Programming
Programming

Programming

Algorithms Artificial Intelligence Autonomous Underwater Vehicles (AUV) Lincoln Laboratory Programming Robotics Students Woods Hole

Featured video: Coding for underwater robotics

Lincoln Laboratory intern Ivy Mahncke developed and tested algorithms to help human divers and robots navigate underwater.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Programming Programming languages Research School of Engineering Software

Helping AI agents search to get the best results out of large language models

EnCompass executes AI agent programs by backtracking and making multiple attempts, finding the best set of outputs generated by an LLM. It could help coders work with AI agents more efficiently.

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MIT researchers propose a new model for legible, modular software

The coding framework uses modular concepts and simple synchronization rules to make software clearer, safer, and easier for LLMs to generate.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Programming Programming languages Research School of Engineering Software

Can AI really code? Study maps the roadblocks to autonomous software engineering

A team of researchers has mapped the challenges of AI in software development, and outlined a research agenda to move the field forward.

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Combining technology, education, and human connection to improve online learning

Caitlin Morris, a PhD student and 2024 MAD Fellow affiliated with the MIT Media Lab, designs digital learning platforms that make room for the “social magic” that influences curiosity and motivation.

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Making AI-generated code more accurate in any language

A new technique automatically guides an LLM toward outputs that adhere to the rules of whatever programming language or other format is being used.

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User-friendly system can help developers build more efficient simulations and AI models

By automatically generating code that leverages two types of data redundancy, the system saves bandwidth, memory, and computation.

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MIT launches new Music Technology and Computation Graduate Program

The program will invite students to investigate new vistas at the intersection of music, computing, and technology.

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

LLMs develop their own understanding of reality as their language abilities improve

In controlled experiments, MIT CSAIL researchers discover simulations of reality developing deep within LLMs, indicating an understanding of language beyond simple mimicry.

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“They can see themselves shaping the world they live in”

Developed by MIT RAISE, the Day of AI curriculum empowers K-12 students to collaborate on local and global challenges using AI.