It’s difficult to build devices that replicate the fluid, precise motion of humans, but that might change if we could pull a few (literal) strings.

This week CSAIL announced a gift from JPMorgan Chase that will enable important new breakthroughs in artificial intelligence research at MIT’s largest interdepartmental lab.

Many companies invest heavily in hiring talent to create the high-performance library code that underpins modern artificial intelligence systems. NVIDIA, for instance, developed some of the most advanced high-performance computing (HPC) libraries, creating a competitive moat that has proven difficult for others to breach.

Imagine that a robot is helping you clean the dishes. You ask it to grab a soapy bowl out of the sink, but its gripper slightly misses the mark.

A computation has two main constraints: the amount of memory a computation requires and how long it takes to do that calculation. If a task requires a certain number of steps, at worst the computer will need to access its memory for each one, meaning it'll require the same number of memory slots.

While early language models could only process text, contemporary large language models now perform highly diverse tasks on different types of data. For instance, LLMs can understand many languages, generate computer code, solve math problems, or answer questions about images and audio.

Proteins are the workhorses that keep our cells running, and there are many thousands of types of proteins in our cells, each performing a specialized function. Researchers have long known that the structure of a protein determines what it can do. 

This week the National Academy of Engineering (NAE) elected Tomás Lozano-Pérez, MIT School of Engineering Professor in Teaching Excellence and CSAIL principal investigator, as a member for his work in robot motion planning and molecular design.

During a meeting of class 6.C40/24.C40 (Ethics of Computing), Professor Armando Solar-Lezama poses the same impossible question to his students that he often asks himself in the research he leads with the Computer Assisted Programming Group at MIT:

Imagine you’re a chef with a highly sought-after recipe. You write your top-secret instructions in a journal to ensure you remember them, but its location within the book is evident from the folds and tears on the edges of that often-referenced page.