Some also use it to send text messages through voice commands while driving, or to communicate with a speaker of another Chinese dialect. But while some impressive progress in voice recognition and instant translation has enabled Xu to talk with his Canadian tenant, language understanding and translation for machines remains an incredibly challenging task (see "AI's Language Problem"). In August, iFlytek launched a voice assistant for drivers called Xiaofeiyu (Little Flying Fish). Min Chu, the vice president of AISpeech, another Chinese company working on voice-based human-computer interaction technologies, says voice assistants for drivers are in some ways more promising than smart speakers and virtual assistants embedded in smartphones.
Whether it's making your email smarter, streamlining tasks or solving the riddle of incurable diseases, AI and machine learning will probably have a huge impact in your life. Andrew Ng, former head of AI for Baidu, has said that machine learning and AI "Will also now change nearly every major industry--healthcare, transportation, entertainment, manufacturing." There's no doubt that a lot of people are starting to see how machine learning and AI might change their industries. Whether it's making your email smarter, streamlining tasks or solving the riddle of incurable diseases, AI and machine learning will probably have a huge impact in your life.
They say their decoder significantly outperforms existing approaches. These included a Long Short Term Memory Network, a recurrent neural network, and a feedforward neural network. "For instance, for all of the three brain areas, a Long Short Term Memory Network decoder explained over 40% of the unexplained variance from a Wiener filter," they say. But Glaser and co deliberately reduced the amount of training data they fed to the algorithms and found the neural nets still outperformed the conventional techniques.
Instagram posts made by individuals diagnosed with depression can be reliably distinguished from posts made by healthy controls, using only measures extracted computationally from posted photos and associated metadata. In studies associating mood, color, and mental health, healthy individuals identified darker, grayer colors with negative mood, and generally preferred brighter, more vivid colors [16–19]. Instagram posts made by depressed individuals prior to the date of first clinical diagnosis can be reliably distinguished from posts made by healthy controls. The authors analyzed 118 studies that evaluated general practitioners' abilities to correctly diagnose depression in their patients, without assistance from scales, questionnaires, or other measurement instruments.
On August 3, sequencing company Veritas Genomics bought one of the most influential: seven-year old Curoverse. In a step forward, the company also hopes to use things like natural language processing and deep learning to help customers query their genetic data on demand. He points to a 2013 study that used polygenic testing to predict heart disease using the Framingham Heart Study data--about as good as you can get, when it comes to health data and heart disease. "They authors showed that yes, given polygenic risk score, and blood levels, and lipid levels, and family history, you can predict within 10 years if someone will develop heart disease," says Butte.
Researchers at Stanford University Medical Center have taken a closer look at the roots of this rage in the mouse brain, and in a study published today in Neuron, they pinpoint the brain cells that give rise to male territorial aggression. "It's a needle in a haystack compared to the 80 million neurons in the mouse brain," says Nirao Shah, senior study author and a professor at Stanford University. When scientists activated their clusters of VMH neurons, the mice still aggressively defended their cage against intruders. But when placed in a different mouse's cage, they didn't attack, even when the VMH neurons were activated--these mice knew they were guests in someone else's home.
Singapore and MIT have been at the forefront of autonomous vehicle development. Now, leveraging similar technology, MIT and Singaporean researchers have developed and deployed a self-driving wheelchair at a hospital. Spearheaded by Daniela Rus, the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science and director of MIT's Computer Science and Artificial Intelligence Laboratory, this autonomous wheelchair is an extension of the self-driving scooter that launched at MIT last year -- and it is a testament to the success of the Singapore-MIT Alliance for Research and Technology, or SMART – a collaboration between researchers at MIT and in Singapore. Rus, who is also the principal investigator of the SMART Future Urban Mobility research group, says this newest innovation can help nurses focus more on patient care as they can get relief from logistics work which includes searching for wheelchairs and wheeling patients in the complex hospital network.
In China today, voice assistant technology works by turning a user's voice commands into text and generating a response based on the meaning of the text. They will also have to understand emotions, since humans' decision making is not based solely on logic, notes Jia Jia, an associate professor at Tsinghua University who studies social affective computing. As of the end of 2016, Baidu claimed 665 million monthly active mobile users, and as of March this year, Alibaba had 507 million mobile monthly active users. For example, to train a neural network to understand texts in sports medicine, you could draw upon data from sports and data from medicine.
Currently, most AI systems are based on layers of mathematics that are only loosely inspired by the way the human brain works. Building AI that can perform general tasks, rather than niche ones, is a long-held desire in the world of machine learning. It argues that deep learning, which uses layers of artificial neurons to understand inputs, and reinforcement learning, where systems learn by trial and error, both owe a great deal to neuroscience. The solution, Hassabis and his colleagues argue, is a renewed "exchange of ideas between AI and neuroscience [that] can create a'virtuous circle' advancing the objectives of both fields."
London's Royal Free hospital failed to comply with the Data Protection Act when it handed over personal data of 1.6 million patients to DeepMind, a Google subsidiary, according to the Information Commissioner's Office. The ICO ruled that testing the app with real patient data went beyond Royal Free's authority, particularly given how broad the scope of the data transfer was. The ruling does not directly criticise DeepMind, a London-based AI company purchased by Google in 2013, since the ICO views the Royal Free as the "data controller" responsible for upholding the data protection act throughout its partnership with Streams, with DeepMind acting as a data processor on behalf of the trust. Streams has since been rolled out to other British hospitals, and DeepMind has also branched out into other clinical trials, including a project aimed at using machine-learning techniques to improve diagnosis of diabetic retinopathy, and another aimed at using similar techniques to better prepare radiotherapists for treating head and neck cancers.