Tag: MIT-IBM Watson AI Lab

New method uses crowdsourced feedback to help train robots

To teach an AI agent a new task, like how to open a kitchen cabinet, researchers often use reinforcement learning — a trial-and-error process where the agent is rewarded for taking actions that get it closer to the goal. In many instances, a human expert must carefully design a reward function, which is an incentive […]

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Students pitch transformative ideas in generative AI at MIT Ignite competition

This semester, students and postdocs across MIT were invited to submit ideas for the first-ever MIT Ignite: Generative AI Entrepreneurship Competition. Over 100 teams submitted proposals for startups that utilize generative artificial intelligence technologies to develop solutions across a diverse range of disciplines including human health, climate change, education, and workforce dynamics. On Oct. 30, […]

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Technique enables AI on edge devices to keep learning over time

Personalized deep-learning models can enable artificial intelligence chatbots that adapt to understand a user’s accent or smart keyboards that continuously update to better predict the next word based on someone’s typing history. This customization requires constant fine-tuning of a machine-learning model with new data. Because smartphones and other edge devices lack the memory and computational […]

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New technique helps robots pack objects into a tight space

Anyone who has ever tried to pack a family-sized amount of luggage into a sedan-sized trunk knows this is a hard problem. Robots struggle with dense packing tasks, too. For the robot, solving the packing problem involves satisfying many constraints, such as stacking luggage so suitcases don’t topple out of the trunk, heavy objects aren’t […]

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A more effective experimental design for engineering a cell into a new state

A strategy for cellular reprogramming involves using targeted genetic interventions to engineer a cell into a new state. The technique holds great promise in immunotherapy, for instance, where researchers could reprogram a patient’s T-cells so they are more potent cancer killers. Someday, the approach could also help identify life-saving cancer treatments or regenerative therapies that […]

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AI models are powerful, but are they biologically plausible?

Artificial neural networks, ubiquitous machine-learning models that can be trained to complete many tasks, are so called because their architecture is inspired by the way biological neurons process information in the human brain. About six years ago, scientists discovered a new type of more powerful neural network model known as a transformer. These models can […]

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