Posted by Ikechukwu Uchendu, AI Resident and Ted Xiao, Software Engineer, Robotics at Google Reinforcement learning (RL) can be used to train a policy to perform a task via trial and error, but a major challenge in RL is learning policies from scratch in environments with hard exploration challenges. For example, consider the setting depicted…
The human brain seems to care a lot about faces. It’s dedicated a specific area to identifying them, and the neurons there are so good at their job that most of us can readily recognize thousands of individuals. With artificial intelligence, computers can now recognize faces with a similar efficiency — and neuroscientists at MIT’s…
When OpenAI revealed its picture-making neural network DALL-E in early 2021, the program’s human-like ability to combine different concepts in new ways was striking. The string of images that DALL-E produced on demand were surreal and cartoonish, but they showed that the AI had learned key lessons about how the world fits together. DALL-E’s avocado…
In machine learning, understanding why a model makes certain decisions is often just as important as whether those decisions are correct. For instance, a machine-learning model might correctly predict that a skin lesion is cancerous, but it could have done so using an unrelated blip on a clinical photo. While tools exist to help experts…
Robots are already adept at certain things, such as lifting objects that are too heavy or cumbersome for people to manage. Another application they’re well suited for is the precision assembly of items like watches that have large numbers of tiny parts — some so small they can barely be seen with the naked eye….
Posted by Gil Shamir and Dong Lin, Research Software Engineers, Google Research Ever queried a recommender system and found that the same search only a few moments later or on a different device yields very different results? This is not uncommon and can be frustrating if a person is looking for something specific. As a…
Thomas Tull, leading visionary entrepreneur and investor, has been appointed a School of Engineering visiting innovation scholar, effective April 1. Throughout his career, Tull has leveraged the power of technology, artificial intelligence, and data science to disrupt and revolutionize disparate industries. Today, as the founder, chair, and CEO of Tulco LLC, a privately held holding…
Posted by Sharan Narang and Aakanksha Chowdhery, Software Engineers, Google Research In recent years, large neural networks trained for language understanding and generation have achieved impressive results across a wide range of tasks. GPT-3 first showed that large language models (LLMs) can be used for few-shot learning and can achieve impressive results without large-scale task-specific…
What does it mean to be human in an age where artificial intelligence agents make decisions that shape human actions? That’s a deep question with no easy answers, and it’s been on the mind of Dan Huttenlocher SM ’84, PhD ’88, dean of the MIT Schwarzman College of Computing, for the past few years. “Advances…
Chemical engineers and materials scientists are constantly looking for the next revolutionary material, chemical, and drug. The rise of machine-learning approaches is expediting the discovery process, which could otherwise take years. “Ideally, the goal is to train a machine-learning model on a few existing chemical samples and then allow it to produce as many manufacturable…