primary to higher-order visual cortices, consistent with established cortical organization. We further extended JNE with Sample-Specificity (JNE-SS), revealing stimulus-selective nonlinear response patterns in functionally specialized brain regions. As the first interpretability metric for quantifying nonlinear responses, JNE provides new insights into brain information processing.
Anthropic's Fable AI brings the capabilities of its unreleased Mythos model to regular users
Anthropic's Fable AI brings the capabilities of its unreleased Mythos model to regular users Anthropic's Fable AI brings the capabilities of its unreleased Mythos model to regular users Claude subscribers can try the model until June 22 without spending usage credits. Anthropic has just announced Fable, the start of a new family of models that brings many of the capabilities of its Mythos system to the public. As a refresher, Mythos is the state-of-the-art model Anthropic debuted at the start of April through Project Glasswing . The project saw Anthropic share access to the model with select partners, including Apple and NVIDIA, with the aim of helping those organizations harden their software against AI cyberattacks. Glasswing also prompted the White House to rethink its policy on AI regulation .