MIT scientists build a system that can generate AI models for biology research
BioAutoMATED, an open-source, automated machine-learning platform, aims to help democratize artificial intelligence for research labs.
Research
When computer vision works more like a brain, it sees more like people do
Training artificial neural networks with data from real brains can make computer vision more robust.
Researchers teach an AI to write better chart captions
A new dataset can help scientists develop automatic systems that generate richer, more descriptive captions for online charts.
Computer vision system marries image recognition and generation
MAGE merges the two key tasks of image generation and recognition, typically trained separately, into a single system.
MIT-Pillar AI Collective announces first seed grant recipients
Six teams conducting research in AI, data science, and machine learning receive funding for projects that have potential commercial applications.
A step toward safe and reliable autopilots for flying
A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.
Bringing the social and ethical responsibilities of computing to the forefront
The inaugural SERC Symposium convened experts from multiple disciplines to explore the challenges and opportunities that arise with the broad applicability of computing in many aspects of society.
New model offers a way to speed up drug discovery
By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds.
MIT researchers make language models scalable self-learners
The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.
Scaling audio-visual learning without labels
A new multimodal technique blends major self-supervised learning methods to learn more similarly to humans.