Not sure what to think about DeepSeek R1, the most recent large language model (LLM) making waves in the global tech community? Faculty from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are here to help!

"The net effect [of DeepSeek] should be to significantly increase the pace of AI development, since the secrets are being let out and the models are now cheaper and easier to train by more people." ~ Associate Professor Phillip Isola

Daniela Rus, a distinguished computer scientist and professor at the Massachusetts Institute of Technology (MIT), has been honored with induction into the prestigious Académie Nationale de Médecine (ANM) as a foreign member on January 7, 2025. As the Director of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), Daniela leads over 1,700 researchers in pioneering innovations to advance computing and improve global well-being.

If someone advises you to “Know your limits,” they’re likely suggesting you do things like exercise in moderation. To a robot, though, the motto represents learning constraints, or limitations of a specific task within the machine’s environment, to do chores safely and correctly.

Daniela Rus, Director of CSAIL and MIT EECS Professor, recently received the 2025 Edison Medal from the Institute of Electrical and Electronics Engineers (IEEE). The award recognizes her leadership and pioneering work in modern robotics.

Many companies are turning to automation—a solution long feared by some workers—in an effort to thrive in this economic environment.

Daniela Rus, Director of CSAIL and MIT EECS Professor, was recently named a co-recipient of the 2024 John Scott Award by the Board of Directors of City Trusts. This prestigious honor, steeped in historical significance, celebrates scientific innovation at the very location where American independence was signed in Philadelphia, a testament to the enduring connection between scientific progress and human potential.

For roboticists, one challenge towers above all others: generalization – the ability to create machines that can adapt to any environment or condition. Since the 1970s, the field has evolved from writing sophisticated programs to using deep learning, teaching robots to learn directly from human behavior. But a critical bottleneck remains: data quality. To improve, robots need to encounter scenarios that push the boundaries of their capabilities, operating at the edge of their mastery.