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AI system learns from many types of scientific information and runs experiments to discover new materials

Artificial Intelligence, DMSE, Energy, Machine Learning, Materials science and engineering, MIT.nano, Nanoscience and nanotechnology, Nuclear science and engineering, Research, School of Engineering

Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables. Compare that with human scientists, who work in a collaborative environment and consider experimental results, the broader scientific literature, imaging and structural analysis, personal experience […]

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Responding to the climate impact of generative AI

Algorithms, Artificial Intelligence, Climate change, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Emissions, Energy, Energy storage, infrastructure, Lincoln Laboratory, Machine Learning, MIT Energy Initiative, MIT Schwarzman College of Computing, MIT Sloan School of Management, Research, School of Engineering, Supercomputing, Sustainable computing

In part 2 of our two-part series on generative artificial intelligence’s environmental impacts, MIT News explores some of the ways experts are working to reduce the technology’s carbon footprint.The energy demands of generative AI are expected to continue increasing dramatically over the next decade.For instance, an April 2025 report from the International Energy Agency predicts that the global

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Lincoln Lab unveils the most powerful AI supercomputer at any US university

Artificial Intelligence, cybersecurity, Department of Defense (DoD), Energy, Haystack Observatory, Human-computer interaction, Lincoln Laboratory, Supercomputing

The new TX-Generative AI Next (TX-GAIN) computing system at the Lincoln Laboratory Supercomputing Center  (LLSC) is the most powerful AI supercomputer at any U.S. university. With its recent ranking from  TOP500, which biannually publishes a list of the top supercomputers in various categories, TX-GAIN joins the ranks of other powerful systems at the LLSC, all supporting

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Martin Trust Center for MIT Entrepreneurship welcomes Ana Bakshi as new executive director

Artificial Intelligence, Business and management, Innovation and Entrepreneurship (I&E), Leadership, Martin Trust Center for MIT Entrepreneurship, MIT Sloan School of Management, Staff, Startups

The Martin Trust Center for MIT Entrepreneurship announced that Ana Bakshi has been named its new executive director. Bakshi started in the role earlier this month at the start of the school year and will collaborate closely with the managing director, Ethernet Inventors Professor of the Practice Bill Aulet, to elevate the center to higher levels.“Ana

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Getting Started with Langfuse [2026 Guide]

Artificial Intelligence, Guide, LLMs

The creation and deployment of applications that utilize Large Language Models (LLMs) comes with their own set of problems. LLMs have non-deterministic nature, can generate plausible but false information and tracing their actions in convoluted sequences can be very troublesome. In this guide, we’ll see how Langfuse comes up as an essential instrument for solving these problems, by offering a strong foundation for

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GPU vs TPU: What’s the Difference?

Artificial Intelligence, Machine Learning

AI and machine learning have pushed the demand for high-performance hardware, making the GPU-versus-TPU discussion more relevant than ever. GPUs, originally built for graphics, have grown into flexible processors for data analysis, scientific computing, and modern AI workloads. TPUs, built by Google as specialized ASICs for deep learning, focus on high-throughput tensor operations and have

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7 Latest AI Drops by Google Will Make You a Powerhouse at Work

Artificial Intelligence, Beginner, GenAI Tools, Generative AI

Google has just dropped its biggest wave of AI updates in months. The best part – each one rewires how we get things done. And to add to that, this range of AI tools and features span across generating content, solving problems, and even getting multi-step, complicated tasks done by the power of AI. From

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Deep Agents Tutorial: Create Advanced AI Agents with LangGraph and Web Search Tools 

Artificial Intelligence, Beginner, Generative AI, LLMs

Imagine an AI that doesn’t just answer your questions, but thinks ahead, breaks tasks down, creates its own TODOs, and even spawns sub-agents to get the work done. That’s the promise of Deep Agents. AI Agents already take the capabilities of LLMs a notch higher, and today we’ll look at Deep Agents to see how

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