Tag
#Algorithms
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Teaching AI models what they don’t know
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Teaching AI models the broad strokes to sketch more like humans do
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An anomaly detection framework anyone can use
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AI learns how vision and sound are connected, without human intervention
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Learning how to predict rare kinds of failures
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New tool evaluates progress in reinforcement learning
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Novel AI model inspired by neural dynamics from the brain
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Designing a new way to optimize complex coordinated systems
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“Periodic table of machine learning” could fuel AI discovery
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Making AI-generated code more accurate in any language
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A faster way to solve complex planning problems
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Training LLMs to self-detoxify their language
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New method efficiently safeguards sensitive AI training data
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Researchers teach LLMs to solve complex planning challenges
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Robotic helper making mistakes? Just nudge it in the right direction
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MIT spinout maps the body’s metabolites to uncover the hidden drivers of disease
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Like human brains, large language models reason about diverse data in a general way
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AI model deciphers the code in proteins that tells them where to go
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Puzzling out climate change
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Streamlining data collection for improved salmon population management
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3 Questions: Modeling adversarial intelligence to exploit AI’s security vulnerabilities
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New training approach could help AI agents perform better in uncertain conditions
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Expanding robot perception
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Explained: Generative AI’s environmental impact
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Teaching AI to communicate sounds like humans do
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Ecologists find computer vision models’ blind spots in retrieving wildlife images
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Teaching a robot its limits, to complete open-ended tasks safely
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AI in health should be regulated, but don’t forget about the algorithms, researchers say
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Daniela Rus wins John Scott Award
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Citation tool offers a new approach to trustworthy AI-generated content
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A new way to create realistic 3D shapes using generative AI
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MIT researchers develop an efficient way to train more reliable AI agents
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Advancing urban tree monitoring with AI-powered digital twins
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3 Questions: Inverting the problem of design
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A causal theory for studying the cause-and-effect relationships of genes
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How AI is improving simulations with smarter sampling techniques
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AI pareidolia: Can machines spot faces in inanimate objects?
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Helping robots zero in on the objects that matter
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3 Questions: Should we label AI systems like we do prescription drugs?
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Accelerating particle size distribution estimation
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Study: AI could lead to inconsistent outcomes in home surveillance
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Enhancing LLM collaboration for smarter, more efficient solutions
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A fast and flexible approach to help doctors annotate medical scans
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A framework for solving parabolic partial differential equations
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New open-source tool helps to detangle the brain
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Helping robots practice skills independently to adapt to unfamiliar environments
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Precision home robots learn with real-to-sim-to-real
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Method prevents an AI model from being overconfident about wrong answers
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Study: When allocating scarce resources with AI, randomization can improve fairness
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MIT researchers advance automated interpretability in AI models
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Creating and verifying stable AI-controlled systems in a rigorous and flexible way
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How to assess a general-purpose AI model’s reliability before it’s deployed
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Reasoning skills of large language models are often overestimated
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MIT researchers introduce generative AI for databases
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Helping nonexperts build advanced generative AI models
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A smarter way to streamline drug discovery
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New algorithm discovers language just by watching videos
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New computer vision method helps speed up screening of electronic materials
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Using ideas from game theory to improve the reliability of language models
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A better way to control shape-shifting soft robots