Robotics

MIT Creates New Framework to Test Ethical AI and Autonomous Systems Researchers at MIT have created a new testing framework to assess whether recommendations from autonomous systems align with human-defined ethical principles. As AI is increasingly used for decision-making in critical areas like power grid management, ensuring these systems operate with fairness and equity for all individuals and communities is paramount. The framework is designed to pinpoint specific situations where an AI decision-support system may be exhibiting unfair treatment. This development addresses the growing need for robust methods to evaluate the ethical implications and ensure the responsible deployment of autonomous systems in high-stakes environments. ...

Pentagon Greenlights AI Model Training on Classified Data The Pentagon is moving forward with a plan to allow technology companies to train their artificial intelligence models on classified data. This initiative represents a significant step in advancing the U.S.’s defense technology capabilities. The strategy aims to accelerate AI development for national security purposes while navigating the complex challenges of juggling innovation with the protection of sensitive information. This move highlights the increasing integration of AI into critical defense infrastructure and the need for robust, adaptive cybersecurity measures to safeguard against potential risks. ...

This week in technology, major partnerships are reshaping autonomous transport, NVIDIA is pushing the boundaries of physical AI, and new platforms are emerging for custom enterprise AI. We also cover key developments in Kubernetes optimization, quantum computing milestones, and a significant acquisition in the open-source community. Here’s what you need to know. Uber and Rivian Partner for 50,000-Vehicle Autonomous Robotaxi Fleet In a landmark partnership set to reshape urban mobility, Uber and Rivian have announced a collaboration to launch a massive fleet of up to 50,000 fully autonomous R2 robotaxis. This initiative aims to accelerate the autonomous vehicle roadmaps for both companies, starting with an initial deployment of 10,000 vehicles. The first robotaxis are scheduled to launch in San Francisco and Miami in 2028, with an ambitious expansion plan targeting 25 cities by 2031. To support this, Uber will invest up to $1.25 billion in Rivian through 2031, contingent on achieving specific performance milestones. The Rivian R2 robotaxis will be available exclusively on the Uber platform. ...

Northwestern’s Evolving Robots Showcase ‘Athletic Intelligence’ and Self-Repair Researchers at Northwestern Engineering have pioneered a new class of modular robots, dubbed “legged metamachines,” that exhibit athletic intelligence and can dynamically adapt to their environment. These robots are built from autonomous, LEGO-like modules, allowing for assembly into numerous configurations. A standout feature is their remarkable ability to recover from damage; for example, if a leg breaks, the remaining parts can continue to function and reconfigure for mobility. The designs were optimized using an AI-driven evolutionary algorithm that simulated natural selection to identify the most efficient and versatile body types for movement. According to the researchers, these are the first robots to be evolved within a computer and then successfully deployed in a real-world outdoor environment. ...

5 Key AI Automation Trends Defining Business for the Next 5 Years Artificial intelligence is becoming essential to daily business operations, with several key trends in AI automation set to define the next five years. A major trend is the shift towards autonomous decision-making systems, where AI manages routine operational choices in areas like retail pricing and financial fraud detection. Another significant development is hyperautomation, which integrates AI with other technologies to automate entire business processes. Intelligent customer experience automation is also advancing, utilizing conversational chatbots and personalized recommendations. The most successful businesses are expected to build collaborative models where humans supervise AI outputs, ensuring both efficiency and accountability. ...

FBI Doubles Down on AI for Investigations and Operations The Federal Bureau of Investigation (FBI) is significantly expanding its use of artificial intelligence in key areas, including criminal investigations, intelligence analysis, and internal operations. According to the Department of Justice’s (DOJ) latest public inventory, the number of AI use cases reported by the FBI has more than doubled to 50. These AI applications encompass machine learning, computer vision, and generative AI, primarily aimed at labor-saving tasks like translation, transcription, and summarization. The 2025 DOJ AI Use Case Inventory reveals a sharp increase in the FBI’s AI tools for law enforcement, jumping from 15 to 27 in just one year, reflecting a broader 30.7% increase in AI adoption across the entire DOJ. ...

UK Announces £1.6 Billion National AI Strategy to Boost Research and Innovation The UK’s primary public research funder, UK Research and Innovation (UKRI), has launched its first national strategy to integrate artificial intelligence into the nation’s science and research sectors. This landmark initiative is backed by a record £1.6 billion in funding for the AI sector, allocated between now and 2030. The strategy is designed to leverage AI for driving innovations across diverse fields, including healthcare, public services, and clean energy. The investment will concentrate on six key areas: advancing AI technology, developing skills and talent, and promoting responsible and trustworthy AI. UKRI-funded AI projects are already demonstrating significant impact, such as a system for detecting faults on the railway network and another that aids in analyzing brain scans for diseases like Alzheimer’s. ...

AI Hardware Crisis: Data Centers Buy Out Western Digital’s 2026 Hard Drive Supply The insatiable demand for AI hardware is causing a significant supply chain crisis. Reports confirm that AI data centers have pre-purchased Western Digital’s entire hard drive production capacity for 2026. This hardware crunch extends beyond storage, with Phison’s CEO warning of an imminent “AI memory crisis” that could bankrupt some consumer electronics companies. The massive storage and memory requirements for training and deploying large-scale AI models are diverting critical components from the enterprise and consumer markets, establishing AI development as the primary driver of the global hardware industry. ...

ZKBoost Protocol Unveiled for Private, Verifiable XGBoost AI Model Training Researchers have introduced ZKBoost, a groundbreaking cryptographic protocol designed to verify XGBoost machine learning model training on sensitive datasets without revealing the underlying data or model parameters. ZKBoost is the first zero-knowledge proof of training (zkPoT) protocol specifically developed for XGBoost, a widely-used algorithm for tabular data. This innovation addresses the critical need for cryptographic guarantees of model integrity in high-stakes applications. The system employs a fixed-point implementation of XGBoost compatible with arithmetic circuits, enabling efficient zero-knowledge proofs. Research indicates this implementation maintains accuracy within 1% of the standard XGBoost, making practical verification on real-world data a reality. ...

OpenAI Unveils Groundbreaking Multimodal AI with Advanced Reasoning OpenAI has revealed a significant advancement in multimodal artificial intelligence with its latest model. This new model can seamlessly process and understand a combination of text, images, audio, and video simultaneously. The key differentiator is its ability to forge logical connections across these diverse data types, achieving a more human-like understanding. Early benchmarks demonstrate a remarkable 40% improvement in multi-step reasoning tasks compared to previous models, showcasing its enhanced capabilities in complex problem-solving. ...