Page 5 - Mit Csail News Today

Passionate about creating educational opportunities in India, MIT PhD student Siddhartha Jayanti recently explored multiprocessor speed limits, in a paper written in the Indian language Telugu.

Researchers from MIT CSAIL predict semantically meaningful and calibrated uncertainty intervals in the latent space of a generative adversarial network to know the exact limits in our ability to clean up, and reconstruct, partly blurred images.

Sybil is a new artificial intelligence tool that can detect lung cancer up to six years in advance. MIT and Mass General Cancer Center researchers designed an AI tool, called

A new study by researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and the MIT Jameel Clinic assesses the impact that discriminatory AI models can have, especially for systems that are intended to provide advice in urgent situations.

Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) came up with an algorithm to automatically assemble products that’s accurate, efficient, and can generalize to a wide range of complex real-world assemblies.

Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) used a GPT-3 large language style model to extract important data from electronic health records to decipher clinical notes and enable better personalized care.

A machine-learning technique called SALIENT addresses key bottlenecks in computation with graph neural networks by optimizing usage of the hardware, particularly GPUs. This upgrade significantly reduces training and inference time on extensive datasets to keep pace with fast-moving and growing data in finance, social networks, and fraud detection in cryptocurrency.

Researchers from the MIT CSAIL have discovered a quicker way to solve an equation used in the algorithms for ‘liquid’ neural neurons.

MIT researchers solved a differential equation behind the interaction of two neurons through synapses to unlock a new type of speedy and efficient artificial intelligence algorithms.

A new algorithm makes headway in solving the problem of exploration vs. exploitation in reinforcement learning. Developed by MIT CSAIL researchers, it attempts to make decision-making more efficient.