Tesla, CSAIL Alliances members, develops and deploys autonomy at scale in vehicles, robots and more.
Tesla believes that an approach based on advanced AI for vision and planning, supported by efficient use of inference hardware, is the only way to achieve a general solution for full self-driving, bi-pedal robotics and beyond.
Add to calendarAmerica/New_YorkTraining Robust Optimus Policies: Tesla AI Tech Talk10/14/2026
Tesla, CSAIL Alliances members, develops and deploys autonomy at scale in vehicles, robots and more.
Tesla believes that an approach based on advanced AI for vision and planning, supported by efficient use of inference hardware, is the only way to achieve a general solution for full self-driving, bi-pedal robotics and beyond.
Tesla Full Self Driving (FSD) drives millions of miles autonomously every day across hundreds of cities. This feat is only possible through training extremely robust policies. When the goal is to similarly have millions of robots doing thousands of useful tasks in a wide variety of environments, we need to ensure that Optimus has similarly robust policies. In this talk, we share some of our strategies in training such robust policies and showcase some of our latest world models that make this possible.
It all started with some exasperated emails. Back in 2009, a group of researchers began venting their frustration with the programming languages designed to help scientists and other researchers perform complex mathematical operations and statistical simulations without learning how to code. These programming languages were rigid and slow. If scientists built something that really worked, they’d need to rewrite the entire program in another language just to run it more quickly.
Agentic workflows are artificial intelligence-powered software systems that chain together multiple models and external tools to tackle complicated tasks, like analyzing a video and answering questions about it.
The multiplication of matrices and of higher-dimensional arrays called tensors lies at the heart of modern computing. Matrix or tensor multiplication is, in fact, the most common operation carried out in artificial intelligence applications, as well as in scientific simulations and computer graphics.
David Clark, Senior Research Scientist at MIT CSAIL, helped design the system that connects nearly every computer on earth. As Chief Protocol Architect of the Internet from 1981 to 1989, he was there for the beginnings of the Internet. Calling the wave of AI technology an “echo” of what happened in the 80’s, Dr. Clark is cautioning, “ maybe we need to slow things down and think a bit.”
What happens when the team behind PlayStation meets the researchers pushing the boundaries of AI? You get The Nexus of Games and AI, a 12-part MIT Independent Activities Period (IAP) course, now available to stream.
Young adults growing up in the attention economy — preparing for adult life, with social media and chatbots competing for their attention — can easily fall into unhealthy relationships with digital platforms. But what if chatbots weren’t mere distractions from real life? Could they be designed humanely, as moral partners whose digital goal is to be a social guide rather than an addictive escape?
The CSAIL Alliances Annual Meeting is our signature three-day event exclusive to CSAIL Alliances members.* This is your opportunity to engage with thought leaders crafting the next wave of AI and computer science and build the relationships that will drive your organization forward.
CSAIL Alliances is proud to support this event run by MIT Sloan students.
The MIT Sloan Fintech Conference is one of the largest student-run conferences in the world, bringing together hundreds of industry leaders, policymakers, founders, and students to explore the most pressing issues shaping the future of fintech.
This year, join us on February 20, 2026 as we discuss how technology like advances in ML and policy (i.e., stablecoins, open banking) are enabling new fintech infrastructure, payment experiences, and customer trust hubs.
