MIT Computer Science

• Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event

  Presentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.

• Memory safety is at a tipping point

  Lincoln Laboratory cybersecurity expert Hamed Okhravi calls for a unified approach to securing computer memory, as a matter of national security.

• Unpacking the bias of large language models

  In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.

• A sounding board for strengthening the student experience

  Composed of “computing bilinguals,” the Undergraduate Advisory Group provides vital input to help advance the mission of the MIT Schwarzman College of Computing.

• This compact, low-power receiver could give a boost to 5G smart devices

  Researchers designed a tiny receiver chip that is more resilient to interference, which could enable smaller 5G “internet of things” devices with longer battery lives.

• Gaspare LoDuca named VP for information systems and technology and CIO

  Chief information officer at Columbia University will join MIT in August.

• Closing in on superconducting semiconductors

  Plasma Science and Fusion Center researchers created a superconducting circuit that could one day replace semiconductor components in quantum and high-performance computing systems.

• Photonic processor could streamline 6G wireless signal processing

  By performing deep learning at the speed of light, this chip could give edge devices new capabilities for real-time data analysis.

• Inroads to personalized AI trip planning

  A new framework from the MIT-IBM Watson AI Lab supercharges language models, so they can reason over, interactively develop, and verify valid, complex travel agendas.

• Melding data, systems, and society

  A new book from Professor Munther Dahleh details the creation of a unique kind of transdisciplinary center, uniting many specialties through a common need for data science.

• How we really judge AI

  Forget optimists vs. Luddites. Most people evaluate AI based on its perceived capability and their need for personalization.

• AI-enabled control system helps autonomous drones stay on target in uncertain environments

  The system automatically learns to adapt to unknown disturbances such as gusting winds.

• Envisioning a future where health care tech leaves some behind

  The winning essay of the Envisioning the Future of Computing Prize puts health care disparities at the forefront.

• Helping machines understand visual content with AI

  Coactive, founded by two MIT alumni, has built an AI-powered platform to unlock new insights from content of all types.

• Animation technique simulates the motion of squishy objects

  The approach could help animators to create realistic 3D characters or engineers to design elastic products.

• New system enables robots to solve manipulation problems in seconds

  Researchers developed an algorithm that lets a robot “think ahead” and consider thousands of potential motion plans simultaneously.

• Teaching AI models what they don’t know

  A team of MIT researchers founded Themis AI to quantify AI model uncertainty and address knowledge gaps.

• Teaching AI models the broad strokes to sketch more like humans do

  SketchAgent, a drawing system developed by MIT CSAIL researchers, sketches up concepts stroke-by-stroke, teaching language models to visually express concepts on their own and collaborate with humans.

• An anomaly detection framework anyone can use

  PhD student Sarah Alnegheimish wants to make machine learning systems accessible.

• AI learns how vision and sound are connected, without human intervention

  This new machine-learning model can match corresponding audio and visual data, which could someday help robots interact in the real world.

• Learning how to predict rare kinds of failures

  Researchers are developing algorithms to predict failures when automation meets the real world in areas like air traffic scheduling or autonomous vehicles.

• Scientists discover potential new targets for Alzheimer’s drugs

  Pathways involved in DNA repair and other cellular functions could contribute to the development of Alzheimer’s.

• The sweet taste of a new idea

  Sendhil Mullainathan brings a lifetime of unique perspectives to research in behavioral economics and machine learning.

• With AI, researchers predict the location of virtually any protein within a human cell

  Trained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.

• Study shows vision-language models can’t handle queries with negation words

  Words like “no” and “not” can cause this popular class of AI models to fail unexpectedly in high-stakes settings, such as medical diagnosis.

• System lets robots identify an object’s properties through handling

  With a novel simulation method, robots can guess the weight, softness, and other physical properties of an object just by picking it up.

• Hybrid AI model crafts smooth, high-quality videos in seconds

  The CausVid generative AI tool uses a diffusion model to teach an autoregressive (frame-by-frame) system to rapidly produce stable, high-resolution videos.

• New tool evaluates progress in reinforcement learning

  “IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.

• Novel AI model inspired by neural dynamics from the brain

  New type of “state-space model” leverages principles of harmonic oscillators.

• Making AI models more trustworthy for high-stakes settings

  A new method helps convey uncertainty more precisely, which could give researchers and medical clinicians better information to make decisions.