Artificial Intelligence and Machine Learning

The technology could lead to devices that restore speaking ability to people who have lost it as a result of brain injury or neurological disorders. An electrode array placed on the brain could help people who've lost the ability to speak. Using electrodes and  artificial intelligence , scientists in California have built a device that can translate brain signals into speech. They say their experimental decoder could lead ultimately to a brain implant that restores the ability to speak to people who have lost it as a result of stroke, traumatic brain injury or neurological diseases like multiple sclerosis and Parkinson’s disease. “This is an exhilarating proof of principle that with technology that is already within reach, we should be able to  build a device that is clinically viable in patients with speech loss ,” Edward Chang, a professor of neurological surgery at the University of California, San Francisco, and the senior author of a paper describing th...

Decentralization is likely to become one of the pillars that influences the next decade of artificial intelligence(AI). The friction between decentralized and centralized models is going to be of the existential challenges of the next years of AI. Continuing relying on centralized models is likely to increase the gap between large companies and countries with the resources to develop AI solutions and the rest of the market. The current centralized nature of AI models introduces a “rich get richer” vicious cycle in which only companies with access to large, labeled datasets and data science talent can benefit from the promises of AI. Understanding the centralization challenges of AI solutions is far from trivial as they range from purely philosophical to practical implementations. If we visualize the traditional lifecycle of an AI solution we will see a cyclical graph that connects different stages such as model creation, training, regularization, etc. My t...