Tag
#Electrical engineering and computer science (EECS)
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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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With AI, researchers predict the location of virtually any protein within a human cell
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Study shows vision-language models can’t handle queries with negation words
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Hybrid AI model crafts smooth, high-quality videos in seconds
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Novel AI model inspired by neural dynamics from the brain
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Making AI models more trustworthy for high-stakes settings
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The MIT-Portugal Program enters Phase 4
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Merging design and computer science in creative ways
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Novel method detects microbial contamination in cell cultures
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“Periodic table of machine learning” could fuel AI discovery
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3D modeling you can feel
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MIT’s McGovern Institute is shaping brain science and improving human lives on a global scale
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Making AI-generated code more accurate in any language
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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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Could LLMs help design our next medicines and materials?
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New method assesses and improves the reliability of radiologists’ diagnostic reports
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For this computer scientist, MIT Open Learning was the start of a life-changing journey
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AI tool generates high-quality images faster than state-of-the-art approaches
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Robotic helper making mistakes? Just nudge it in the right direction
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Collaborating to advance research and innovation on essential chips for AI
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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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Creating a common language
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Validation technique could help scientists make more accurate forecasts
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Streamlining data collection for improved salmon population management
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User-friendly system can help developers build more efficient simulations and AI models
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3 Questions: Modeling adversarial intelligence to exploit AI’s security vulnerabilities
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Toward video generative models of the molecular world
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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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A new computational model can predict antibody structures more accurately
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Ecologists find computer vision models’ blind spots in retrieving wildlife images
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MIT researchers introduce Boltz-1, a fully open-source model for predicting biomolecular structures
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Lara Ozkan named 2025 Marshall Scholar
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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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Researchers reduce bias in AI models while preserving or improving accuracy
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Enabling AI to explain its predictions in plain language
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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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MIT delegation mainstreams biodiversity conservation at the UN Biodiversity Convention, COP16
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A new way to create realistic 3D shapes using generative AI
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Photonic processor could enable ultrafast AI computations with extreme energy efficiency
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Improving health, one machine learning system at a time
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Advancing urban tree monitoring with AI-powered digital twins
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Can robots learn from machine dreams?
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A causal theory for studying the cause-and-effect relationships of genes
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A portable light system that can digitize everyday objects
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Nanoscale transistors could enable more efficient electronics
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A faster, better way to train general-purpose robots
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Making it easier to verify an AI model’s responses
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Combining next-token prediction and video diffusion in computer vision and robotics
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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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New security protocol shields data from attackers during cloud-based computation
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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