NVIDIA and Berkeley Lab have developed Huge Ensembles (HENS), a machine learning tool that enhances extreme weather prediction with less computational power. By generating 27,000 years of climate data, HENS streamlines forecasts, allowing researchers to analyze rare weather events quickly and efficiently, while being energy-conserving and cost-effective.

A new study reveals how people are using ChatGPT in their daily lives, indicating a significant shift towards personal engagement over work-related tasks. Findings show that nearly 70% of interactions fall into non-work categories, highlighting AI's growing integration into personal activities like learning and leisure.

XTX has developed and open-sourced TernFS, a robust distributed filesystem designed to meet the demands of their growing computational needs. Capable of scaling to exabytes and offering significant redundancy, TernFS addresses storage challenges while ensuring high performance across multiple regions.

A former Palantir employee turned activist sheds light on the company’s controversial role in defense and surveillance. Juan Sebastián Pinto discusses his disillusionment with Palantir's involvement in issues such as immigration and international conflict, and his drive to advocate against the misuse of its technologies.

The EU Data Act is reshaping the SaaS landscape by eliminating traditional Annual Recurring Revenue (ARR) guarantees. As subscriptions transition to “cancel anytime” models, companies face new challenges with involuntary churn and customer retention. This article explores the implications and strategic shifts necessary to adapt to this evolving market.

This article explores the intertwined history of artificial intelligence and technology, highlighting the challenges and advancements from the symbolic paradigm to machine learning. Authors Arvind Narayanan and Sayash Kapoor critique the hype surrounding AI, stressing the importance of understanding its capabilities and limitations amidst commercial frenzy.

Notion's introduction of AI agents in its 3.0 update brings new capabilities for task automation and data management. However, it also exposes vulnerabilities, such as the potential for data exfiltration via malicious prompts, prompting important discussions on security implications in AI-driven SaaS platforms.

This study evaluates the privacy practices of 12 popular AI healthcare chatbots. The findings highlight significant gaps in user data protection, including inadequate privacy policies and limited control over personal information. Insights from this research aim to inform developers and policymakers to enhance privacy safeguards in chatbot applications.

Large language models are becoming common in businesses, but they pose risks of leaking sensitive data. This article argues for strict access control during model training and usage to prevent unauthorized data exposure, presenting a framework that enhances security for multi-user AI systems, as applied in Microsoft Copilot Tuning.

This article presents GCR-PPO, a novel method for improving multi-objective reinforcement learning in robotics. By addressing gradient conflicts among various task objectives, it enhances scalability and performance without significantly increasing computational costs, achieving notable improvements in complex tasks evaluated in standard benchmarks.

The MiMo-Audio-Tokenizer presents a unified approach to audio tokenization, enhancing both semantic extraction and high-fidelity audio reconstruction. With its transformer-based architecture, it efficiently processes audio and text, ensuring improved performance in cross-modal tasks.

RamTorch is a PyTorch library designed for memory-efficient deep learning, allowing large models to be trained and inferred even when they exceed GPU memory limits. It utilizes CPU-GPU hybrid components and intelligent data transfer strategies for optimal performance without compromising on efficiency.

This article introduces a lightweight bash script for querying AI models through the OpenRouter API. It offers features for command generation, code snippets, and quick answers, making it a versatile tool for developers and users wanting streamlined access to AI capabilities.

ScaleCUA represents a significant advancement in scaling open-source computer use agents for cross-platform applications. By offering a large-scale dataset covering six operating systems and three task domains, it enhances the capabilities of CUAs and achieves impressive performance benchmarks across various environments.

MCP Pointer is a local tool designed for seamless integration between browser DOM elements and AI coding tools. It features a Chrome Extension for easy element selection and an MCP server that relays detailed context, enhancing web development efficiency through real-time AI interaction.