Sarah Dai, based in Beijing, covers technology and capital flows in the world of start-ups in Greater China. Previously, she worked as financial correspondent for Caixin Media in Hong Kong for over two years and wrote for China Daily in Beijing and London.

In the recently released game Coffee Talk, you play a coffee-shop barista who stands at a counter, through long, rainy Seattle nights, making drinks for customers as they tell you about their lives. Your only interaction is pressing a button to move the conversation on and occasionally crafting a drink using the available ingredients. The beautiful pixel art interior of your shop, the fleeting glimpses of passersby outside, and the jazzy soundtrack replicate things we love about hanging out in real coffee places. Also, this is an alternative version of Seattle populated not just by humans, but by elves, demons and other fantastical beings, so your clientele is pretty varied. Elves tell you about their love lives, insomniac werewolves seek calm and quiet – you listen and you try to make drinks that will soothe them.

IDC predicts spending on AI systems will reach $97.9B in 2023, more than two and one-half times the ... [ ] $37.5B that will be spent in 2019. Machine learning's growing adoption in business across industries reflects how effective its algorithms, frameworks and techniques are at solving complex problems quickly. Open jobs requiring TensorFlow experience is a useful way to quantify how prevalent machine learning is becoming in business today. There are 4,134 open positions in the U.S. on LinkedIn that require TensorFlow expertise and 12,172 open positions worldwide as of today. Open jobs on LinkedIn requesting machine learning expertise in the U.S. further reflect its growing dominance in all businesses.

UNIVERSITY PARK, Pa.-- Enrique Del Castillo, distinguished professor of industrial engineering and professor of statistics at Penn State, has returned from his Fulbright U.S. Scholar Program, where he conducted research at the University of Coimbra in Coimbra, Portugal. Awarded by the J. William Fulbright Foreign Scholarship Board, Del Castillo was one of approximately 800 U.S. citizens selected to take their expertise abroad for the 2019-20 academic year through the program. Recipients of Fulbright Awards are selected on the basis of academic and professional achievement, as well as record of service and demonstrated leadership in their respective fields. The research project for which he was granted the Fulbright Fellowship, titled "Optimization and control of industrial production processes by active learning methods based on'big' and complex data," sought collaborative research between Penn State's Engineering Statistics and Machine Learning Laboratory and the University of Coimbra's chemometrics group in the Department of Chemical Engineering. Del Castillo worked on the optimization of production processes via machine learning for various industries with the chemometrics group; in particular, they focused on wine, paper and pharmaceuticals.

With coyote attacks on humans in cities and suburbs making headlines – coyotes injured two people in Chicago earlier this month – officials could tap into a data repository to get a better handle on what's bringing the area's animals into such close proximity to humans. Called eMammal, the tool has been around for several years in one form or another and has helped researchers manage camera-trapping projects. It uses a data pipeline that takes images and metadata from the field through a cloud-based review processes and into SIdora, a Smithsonian Institution data repository. To date, eMammal has data on more than 1 million detections of wildlife worldwide, including in cities. Smithsonian researchers collaborated with others at the North Carolina Museum of Natural Sciences, Conservation International and the Wildlife Conservation Society to develop an open standard for camera trap metadata -- the Camera Trap Metadata Standard -- as part of the eMammal project. Camera traps are ruggedized cameras that researchers place in forests, jungles, grasslands, cities and elsewhere to capture images of mammals.

Cardiology was already heavily data driven, where clinical practice is driven by clinical study data, but mining a cardiology department's own data via the cardiovascular information system (CVIS or cardiac PACS) allows insights into a department's own patient population, best practices, workflow, physician and technologist workloads, inventory usage and patient outcomes. This data is now being leveraged to flow into a variety of clinical registries, certification programs, data mining for population health initiatives, and for the training and integration of artificial intelligence (AI) and machine learning algorithms that are starting to be adopted across the healthcare continuum. "We need to be able to retrieve these data elements out of the medical records. But when we talk about traditional methods of data collection like transcription and paper-based documentation, it really does not allow clinicians to get this data out, so there is a need for structured reporting," said Jennifer Ireland, senior product manager, Centricity Cardio Workflow, GE Healthcare. She said structured reports need to be integrated into clinical workflows, and that clinicians need three things from these structured reports: what they saw, what they did and what is the end result, including their own conclusion or recommendation.

The year 2017 saw a sudden emergence of interest and support for Artificial Intelligence (AI) programming by children. Stephen Wolfram wrote a chapter in his An Elementary Introduction to the Wolfram Language textbook about machine learning. He wrote a blog post Machine Learning for Middle Schoolers, where he describes the rationale behind the different examples and exercises. Dale Lane launched Machine Learning for Kids, which he recently described in his excellent article in Hello World 4. Google launched the first of two AIY projects for voice and vision kits for Raspberry Pi projects. Google also launched the Teachable Machine and a collection of browser-based machine learning experiments.

After announcing a $550 million fundraise last August, U.K. AI-based health services startup Babylon Health is putting some of that money to use with its widest-ranging project to date. The company has inked a 10-year deal with the city of Wolverhampton in England to provide an integrated health app covering 300,000 people, the entire population of the city. The financial terms of the deal are not being disclosed, but Babylon confirmed that the NHS is not taking a stake in the startup as part of it. The plan is to start rolling out the first phase of the app by the end of this year. Babylon Health is known for building AI-based platforms that help diagnose patients' issues.

Artificial intelligence is alerting and Mac malware is diverting, but first: a cartoon about baby privacy. Here's the news you need to know, in two minutes or less. Want to receive this two-minute roundup as an email every weekday? On January 9, the World Health Organization notified the public of a flu-like outbreak in Wuhan, China, that led to city lockdowns affecting tens of millions of people. But a Canadian health monitoring platform sent news of the outbreak to its customers more than a week earlier, on December 31.