Machine learning

An illustration of real-world behavioral commonalities in raw data of transactions.

Inventing the “Google” for predictive analytics

Platform analyzes big data to answer plain-language business queries in minutes instead of months.

December 19, 2017

To solve complex problems, data scientists must shepherd their raw data through a series of steps, each one requiring many human-driven decisions. The last step in the process, deciding on a modeling technique, is particularly crucial.

Auto-tuning data science: New research streamlines machine learning

A new automated machine-learning system performs as well or better than its human counterparts — and works 100 times faster.

December 19, 2017

As part of an investigation into the nature of humans' physical intuitions, MIT researchers trained a neural network to predict how unstably stacked blocks would respond to the force of gravity.

Computer systems predict objects’ responses to physical forces

Results may help explain how humans do the same thing.

December 13, 2017

Neural nets are so named because they roughly approximate the structure of the human brain. Typically, they’re arranged into layers, and each layer consists of many simple processing units — nodes — each of which is connected to several nodes in the layers above and below. Data is fed into the lowest layer, whose nodes process it and pass it to the next layer. The connections between layers ...

Reading a neural network’s mind

Technique illuminates the inner workings of artificial-intelligence systems that process language.

December 10, 2017

To determine what products a given customer might like, recommendation systems at websites such as Amazon and Netflix look for other customers who have assigned similar ratings to a similar range of products, and extrapolate from there.

Try this! Researchers devise better recommendation algorithm

Improved recommendation algorithm should work especially well when ratings data are “sparse.”

December 6, 2017

Vivienne Sze and Joel Emer teach Hardware Architecture for Deep Learning, a class in MIT’s Department of Electrical Engineering and Computer Science that focuses on building specialized hardware for AI.

Building the hardware for the next generation of artificial intelligence

Class taught by Vivienne Sze and Joel Emer brings together traditionally separate disciplines for advances in deep learning.

November 30, 2017

A team of researchers at MIT, the University of Massachusetts at Amherst, and the University of California at Berkeley hope to close the materials-science automation gap, with a new artificial-intelligence system that would pore through research papers to deduce “recipes” for producing particular materials.

Artificial intelligence aids materials fabrication

System could pore through millions of research papers to extract “recipes” for producing materials.

November 5, 2017

A new MIT computer system speeds computations involving “sparse tensors,” multidimensional data arrays that consist mostly of zeroes.

Faster big-data analysis

System for performing “tensor algebra” offers 100-fold speedups over previous software packages.

October 30, 2017

“I think that the concept of massive and open data science can be really leveraged for areas where there’s a strong social impact but not necessarily a single profit-making or government organization that is coordinating responses,” MIT graduate student Micah Smith says about FeatureHub.

Crowdsourcing big-data analysis

Web-based system automatically evaluates proposals from far-flung data scientists.

October 30, 2017

MIT Plasma Science and Fusion Center principal research scientist Robert Granetz.

3 Questions: Robert Granetz on fusion research

MIT research scientist is exploring how machine learning can predict and prevent disruptions in reactors.

October 10, 2017

A new system from MIT's Computer Science and Artificial Intelligence Laboratory works by analyzing light at the edge of walls, which is impacted by the reflections of objects around the corner from the camera.

An algorithm for your blind spot

Using smartphone cameras, system for seeing around corners could help with self-driving cars and search-and-rescue.

October 9, 2017

A new machine-learning system analyzes successful repairs to buggy software and learns how to repair new bugs.

Bug-repair system learns from example

Automatic code-patching system corrects nearly twice as many errors as its predecessors.

September 28, 2017

New leadership for MIT-IBM Watson AI Lab

Computer vision and machine learning expert Antonio Torralba to lead new artificial intelligence research lab.

September 20, 2017

Identifying optimal product prices

New research describes a price-optimization method to increase online retailers’ revenue, market share, and profit.

September 18, 2017

Researchers will present a new general-purpose technique for making sense of neural networks trained to perform natural-language-processing tasks, in which computers attempt to interpret freeform texts written in ordinary, or natural language (as opposed to a programming language, for example).

How neural networks think

General-purpose technique sheds light on inner workings of neural nets trained to process language.

September 8, 2017

MIT News | Massachusetts Institute of Technology

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