Programming
Programming

Programming

Algorithms Artificial Intelligence Brain and cognitive sciences Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Defense Advanced Research Projects Agency (DARPA) Electrical Engineering & Computer Science (eecs) machine learning MIT Schwarzman College of Computing Programming Programming languages Research School of Engineering School of Science

MIT researchers introduce generative AI for databases

This new tool offers an easier way for people to analyze complex tabular data.

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Technique improves the reasoning capabilities of large language models

Combining natural language and programming, the method enables LLMs to solve numerical, analytical, and language-based tasks transparently.

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The power of App Inventor: Democratizing possibilities for mobile applications

More than a decade since its launch, App Inventor recently hosted its 100 millionth project and registered its 20 millionth user. Now hosted by MIT, the app also supports experimenting with AI.

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Creating bespoke programming languages for efficient visual AI systems

Associate Professor Jonathan Ragan-Kelley optimizes how computer graphics and images are processed for the hardware of today and tomorrow.

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Natural language boosts LLM performance in coding, planning, and robotics

Three neurosymbolic methods help language models find better abstractions within natural language, then use those representations to execute complex tasks.

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“We offer another place for knowledge”

After acquiring data science and AI skills from MIT, Jospin Hassan shared them with his community in the Dzaleka Refugee Camp in Malawi and built pathways for talented learners.

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Generating opportunities with generative AI

Rama Ramakrishnan helps companies explore the promises and perils of large language models and other transformative AI technologies.

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Armando Solar-Lezama named inaugural Distinguished College of Computing Professor

EECS professor appointed to new professorship in the MIT Schwarzman College of Computing.

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Probabilistic AI that knows how well it’s working

It’s more important than ever for artificial intelligence to estimate how accurately it is explaining data.

Algorithms Artificial Intelligence Brain and cognitive sciences Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Programming Quest for Intelligence Research School of Engineering School of Science Technology and society

Automating the math for decision-making under uncertainty

A new tool brings the benefits of AI programming to a much broader class of problems.