Google AI today shared that it's created a model for detecting an endangered species of orca whales in the Salish Sea, a waterway between the United States and Canada. Underwater microphones situated at a dozen points in the Salish Sea that includes the state of Washington and Vancouver Bay are used to alert officials when a Southern Resident killer whale is detected. Less than 100 of these whales are thought to still be alive, according to the Center for Whale Research. The orca detection model is the latest from Google, and it follows previous acoustic AI work to detect the sound of chainsaws in rainforests to stop illegal lumber operations and work last year with the National Oceanic and Atmospheric Administration (NOAA) in the U.S. to help protect humpback whales. The orca model runs on a platform operated by the nonprofit Rainforest Connection.

The company employs a team of pharmacists, clinicians, technical and administrative support staff to provide GP surgeries with respiratory, cardiovascular and diabetes clinics, as well as care home and home-bound patient support. The Innovate UK funded partnership will allow Firza to grow its client-base more quickly and increase the size of its contracts so the company can expand into wider UK and global markets in healthcare. In 2020, the healthcare market in the UK will be worth over £127 billion (Institute for Fiscal Studies, 2017) of which administrative services provision to GP surgeries accounts for £160 million. By freeing up the time of NHS staff this partnership could potentially make the NHS more productive - helping it save money on staff costs.

From US real estate giant inadvertently leaking 900 million records to Danish hearing aid manufacturer Demant being a victim to a 95 million US dollars hack –cybercriminals ran rampant in the last year. In the USA alone, there were ransomware attacks against 621 government agencies, schools and healthcare providers in the first nine months of 2019. Cybercrime also became much more sophisticated in the year. And this is a trend that will continue in 2020 and beyond. While the classic phishing method –where a login page tricks a user into giving their information – is still very much popular, the use of Artificial Intelligence by malicious parties is an emerging threat that cannot be ignored.

Robots are complex machines with lots of components. Each of these components has a precise purpose, and when each component acts as expected, it creates a seamless system that can accomplish intricate tasks. This idea scales to networks of robots working in tandem to accomplish even more complex tasks. In this case, when one machine falters or fails to collaborate with the others, it can cause chaos: Picture a drone flying away from its fleet and failing to photograph its assigned area, or a self-driving car getting too close to another and disrupting carefully designed platoon. Making networks like these smarter, more functional, and more efficient is the subject of two research projects at Lehigh University led by Nader Motee, an associate professor of mechanical engineering and mechanics at the P.C. Rossin College of Engineering and Applied Science.

These and many other insights are from Javelin Strategy and Research report published this month, Protecting Digital Innovation: Emerging Fraud and Attack Vectors. A copy of the report can be downloaded here (25 pp., PDF, opt-in). The methodology is based on a survey of 200 fraud and payment decision-makers for businesses headquartered in the United States. Respondents are evenly distributed from four industries including consumer banking, insurance, restaurants/food service, and retail merchants. The survey's results are noteworthy because they reflect how AI and machine learning-based fraud prevention techniques are helping retailers, financial services, insurance and restaurants to reduce false positives that in turn reduces friction for their customers.

An AI-driven health monitoring and disease detection platform was able to catch the signs of the Wuhan viral outbreak approximately a week before government agencies warned the public, providing a look at how AI can be used to catch disease outbreaks in a timely fashion. While the official World Health Organization notification of the Wuhan virus went out on January ninth and the US Center for Disease Control and Prevention (CDC) received word of the outbreak on January sixth, the first warning signs of the outbreak were picked up by a Canadian health monitoring system almost a week prior. As Wired reported, the AI-driven health system BlueDot warned its clients about the possible outbreak on December 31st. Bluedot uses AI algorithms to monitor different global news sources and detect patterns in health reports. It also takes into account information on plant and animal disease networks. Using the information it collects, BlueDot epidemiologists then delivers warnings and predictions about possible health risks and outbreaks to its subscribers.

Malcom Finlay (Bart's Health Centre, London, UK) reviews the growing role of artificial intelligence (AI) in diagnosing arrhythmias. Johnny, a 72-year-old film producer, is meeting clients when his watch gently vibrates notifying him of his irregular pulse. He pressed his finger to his strap, and with a swipe sends the single lead ECG to his cardiologist without pausing the meeting. The AI delivered backbone powering self-diagnostics and wearables is invisible but always present: AI is taking over the medical world. Or so it would seem.

Artificial intelligence (AI) is increasingly embedded into every aspect of life, and China is pouring billions into its bid to become an AI superpower. China's three-step plan is to pull equal with the United States in 2020, start making major breakthroughs of its own by mid-decade, and become the world's AI leader in 2030. There's no doubt that Chinese companies are making big gains. Chinese government spending on AI may not match some of the most-hyped estimates, but China is providing big state subsidies to a select group of AI national champions, like Baidu in autonomous vehicles (AVs), Tencent in medical imaging, Alibaba in smart cities, Huawei in chips and software. Baidu ("China's Google") is based in Beijing, where the local government has kindly closed more than 300 miles of city roads to make way for AV tests.

Evaluating the effectiveness of therapies for neurodegenerative diseases is often difficult because each patient's progression is different. A new study shows artificial intelligence (AI) analysis of blood samples can predict and explain disease progression, which could one day help doctors choose more appropriate and effective treatments for patients. Scientists at The Neuro (Montreal Neurological Institute and Hospital) of McGill University and the Ludmer Centre for Neuroinformatics and Mental Health used an AI algorithm to analyze the blood and post-mortem brain samples of 1969 patients with Alzheimer's and Huntington's disease. Their goal was to find molecular patterns specific to these diseases. The algorithm was able to detect how these patients' genes expressed themselves in unique ways over decades.

The last decade witnessed the technology landscape change rapidly. As humans kept pace, it also birthed the need for extensive reskilling. The next decade will be about the democratisation of technology when it's far more accessible (even to the under-privileged), immersive, personalised, and affordable. Reduced turnaround times, increased outreach and pinpointed go-to-market strategies will unlock a whole new world of opportunities. Importantly, this decade will allay the fear of job losses that dominated political capital all across the world.