Agentic AI Browsers are vulnerable to scams due to inconsistent security measures, allowing them to interact with phishing sites and malicious prompts without user awareness, leading to potential financial loss.
Google's Liquid Cooling
Google's liquid cooling system for datacenters leverages water's superior thermal conductivity, enhancing cooling efficiency for power-hungry TPUs amid the AI boom, with a design that spans racks rather than individual servers.
Nvidia's new 'robot brain' goes on sale for $3,499
Nvidia's Jetson AGX Thor chip, priced at $3,499, is designed to enhance robotics capabilities, enabling the creation of advanced robots and supporting generative AI models essential for humanoid functions.
IBM's Power11 Processor Architecture at Hot Chips 2025
IBM's Power11 architecture builds upon the successful Power10, emphasizing a system-focused approach with fewer, larger cores and enhanced AI integration, reflecting industry trends and client feedback.
How many paths of length K are there between A and B? (2021)
The problem of counting paths of length K from node A to node B in a directed graph can be solved efficiently using advanced techniques from coding theory and linear algebra, achieving a time complexity of O(EV + V log V log K), which is faster than traditional methods.
Take It for a Spin: NVIDIA Rolls Out DRIVE AGX Thor Developer Kit to World’s Automotive Developers
NVIDIA's DRIVE AGX Thor developer kit, powered by DriveOS 7, is designed to enhance the development of autonomous vehicles with advanced capabilities in reasoning, vision, and action models, making it a pivotal tool for automotive developers.
[D]GEPA: Reflective Prompt Evolution beats RL with 35× fewer rollouts
GEPA (Genetic-Pareto Prompt Evolution) achieves a 19% performance improvement over traditional reinforcement learning methods while requiring 35× fewer rollouts, showcasing a significant advancement in adapting compound LLM systems.
NVIDIA Jetson Thor Unlocks Real-Time Reasoning for General Robotics and Physical AI
NVIDIA Jetson Thor delivers 2,070 FP4 teraflops, significantly enhancing real-time reasoning capabilities for robotics, enabling complex applications like agentic AI and high-speed sensor processing.
CommonKV: Compressing KV Cache with Cross-layer Parameter Sharing
CommonKV introduces a training-free method for compressing KV caches in Large Language Models (LLMs) by leveraging Singular Value Decomposition (SVD) for adjacent parameter sharing, addressing memory challenges without the need for model architecture modifications.