Artificial intelligence is opening new possibilities in biology, allowing researchers to design proteins with structures and functions that may not exist in nature. Yet turning these computational possibilities into useful medicines, industrial enzymes, and sustainable technologies requires enormous computing resources, advanced scientific models, and repeated experimental validation. A major computing grant to the University of Washington Medicine Institute for Protein Desig

Optical frequency combs have become one of the most important precision tools in modern photonics, enabling researchers to measure light frequencies with extraordinary accuracy and underpinning advances in atomic clocks, spectroscopy, telecommunications, sensing, and fundamental physics. Yet their exceptional performance has traditionally come with a practical constraint: sophisticated frequency-comb systems can be difficult to control, stabilize, and deploy outside specializ

Artificial intelligence is increasingly moving beyond cloud data centers and into cameras, drones, vehicles, industrial machines, aerospace systems, and other devices that must make decisions locally. This shift toward edge AI promises lower latency, greater privacy, reduced dependence on network connectivity, and potentially lower operating costs. Yet deploying sophisticated AI models onto specialized hardware remains one of the industry's most persistent engineering challen

Artificial intelligence has opened a new chapter in the study of historical cryptography, with advanced AI systems reportedly helping researchers solve two German Enigma messages that had resisted decryption for decades. The cases involve OpenAI's GPT-6 Astra and Anthropic's Claude Opus 5, but the significance extends beyond the recovery of two historical plaintexts. The experiments demonstrate how modern AI can combine archival investigation, programming, mathematical reason

Artificial intelligence is moving beyond the traditional boundaries of software development, data analysis and digital automation. One of its most consequential frontiers is biology, where AI systems can analyze enormous collections of genetic information, identify patterns that are difficult for humans to detect, generate hypotheses and help scientists decide which biological mechanisms deserve experimental investigation. Anthropic is now attempting to turn that potential in

Medical imaging is entering a new phase in which artificial intelligence is moving beyond narrowly defined disease detectors toward general-purpose systems capable of examining complex scans for multiple abnormalities at once. Alibaba’s DAMO Academy has taken a significant step in that direction with DAMO RADAR, an open-weight medical AI model designed to analyze contrast-enhanced abdominal CT scans and identify 146 clinical findings across 18 organs and anatomical structures

The artificial intelligence infrastructure race is entering a new phase. OpenAI and Anthropic have committed to enormous amounts of computing capacity, with projects measured in gigawatts and investments extending across multiple cloud and data center partners. Yet reports that both companies are exploring smaller data center deployments of roughly 20 to 30 megawatts reveal an important shift in how AI computing may be built and delivered. The move does not signal the end of

The rapid expansion of artificial intelligence is creating a new infrastructure challenge: computing capacity is increasingly constrained not only by chips, networks and capital, but by access to electricity. As AI workloads become larger and data centers grow into facilities capable of consuming enormous amounts of power, the traditional model of treating a data center as a fixed, continuously operating electricity customer is becoming harder to sustain. The challenge is par

Solid-state batteries are widely regarded as one of the most promising routes toward higher-energy, safer rechargeable energy storage. By replacing the flammable liquid electrolyte used in conventional lithium-ion cells with a solid ion-conducting material, the technology could enable lithium-metal anodes, thinner cell architectures, improved safety, and substantially greater energy density. Yet one fundamental problem continues to obstruct commercialization: lithium dendrite

OpenAI’s relationship with Samsung Electronics is moving beyond the conventional boundaries of an AI software partnership, placing semiconductors, memory technology, enterprise deployment, and large-scale computing infrastructure at the center of a rapidly expanding strategic relationship. Recent comments from OpenAI Korea suggested that joint research and production of next-generation chips had become one of the areas where the two companies had made significant progress. Op

The enterprise artificial intelligence market is entering a decisive stage. The central challenge is no longer simply building increasingly capable AI models. It is turning those models into reliable systems that employees can actually use, integrate into business processes, and scale across complex organizations. That transition is proving difficult. Companies have invested heavily in generative AI, yet moving from demonstrations and pilot projects to measurable business out

The artificial intelligence infrastructure market is entering a new phase in which the battle is no longer defined solely by access to the fastest general-purpose AI accelerators. Cloud providers increasingly want silicon designed around specific workloads, power constraints, networking requirements, and economic models. Qualcomm’s new long-term agreement with Amazon reflects this shift, bringing the chipmaker deeper into hyperscale data centers while giving Amazon another av

The idea of reversing biological aging has moved from speculative longevity research toward a more measurable scientific question: can an intervention make the molecular profile of human cells and tissues resemble that of younger individuals? A new clinical analysis involving rentosertib, an AI-designed drug candidate being developed for idiopathic pulmonary fibrosis (IPF), provides an intriguing early signal. Researchers analyzed blood-protein data from 42 participants in a

Weather forecasting is becoming an increasingly important proving ground for artificial intelligence. Unlike many AI applications, atmospheric prediction must operate within a system that is chaotic, highly interconnected, data-intensive, and constantly changing. A small error in the initial state of the atmosphere can grow rapidly, making accurate prediction especially difficult as the forecast horizon increases. Google’s WeatherNext 3 represents a significant step in the ev

Artificial intelligence is entering a new phase in which AI systems do more than answer questions. Agentic platforms can research information, interact with applications, analyze files, create documents, execute multi-step workflows, and continue working with limited human supervision. Yet this growing autonomy has exposed a fundamental problem: the most useful information is often the information organizations are least willing to send to a cloud-based AI system. Perplexity'

Industrial robotics has spent decades pursuing greater precision, speed, and autonomy. Yet one of the industry's most persistent problems has remained surprisingly simple: robots are often difficult to adapt once they leave the laboratory or arrive on a factory floor. A new generation of robotics companies is attempting to change that equation by placing human workers directly into the learning loop. Reimagine Robotics, founded by former Google DeepMind engineers and emerging

The economics of artificial intelligence are increasingly being shaped not only by how capable models become, but by how efficiently those models can be served to millions of users. Training remains enormously compute-intensive, but inference, the process of generating responses after a model has been trained, is becoming an equally important infrastructure challenge as AI assistants, autonomous agents, coding systems, and multimodal applications move into everyday use. OpenA

Apple’s latest silicon generation signals a significant shift in the company’s strategy for personal computing, moving beyond conventional processor upgrades toward a more deliberate architecture for artificial intelligence, local model execution, professional workloads, and energy-efficient computing. The introduction of the M6 and M5 Ultra brings two very different approaches to the same objective: increasing the amount of computational work users can perform locally. The M

The artificial intelligence boom is creating a new infrastructure bottleneck. The challenge is no longer simply obtaining advanced GPUs. Companies also need electricity, land, cooling systems, networking, buildings, grid connections, and enough physical capacity to deploy thousands of accelerators at scale. Nvidia increasingly appears to be positioning itself at the center of that entire equation. Reports that Nvidia is connecting companies seeking its GPUs with data center o

The race to build increasingly capable artificial intelligence systems is entering a new phase. Computing power remains central, but access to GPUs alone is no longer enough. The next generation of AI requires enormous quantities of electricity, specialized data centers, high-capacity networks, suitable land, cooling systems, transmission infrastructure, financing and long-term operational planning. The emerging PORTS-Pike Technology Campus in Pike County, Ohio, illustrates t