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Scientists turn brain signals into speech with help from AI

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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...
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The Challenges of Centralized AI

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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...
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How do you see AI in clinical research?

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3 Types of Artificial Intelligence (AI) to Impact Clinical Research in the Next 3 Years Generally, research studies recommend looking at AI through the lens of business capabilities rather than technologies. There are three types of AI being deployed by life science businesses that can provide a framework for improving efficiencies. Very broadly, AI can support  1)  automation of business processes , 2)  gaining insight into data  through data analysi s , and 3)  making critical decisions  based on the large volumes of data and thus impacting overall business through the big data analysis and engagement with the customers, patients, suppliers and employees. Process Automation / Focus on Efficiencies This type of AI relates to automation of what we can broadly call ‘back-office’ function and it is deployed through more efficient handling of digital and physical tasks using technology. Such tasks may include Transferring the data ...
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The Latest Innovations in Artificial Intelligence

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What are some of the most recent developments in AI? With so many emerging applications for artificial intelligence making a splash across a wide range of industries, it can be difficult to keep up. This post will touch on some cool advances made in 2019 and look at what’s on the horizon. AI takes a deep dive Robotics is a prime area of development for the AI community so it’s no surprise that there are plenty of start-ups conducting research with the intention of taking the field further. Seattle company Olis Robotics caught the attention of  GeekWire  earlier this year with a solution designed to take robotics not just to the next level,  but somewhere else entirely . According to CEO Don Pickering, “Olis Robotics’ innovation currently manifests in a plug-and-play controller loaded with our AI-driven software platform. The controller and our proprietary software can operate tethered robots on the ocean floor, satellite servicing robots using high-latency sat...
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Looking Into Python

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Developed by Guido van Rossum in 1990’s, Python is an all purpose programming language that is object-oriented, and interactive. Similar to the programming language Perl, Python’s source code can be found under the GNU General Public License (GPL). Why you should learn Python? Python is an asset to working professionals or even students who are aspiring to become software engineers, especially when they are/they want to work in the web development domain. Few advantages of learning Python are: Python is a Beginner’s Language  − Python is a great choice for beginner-level programmers. It is highly compatible with a lot of applications, be it games, WWW browsers or simple text processing Python is Interactive  − With Python, the user can directly interact with the interpreter to write their programs Python is Interpreted  −  The interpreter processes this programming language at runtime. There is no need for the user to compile the program before execut...
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