The world’s best player of what might be humankind’s most complicated board game was defeated on Tuesday by a Google computer program. Adding insult to potentially deep existential injury, he was defeated at Go — a game that claims centuries of play by humans — in China, where the game was invented. The human contender, a 19-year-old Chinese national named Ke Jie, and the computer are only a third of the way through their three-game match this week.
Cera is a medical AI startup looking to change the way we approach social care. Currently, the company offers a marketplace-platform to match carers with patients and a newly released virtual assistant called Martha. Martha can be accessed online or by text message.
While it is relatively simple now, in the future the plan is for Martha to parse a patient’s medical records. The hope is this would allow Martha to send warnings if a patient was behaving strangely or if behaviour could be used to give early warnings of illness.
Robert Hart, from Quartz, argues that when 1 in 6 patients in the NHS receives an incorrect diagnosis, it is unsurprising that AI could have an important role to play. There have already been examples of AI having more success than human doctors within lung cancer detection and identification of rare eye diseases.
However, what happens when something goes wrong? Hart states that even computer-literate doctors will be unable to find out why an AI has made a specific decision given their ‘blackbox’ nature. This leads to a broader philosophical debate around who is to blame. The AI itself? The developers? The organisation responsible for the AI? As Hart suggests, “Not knowing undermines patient trust, places doctors in difficult positions, and potentially deters investment in the field”.
Researchers at the University of Waterloo, in partnership with Cardon Rehabilitation and Medical Equipment, have created an Automated Rehabilitation System to allow people recovering from hip and knee replacements to see how well they are performing rehabilitative exercises.
The system, which combines motion sensors
with software programs, attaches sensors to a person’s limbs — such as above the knee and ankle in knee replacement cases — which send data to a computer while patients do exercises prescribed by physiotherapists. Using human body modelling and machine learning, the system then analyzes, organizes, and stores the data and generates visual representation of the motion.
Injuries have a great impact on professional soccer, due to their large influence on team performance and the considerable costs of rehabilitation for players. Existing studies in the literature provide just a preliminary understanding of which factors mostly affect injury risk, while an evaluation of the potential of statistical models in forecasting injuries is still missing.
In this paper, the authors propose a multidimensional approach to injury prediction in professional soccer
which is based on GPS measurements and machine learning. By using GPS tracking technology, they collect data describing the training workload of players in a professional soccer club during a season. They show that their injury predictors are both accurate and interpretable by providing a set of case studies of interest to soccer practitioners.
Women in artificial intelligence (AI) and machine learning (ML), or the lack thereof, is not a new topic in media, just as gender equality and disparity in the workplace is not a new subject of research for academics and think tanks. But discussing these issues openly is no less important. While they address the potential reasons and implications of these issues toward the end of this article, their initial interest in this subject came from our desire to know the following:
How many women are in C-level and other leadership roles in the AI and ML industries compared to males?
How might these numbers compare to other industries and the workforce at large?
What are the potential implications of female presence (or lack thereof) in leadership roles within AI and ML companies?
French startup Stanley Robotics just raised $4 million (€3.6 million). The company is building giant robots that pick up your car at the entrance of a parking lot and park it for you.
Stanley Robotics plans to take advantage of that with a robot called Stan. It is going to make airport parking lots more efficient through its creation robot valet-parking. All of this sounds great on paper, but the most reassuring thing is that Stanley Robotics is already operating at Charles-de-Gaulle airport in Paris. It’s been years in the making, but a parking lot is now operated by robots.
Last month, IKEA launched its own line of low-cost smart lighting, called TRÅDFRI, and up until now, users have had to rely on a remote control or a proprietary app to use the product. But no longer.
Yesterday, the Swedish retailer announced that their IKEA Home Smart products will respond to voice commands from Alexa, Siri, and Google Assistant starting this summer. Additionally, the product line will integrate with Apple’s HomeKit. “With IKEA Home Smart we challenge everything that is complicated and expensive with the connected home. Making our products work with others on the market takes us one step closer to meet people’s needs, making it easier to interact with your smart home products,” said IKEA Home Smart’s business leader Björn Block.