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MIT News - Machine learning
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Showing 51-100 of 149 entries
MIT Sea Grant works with the Woodwell Climate Research Center and other collaborators to demonstrate a deep learning-based system for fish monitoring.
By moving their hands and fingers, users can direct a robot to play piano or shoot a basketball, or they can manipulate objects in a virtual environment.
With this new technique, a robot could more accurately detect hidden objects or understand an indoor scene using reflected Wi-Fi signals.
This new metric for measuring uncertainty could flag hallucinations and help users know whether to trust an AI model.
Academia-industry relationship is an early-stage accelerator, supporting professional progress and research.
Researchers at MIT, Mass General Brigham, and Harvard Medical School developed a deep-learning model to forecast a patient’s heart failure prognosis up to a year in advance.
Professor Jesse Thaler describes a vision for a two-way bridge between artificial intelligence and the mathematical and physical sciences — one that promises to advance both.
A new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.
Assistant Professor Matthew Jones is working to decode molecular processes on the genetic, epigenetic, and microenvironment levels to anticipate how and when tumors evolve to resist treatment.
From early motion-sensing platforms to environmental monitoring, the professor and head of the Program in Media Arts and Sciences has turned decades of cross-disciplinary research into real-world impact.
New work suggests the brain can deliver neuron-specific feedback during learning — resembling the error signals that drive machine learning.
A new approach could help users know whether to trust a model’s predictions in safety-critical applications like health care and autonomous driving.
The approach could help engineers tackle extremely complex design problems, from power grid optimization to vehicle design.
By leveraging idle computing time, researchers can double the speed of model training while preserving accuracy.
By providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.
Research from the MIT Center for Constructive Communication finds leading AI models perform worse for users with lower English proficiency, less formal education, and non-US origins.
A new method developed at MIT could root out vulnerabilities and improve LLM safety and performance.
By minimizing the need to drive around looking for a parking spot, this technique can save drivers up to 35 minutes — and give them a realistic estimate of total travel time.
The context of long-term conversations can cause an LLM to begin mirroring the user’s viewpoints, possibly reducing accuracy or creating a virtual echo-chamber.
Associate Professor Rafael Gómez-Bombarelli has spent his career applying AI to improve scientific discovery. Now he believes we are at an inflection point.
Removing just a tiny fraction of the crowdsourced data that informs online ranking platforms can significantly change the results.
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.
MIT researchers’ DiffSyn model offers recipes for synthesizing new materials, enabling faster experimentation and a shorter journey from hypothesis to use.
As AI technology advances, a new interdisciplinary course seeks to equip students with foundational critical thinking skills in computing.
New “biomimetic” model of brain circuits and function at multiple scales produced naturalistic dynamics and learning, and even identified curious behavior by some neurons.
New research detects hidden evidence of mistaken correlations — and provides a method to improve accuracy.
“MechStyle” allows users to personalize 3D models, while ensuring they’re physically viable after fabrication, producing unique personal items and assistive technology.
While the growing energy demands of AI are worrying, some techniques can also help make power grids cleaner and more efficient.
With the help of AI, MIT Research Scientist Judah Cohen is reshaping subseasonal forecasting, with the goal of extending the lead time for predicting impactful weather.
New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
CSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.
MIT-IBM Watson AI Lab researchers developed an expressive architecture that provides better state tracking and sequential reasoning in LLMs over long texts.
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
16 Dec
An AI-driven system lets users design and build simple, multicomponent objects by describing them with words.
Assistant Professor Yunha Hwang utilizes microbial genomes to examine the language of biology. Her appointment reflects MIT’s commitment to exploring the intersection of genetics research and AI.
The approach could apply to more complex tissues and organs, helping researchers to identify early signs of disease.
The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting.
The technique can help scientists in economics, public health, and other fields understand whether to trust the results of their experiments.
Founded by MIT alumni, the Pickle Robot Company has developed machines that can autonomously load and unload trucks inside warehouses and logistic centers.
This new technique enables LLMs to dynamically adjust the amount of computation they use for reasoning, based on the difficulty of the question.
With insect-like speed and agility, the tiny robot could someday aid in search-and-rescue missions.
MIT CSAIL and LIDS researchers developed a mathematically grounded system that lets soft robots deform, adapt, and interact with people and objects, without violating safety limits.
1 Dec
AquaCulture Shock program, in collaboration with MIT-Scandinavia MISTI, offers international internships for AI and autonomy in aquaculture
Large language models can learn to mistakenly link certain sentence patterns with specific topics — and may then repeat these patterns instead of reasoning.
MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases
25 Nov
BoltzGen generates protein binders for any biological target from scratch, expanding AI’s reach from understanding biology toward engineering it.
AI supports the clean energy transition as it manages power grid operations, helps plan infrastructure investments, guides development of novel materials, and more.
19 Nov
MIT neuroscientists find a surprising parallel in the ways humans and new AI models solve complex problems.
Quantum chemist and School of Science Dean’s Postdoctoral Fellow Ernest Opoku is working on computational methods to study how electrons behave.
The virtual VideoCAD tool could boost designers’ productivity and help train engineers learning computer-aided design.
Associate Professor Phillip Isola studies the ways in which intelligent machines “think,” in an effort to safely integrate AI into human society.