Given that our smartphones have largely become appendages over the last decade, it’s hard to imagine that ten years ago there was no Instagram, Uber, TikTok or Tinder. The ways we move, shop, eat and communicate continue to evolve thanks to the technologies we use. It can be easy to forget how quickly things have changed - so let’s turn back the clocks and reminisce about some of the computing breakthroughs that have transformed our lives in the ’10s.
Computer vision models have learned to identify objects in photos so accurately that some can outperform humans on some datasets. But when those same object detectors are turned loose in the real world, their performance noticeably drops, creating reliability concerns for self-driving cars and other safety-critical systems that use machine vision.
In opening the AI and the Work of the Future Congress, MIT Professor Daniela Rus presented diverging views of how artificial intelligence will impact jobs worldwide.
By automating certain menial tasks, experts think AI is poised to improve human quality of life, boost profits, and create jobs, said Rus, director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science.
Existing efforts to detect IP hijacks tend to look at specific cases when they’re already in process. But what if we could predict these incidents in advance by tracing things back to the hijackers themselves?
Cities are now beginning to question how much citizen data, if any, they can use to track government operations. In a new study, MIT researchers find that there is, in fact, a way for cities to preserve citizen privacy while using their data to improve efficiency.
A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) came up with a new system for better predicting health outcomes: a machine learning model that can estimate, from the electrical activity of their heart, a patient’s risk of cardiovascular death.
A team from MIT CSAIL has developed a new radix-sorting algorithm called Regions Sort which is up to four times faster than similar algorithms while using half the memory.
Wearing a sensor-packed glove while handling a variety of objects, MIT CSAIL researchers have compiled a massive dataset that enables an AI system to recognize objects through touch alone. The information could be leveraged to help robots identify and manipulate objects, and may aid in prosthetics design.
