Recently, "MIT Technology Review" released the world's top ten breakthrough technologies in 2017, and once again received high attention from all walks of life. This annual technology feast comprehensively presents the direction of future technology development and the profound changes that our life will inevitably face.
There is almost no suspense, and artificial intelligence represented by Reinforcement Learning (RL) ranks first. Although everyone knows that AI is the most popular AlphaGo in the game of Go, the innovation of this underlying technology has brought about tremendous changes in the medical field. In addition, the medical field has a very hot gene therapy in recent years, as well as a sensational cell mapping program in the second half of last year.
Another is that the Singularity Network has been paying attention, but there has been very little attention to the Brain-computer interface (BCI). The author has always believed that this is a field full of sci-fi colors. Although it is mainly used on the sultry, we believe that its future application prospects are not limited to the medical field, and its imagination space is unlimited. This time, the MIT Technology Review stood with us.
Cell Atlas Program (Figure: Broad Institute)
It’s also a coincidence that just yesterday’s MIT Technology Review released the top 10 global breakthrough technology lists, Stanford University electrical engineering professor Krishna Shenoy and neurosurgery professor Jaimie Henderson joined the famous open source journal eLife. The authors published important clinical research papers on brain-computer interface. They successfully let the three test subjects accurately control the cursor of the computer screen through simple imagination. The three paralyzed patients successfully input what they want to say on the computer screen by imagination. One of the patients can enter an average of 39 letters in about 1 minute, which is about 8 words (1). According to the paper, this is the first time in the world to achieve such fast and accurate character input through the brain-computer interface.
Krishna Shenoy, Professor of Electrical Engineering, Stanford University
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