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Are you a CSAIL entrepreneur? Are you curious about the resources that CSAIL Alliances, as well as the rest of the MIT Ecosystem can offer you? Sign up for Office Hours using the form to ask Christiana Kalfas, Sr.

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alt="Language models may develop their own understanding of reality as a way to improve their generative abilities, indicating that the models may someday understand language at a deeper level than they do today (Credits: Alex Shipps/MIT CSAIL)."
CSAIL article

Ask a large language model (LLM) like GPT-4 to smell a rain-soaked campsite, and it’ll politely decline. Ask the same system to describe that scent to you, and it’ll wax poetic about “an air thick with anticipation" and “a scent that is both fresh and earthy," despite having neither prior experience with rain nor a nose to help it make such observations. 

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Three new frameworks from MIT CSAIL reveal how natural language can provide important context for language models that perform coding, AI planning, and robotics tasks (Credit: Alex Shipps/MIT CSAIL, with components from the researchers and Pixabay).
CSAIL article

Large language models (LLMs) are becoming increasingly useful for programming and robotics tasks, but for more complicated reasoning problems, the gap between these systems and humans looms large. Without the ability to learn new concepts like humans do, these systems fail to form good abstractions — essentially, high-level representations of complex concepts that skip less-important details — and thus sputter when asked to do more sophisticated tasks.

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To close the gap with classical computers, researchers created the quantum control machine — an instruction set for a quantum computer that works like the classical idea of a virtual machine (Credits: Alex Shipps/MIT CSAIL).
CSAIL article

When MIT professor and now Computer Science and Artificial Intelligence Laboratory (CSAIL) member Peter Shor first demonstrated the potential of quantum computers to solve problems faster than classical ones, he inspired scientists to imagine countless possibilities for the emerging technology. Thirty years later, though, the quantum edge remains a peak not yet reached.

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sloan fellos
CSAIL article

Three MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) members are among 126 early-career researchers honored with 2024 Sloan Research Fellowships by the Alfred P. Sloan Foundation. Representing the departments of Chemistry, Electrical Engineering and Computer Science, and Physics, and the MIT Sloan School of Management, the awardees will receive a two-year, $75,000 fellowship to advance their research.

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alt="MIT CSAIL's AI system melds simulations and physical testing to forge materials with newfound durability and flexibility for diverse engineering applications."
CSAIL article

Every time you smoothly drive from point A to point B, you're not just enjoying the convenience of your car, but also the sophisticated engineering that makes it safe and reliable. Beyond its comfort and protective features lies a lesser-known yet crucial aspect: the expertly optimized mechanical performance of microstructured materials. These materials, integral yet often unacknowledged, are what fortify your vehicle, ensuring durability and strength on every journey.