"Neural Lander" Uses AI to Land Drones Smoothly
Professors Chung, Anandkumar, and Yue have teamed up to develop a system that uses a deep neural network to help autonomous drones "learn" how to land more safely and quickly, while gobbling up less power. The system they have created, dubbed the "Neural Lander," is a learning-based controller that tracks the position and speed of the drone, and modifies its landing trajectory and rotor speed accordingly to achieve the smoothest possible landing. The new system could prove crucial to projects currently under development at CAST, including an autonomous medical transport that could land in difficult-to-reach locations (such as a gridlocked traffic). "The importance of being able to land swiftly and smoothly when transporting an injured individual cannot be overstated," says Professor Gharib who is the director of CAST; and one of the lead researchers of the air ambulance project. [Caltech story]
Professor Anandkumar Receives 2018 Good Tech Award
Professor Animashree (Anima) Anandkumar has been recognized by the New York Times “good tech” awards as a leading Artificial intelligence (A.I.) researchers who uses “ technology to help others in real, tangible ways.” The New York Times article states, “Artificial intelligence will be one of the most important areas of computer science in the coming years. It’s also one of the least diverse. Just 12 percent of A.I. researchers are women, and the number of black and Latino executives in the field is vanishingly small… Anandkumar, Nvidia’s director of machine learning research and a professor at Caltech, saw that the name of the A.I. field’s marquee annual event — the Neural Information Processing Systems conference, or NIPS — had been used as fodder for sexist jokes. So she started a #ProtestNIPS campaign to change the name, and drew up a petition that gathered more than 2,000 signatures. Eventually, the conference’s board relented, and the event is now abbreviated as “NeurIPS.” It was a small gesture of inclusion that could go a long way toward making women feel more welcome in the field for years to come.” [NYTimes article] [Tensorial-Professor Anima on AI]
Award For Technical Clarity and Ease of Understanding
Animashree (Anima) Anandkumar, Bren Professor of Computing and Mathematical Sciences, and colleagues have won a Best Poster Award at the Neural Information Processing Systems (NIPS) MLtrain workshop. The submission was called “Tensor Regression Networks with TensorLy and MXNet” and the work showed that tensor contractions and regression layers are an effective replacement for fully connected layers in deep learning architectures. The MLtrain workshop focuses on making research more accessible through ipython notebooks and the submissions are judged based on the technical clarity and ease of understanding of the poster and the code.
AWS and Caltech Partner to Accelerate AI and Machine Learning
From autonomous robotics to state of-the-art computer vision, Caltech and Amazon have a lot in common, including the belief that pushing the boundaries of artificial intelligence (AI) and machine learning (ML) will not only disrupt industries, but it will fundamentally change the nature of scientific research. As part of this two-year renewable research collaboration, Amazon will provide both financial support, in the form of funding for graduate fellowships, and computing resources, in the form of AWS Cloud credits, to accelerate the work of faculty and students at Caltech in these areas. [AWS AI Blog]