What does the future hold for generative AI?
Rodney Brooks, co-founder of iRobot, kicks off an MIT symposium on the promise and potential pitfalls of increasingly powerful AI tools like ChatGPT.
Machine learning
New method uses crowdsourced feedback to help train robots
Human Guided Exploration (HuGE) enables AI agents to learn quickly with some help from humans, even if the humans make mistakes.
Optimizing costs for Amazon SageMaker Canvas with automatic shutdown of idle apps | Amazon Web Services
Amazon SageMaker Canvas is a rich, no-code Machine Learning (ML) and Generative AI workspace that has allowed customers all over the world to more easily adopt ML technologies to solve…
Synthetic imagery sets new bar in AI training efficiency
MIT CSAIL researchers innovate with synthetic imagery to train AI, paving the way for more efficient and bias-reduced machine learning.
Technique enables AI on edge devices to keep learning over time
With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.
This 3D printer can watch itself fabricate objects
Computer vision enables contact-free 3D printing, letting engineers print with high-performance materials they couldn’t use before.
Explained: Generative AI
How do powerful generative AI systems like ChatGPT work, and what makes them different from other types of artificial intelligence?
Using AI to optimize for rapid neural imaging
MIT CSAIL researchers combine AI and electron microscopy to expedite detailed brain network mapping, aiming to enhance connectomics research and clinical pathology.
2023-24 Takeda Fellows: Advancing research at the intersection of AI and health
Thirteen new graduate student fellows will pursue exciting new paths of knowledge and discovery.
Generating opportunities with generative AI
Rama Ramakrishnan helps companies explore the promises and perils of large language models and other transformative AI technologies.