Someday, you may want your home robot to carry a load of dirty clothes downstairs and deposit them in the washing machine in the far-left corner of the basement. The robot will need to combine your instructions with its visual observations to determine the steps it should take to complete this task.

Mark Hamilton, an MIT PhD student in electrical engineering and computer science and affiliate of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), wants to use machines to understand how animals communicate. To do that, he set out first to create a system that can learn human language “from scratch.”

When robots come across unfamiliar objects, they struggle to account for a simple truth: Appearances aren’t everything. They may attempt to grasp a block, only to find out it’s a literal piece of cake. The misleading appearance of that object could lead the robot to miscalculate physical properties like the object’s weight and center of mass, using the wrong grasp and applying more force than needed.

In sports training, practice is the key, but being able to emulate the techniques of professional athletes can take a player’s performance to the next level. AI-based personalized sports coaching assistants assist with this by utilizing published datasets. With cameras and sensors strategically placed on the athlete's body, these systems can track everything, including joint movement patterns, muscle activation levels, and gaze movements.

Let’s say you want to train a robot so it understands how to use tools and can then quickly learn to make repairs around your house with a hammer, wrench, and screwdriver. To do that, you would need an enormous amount of data demonstrating tool use.

The internet is awash in instructional videos that can teach curious viewers everything from cooking the perfect pancake to performing a life-saving Heimlich maneuver.

When you’re trying to understand which diseases or physical traits you’re predisposed to, the answers are sprinkled across your DNA. One powerful method for decoding this genetic forecast is polygenic scores, which give patients estimates of their risk for a condition and the likelihood of having physical characteristics (phenotypes, like being tall). Researchers seek to improve the accuracy of these cumulative predictions to account for most of the known genetic contributions.

Researchers from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and Google Research may have just performed digital sorcery — in the form of a diffusion model that can change the material properties of objects in images.

Your heart is a tireless organ that beats about 3 billion times over an average lifetime and is simply essential for life. Unsurprisingly, cardiovascular disease is the leading cause of death worldwide, costing millions of lives each year. This relentless condition primarily damages the heart, which is divided into four main chambers: the right atrium, left atrium, right ventricle, and left ventricle. Understanding the functions and vulnerabilities of these chambers is crucial in the fight against heart disease.

“I'll have you eating out of the palm of my hand” is an unlikely utterance you'll hear from a robot. Why? Most of them don't have palms.