Microsoft announced this morning that it has acquired Maluuba, a Toronto startup focused on using deep learning for natural language processing. Deep learning is an approach to artificial intelligence currently in vogue that has driven incredible gains in the field over the last five years. As Microsoft wrote in the blog post announcing the purchase, “We’ve recently set new milestones for speech and image recognition using deep learning techniques, and with this acquisition we are, as Wayne Gretzky would say, skating to where the puck will be next — machine reading and writing.”
The Verge covered Maluuba in the summer of 2016, when the startup shared the results of an AI system that could read and comprehend text with near human capability, outperforming similar systems shown off by Google and Facebook. Along with acquiring the company, Microsoft has also established closer ties with Yoshua Bengio, a pioneer in the field of deep learning who served as an advisor to Maluuba, and will now become and advisor to Microsoft’s AI division.
Most of today’s robot hands can perform easy tasks. They’re uber-practical grippers, simple and useful. But is it really so much to ask for robotic masterworks as dextrous as Luke Skywalker’s bionic hand in Star Wars? In short, yes, yes it is. It might have been a long time ago in a galaxy far far away—but most Star Wars tech is beyond us.
Still, it’s hard not to get in a Star Wars state of mind watching this beautiful robot hand engineered by Yale postdoc Joseph (Zhe) Xu and the University of Washington’s Emanuel Todorov.
Syn. Neurons via Q-Dot Laser. Nice.
Greek researchers working at the National and Kapodistrian University of Athens (EKPA) optical communication photonic technology laboratory have developed an artificial “neuron” that simulates fundamental functions of the human brain, at speeds that are many orders of magnitude higher.
A paper on the new breakthrough made by the Greek team, led by Prof. Dimitris Syvridis with Dr. Charis Mesaritakis as main researcher and with Alexandros Kapsalis and Adonis Bogris listed as authors, was published in the “Scientific Reports” section of the science journal “Nature” on December 19.
Simulating the action of biological neurons is the “Holy Grail” of computing; the proposal developed by Mesaritakis and his team uses an integrated all-optical neuron based on an InAs/InGaAs semiconductor quantum-dot passively mode-locked laser.
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