The rapid emergence and spread of the novel coronavirus, 2019-nCoV, has alarmed people around the world. While the possibility of a global pandemic is real, people can take some solace in the fact that public health officials have at their disposal an array of powerful data collection and analytics techniques that previous generations lacked. The virus, which causes a pneumonia-like illness that's quite similar to the Severe Acute Respiratory Syndrome (SARS) outbreak 2003 that killed 800 people, appears to have jumped into the human biome at an exotic meet market in Wuhan, China, where delicacies like bats and snakes were sold to the public. But what makes 2019-nCoV dangerous is its ability to spread from human to human, and that's how more than 17,000 Chinese citizens have gotten sick. However, before Chinese authorities could quarantine Wuhan and surrounding areas, infected individuals were allowed to travel around the world, and today individuals in 20 countries have been reported to be infected with 2019-nCoV, which the World Health Organization (WHO) last week declared a global health emergency.

Jokingly dubbed "deal prevention units" by some front-office staff, compliance teams now have the third most-stressful City jobs after that of an investment banker and a trader. Pre-crisis, pre-Brexit and pre-cybercrime, compliance used to be (almost!) a stress-free job with regular hours. As regulatory pressure intensifies and personal liability mounts, compliance officers are under increased pressure do the right thing every time, personally and professionally. Our latest research, The Cost of Compliance and How to Reduce It, shows that a typical European bank, serving 10 million customers, could save up to €10 million annually and avoid growing fines by the regulator by implementing technology to improve the "Know Your Customer" (KYC) processes. Following new EU Anti-Money Laundering (AML4/5) and Counter-Terrorist Financing (CTF) rules extending the scope of KYC requirements, the cost each year of punitive non-compliance fines is now €3.5 million.

Hoan Ton-That, CEO of creepy facial recognition company Clearview AI, made the bold claim on Tuesday that his company has the right to publicly posted photos on Twitter and wielded the First Amendment as his reason. Clearview AI faced heat after it was discovered they had mined billions of publicly accessible images from Facebook and Ton-That's comments prove the company isn't backing down. EXCLUSIVE: The founder of a facial recognition company described as both "groundbreaking" and "a nightmare" is speaking out. In an interview with CBS This Morning, Ton-That was asked about Twitter's cease-and-desist order requesting that his company stop scraping it's data and delete everything Clearview AI has collected from the platform. In response, the facial recognition CEO claimed his company has a first amendment right to the data.

Claims 1 and 8 as recited are not practically performed in the human mind. As discussed above, the claims recite monitoring operation of machines using neural networks, logic decision trees, confidence assessments, fuzzy logic, smart agent profiling, and case-based reasoning. . . .

Sustainability is at the forefront of all aspects of the supply chain in retail. From product development and production to shipping and returns, every aspect of the retail industry is working to become more sustainable. Increasing these efforts is challenging, as many retailers frequently introduce new products to meet the demands of the constantly evolving consumer. On average, up to 20% of clothing goes unsold and is often incinerated. Additionally, returned goods create more than 5 billion pounds of waste in U.S. landfills each year.

Machine learning algorithms excel at generating realistic photos, videos, and even voices. Last year, researchers at AI startup Dessa created a convincing fake audio file of popular American podcaster Joe Rogan's voice. In an Instagram post, Rogan responded to the highly realistic spoof: "At this point I've long ago left enough content out there that they could basically have me saying anything they want…" Although few-shot training may be changing this, Rogan was not wrong about the large voice library he has generated. Generally speaking, in ML the more training data the better, and this is also the case in voice synthesis. Although current machine learning techniques enable researchers to synthesize even singing voices at a similarly high quality, existing singing-voice datasets typically include only single singers.

What happens when the road gets bumpier? Not too long ago, tech enthusiasts were telling us that by 2020, we'd see self-driving cars hit the mainstream, with some 10 million on the roads. That turned out to be a wild overestimation. The actual number of vehicles in testing is thousands of times smaller, and they're still driving mostly in controlled conditions. Companies have also scaled back their ambitions, aiming more for driver support than full autonomy, just as sober-minded transport experts told us to expect. But slower development is probably just as well, as it should help improve vehicle safety and give engineers time to prepare for other threats, such as hackers turning cars into destructive weapons.

Confirming a diagnosis of Alzheimer's disease requires an expensive PET scan that uses a high dose of full-body radiation. With seed grant support from the Stanford Institute for Human-Centered Artificial Intelligence (HAI), a group of Stanford researchers can now diagnose Alzheimer's Disease just as successfully by applying artificial intelligence (AI) to low-dose PET scans and simultaneously acquired MRI images. "This work has the advantage for the patients of being safer, lower dose, faster, cheaper all the things you'd want as a patient," said Greg Zaharchuk, professor of radiology at Stanford University and 2018 HAI seed grantee. Using artificial intelligence, Zaharchuk's team has become adept at what's called image transformation. They can take one image or set of images and use a type of AI called a convolutional neural network (CNN) to produce a new set of images as the output.

The British startup Exscientia claims it has developed the first medication created using artificial intelligence that will be clinically tested on humans. The medication, which is meant to treat obsessive-compulsive disorder, took less than a year from conception to trial-ready capsule. Human trials are set to begin in March, but would you take a drug designed using artificially intelligent software? The appeal of AI-designed drugs is relatively straightforward. There are lots and lots of possible molecules that might be useful in medications, far too many for all the medical researchers in the world to manually test.

The contract is for a project related to improving situational awareness for the Canadian Armed Forces ("CAF") and security personnel using video analytics, artificial intelligence and augmented reality. This project will continue previous work completed by Xtract.ai for the CAF to develop technology solutions to augment the situational awareness of their soldiers and address the following challenges: Work will proceed in multiple phases, including the design, development and deployment of advanced machine learning models, proprietary data sets and integration with advanced visualization hardware. "We're very excited to leverage the Xtract.ai The Xtract.ai team is already under way in the project's design and development phase, and will make announcements, as required, on the progress of its efforts in achieving the goals of Canadian Department of National Defense. The firm has an award winning, highly skilled team that develops AI solutions to solve challenges across computer vision (CV), natural language processing (NLP), anomaly detection, and time-series analysis for applications ranging from security and defense to environmental solutions and healthcare.