MIT Technology Review sits down with Gates to talk about breakthrough technologies, China, and reasons to be cheerful about the future.
We typically imagine robots looking like humans, but there’s a real advantage to other “form factors” that mimic pack animals.
For example, check out this new robot that MIT just made: a mini cheetah robot, the first four-legged robot to do a backflip.
At only 20 pounds the limber quadruped can bend and swing its legs wide, enabling it to walk either right side up or upside down. More practically, the robot can also trot over uneven terrain about twice as fast as an average person’s walking speed.
Oliver Cameron is the Co-Founder and CEO of Voyage. Before that he was the lead of the Udacity Self-Driving Car program that made ideas in autonomous vehicle research and development accessible to the world. For more lecture videos on deep learning, reinforcement learning (RL), artificial intelligence (AI & AGI), and podcast conversations, visit our website or follow TensorFlow code tutorials on the GitHub repo.
In this video, Drago Anguelov, a Principal Scientist at Waymo, talks about developing and applying machine learning methods for autonomous vehicle perception and, more generally, in computer vision and robotics.
In this video, Lex Fridman interviews Kyle Vogt,, the President and CTO of Cruise Automation. Cruise Automation leading an effort in trying to solve one of the biggest robotics challenges of our time: vehicle autonomy.
He is the co-founder of 2 successful companies (Cruise and Twitch) that were each acquired for 1 billion dollars. This conversation is part of the Artificial Intelligence podcast and the MIT course 6.S094: Deep Learning for Self-Driving Cars.
Lex Fridman examines the 2019 state of the art of autonomous vehicles in this MIT lecture.
MIT’s Cheetah 3 robot can now leap and gallop across rough terrain, climb a staircase littered with debris, and quickly recover its balance when suddenly yanked or shoved, all while essentially blind.
In this video, Lex Friedman interviews Tomaso Poggio as part of the Artificial Intelligence podcast and the MIT course 6.S099: Artificial General Intelligence Tomaso Poggio is a professor at MIT and is the director of the Center for Brains, Minds, and Machines. Cited over 100,000 times, his work has had a profound impact on our understanding of the nature of intelligence, in both biological neural networks and artificial ones.
He has been an advisor to many highly-impactful researchers and entrepreneurs in AI, including Demis Hassabis of DeepMind, Amnon Shashua of MobileEye, and Christof Koch of the Allen Institute for Brain Science.
has just posted another excellent lecture — this time on the recent developments in deep learning that are defining the state of the art in the field