In 2018, California's state government began rolling out a new "mental health" initiative. The tech companies of Silicon Valley were creating smartphone apps that could prompt users to seek mental health care, and the state wanted to provide support. After all, researchers claim that more than half of Americans with mental health problems don't receive treatment, and one reason for that might be that treatment is expensive or unavailable in certain regions. Of the thousands of mental health apps in existence today, the state selected two. The first app is called 7 Cups, by a company called 7 Cups of Tea. They're focused on connecting mental health service users, in text-based chat sessions, with what they call "listeners"--volunteers who are trained in "active listening." But, according to The New York Times, the company has been plagued with issues, including listeners having inappropriate conversations with their clients and investigations of its alleged financial misconduct. The other company partnering with the state of California is Mindstrong Health. Their app (branded Mindstrong on March 17, 2020, previously known as Health) is available on the Google Play Store and the Apple App Store. However, you can only use the app if you have been given a code to participate by one of the health insurance companies they've partnered with. The company won't tell you which companies they work with--it's by invitation only.

EU trade policy should carve out space for the regulation of ethical and responsible artificial intelligence (AI) in future trade talks. This is the finding of a new study by researchers from the University of Amsterdam's (UvA) Institute for Information Law. The Dutch Ministry of Foreign Affairs commissioned the study to generate further knowledge about the interface between international trade law and European norms and values when it comes to the use of AI. As AI seeps ever more comprehensively into our daily lives--through our phones, our cars, even in our doctors' offices--the need to ensure responsible use of such technologies becomes ever greater. Responsible use of AI is therefore a top priority for the Dutch government and for the EU as a whole.

Even then, in these times of heightened data usage and privacy regulations, it may not always be possible to let algorithms loose across a company's data assets. It is extremely important to ensure that all the right consents and controls are in place. This requires a high degree of data maturity as it involves a diverse variety of datasets, each with its own set of rules and principles. Organisations then need to create an integrated data platform that can connect these data sources to AI algorithms.

When people started doing more and more things on the internet, cyber safety became a must, especially when money was involved. There are thousands of threats awaiting you on the website, and they might cost you more than nerves. That's why cybersecurity is of extreme importance. Currently, people are using various protection layers, for instance, antivirus and antimalware programs, VPN's, multi-factor authentication, and so on. Unfortunately, the amount of cyberattacks is not decreasing.

We demonstrate a first example for employing deep learning in predicting frame errors for a Collaborative Intelligent Radio Network (CIRN) using a dataset collected during participation in the final scrimmages of the DARPA SC2 challenge. Four scenarios are considered based on randomizing or fixing the strategy for bandwidth and channel allocation, and either training and testing with different links or using a pilot phase for each link to train the deep neural network. Interestingly, we unveil the efficacy of randomization in improving detection accuracy and the generalization capability of certain deep neural network architectures with Bootstrap Aggregating (Bagging).

Artificial intelligence (AI) has had a major and positive impact on a range of industries already, with the potential to give much more in the future. We sat down with Ofer Tirosh, CEO of Tomedes, to find out how the translation industry has changed as a result of advances in technology over the past 10 years and what the future might hold in store for it. Translation services have felt the impact of technology in various positive ways during recent years. For individual translators, the range and quality of computer-assisted translation (CAT) tools have increased massively. A CAT tool is a piece of software that supports the translation process.

The drug development lifecycle is long and fraught with heavy risk -- it takes a staggering 10 – 15 years on average, with ultimately only 12 percent of drugs in clinical trials gaining approval by the U.S. Food and Drug Administration (FDA) [1]. To put this in perspective, 22.7 percent of all global research and development spending in 2017 was in the healthcare industry, second only to 23.1 percent spent in the computing and electronics industry, yet the product lifecycle is longer, and costs are much higher [2]. For example, the original iPhone took two and a half years to develop from concept to launch, and an estimated $150 million spent in research and development [3]. In contrast, the average cost of new drug and biologics is $2.87 billion when factoring in the post-approval research and development costs, according to figures released in May 2016 by The Tufts Center for the Study of Drug development (CSDD) [4]. For pharmaceutical companies that have launched more than four drugs, the median cost is closer to a staggering $5.3 billion according to analysis by industry expert Matthew Herper of Forbes [5].

The coronavirus pandemic is having a peculiarly American side effect: Gun sales are surging. The stocks of publicly traded guns and ammo companies American Outdoor Brands Corp., Vista Corp., and Sturm Ruger & Co. are up. Sales leaped by more than 19% in January and 17% in February, compared with the same months in 2019, according to Small Arms Analytics & Forecasting. Gun buyers in the United States bought an estimated 1.24 million guns in, January up from 1.04 million the year before, and 1.36 million in February, up from 1.26 million the year before, according to Small Arms Analytics, which bases estimates on background check data. Those millions of new guns are in addition to the approximately 400 million guns American already own.

On March 16, 2020, the White House Office of Science and Technology Policy (OSTP) announced the availability of an open research dataset on COVID-19, as well as stated a call to action for the nation's artificial intelligence (AI) researchers to help scientists fight the disease. Established in 1976, the OSTP provides scientific and technological advice to the President and the Executive Office, among other duties. The CORD-19 (COVID-19 Open Research Dataset) is the result of a collaboration between the Allen Institute for Artificial Intelligence (AI2), Microsoft, the National Library of Medicine at the National Institutes of Health (NIH), Georgetown University's Center for Security and Emerging Technology (CSET), and the Chan Zuckerberg Initiative in response to a request by the White House Office of Science and Technology Policy. Together these institutions issued a joint call to action to the world's AI researchers to create text and data mining tools to help accelerate COVID-19 research. The Allen Institute's Semantic Scholar has an adaptive feed on COVID-19 research.

Interpol concluded a partnership with a South Korean artificial intelligence startup aimed at tracking and combating cryptocurrency-related crimes on the darknet. The organisation will use a new data analysing engine to track illegal activity. The darknet has been a pain in the neck for the police and law enforcement agencies for years. Criminals steal people's confidential information and sell it for illegal purposes, at the same time making it nearly impossible to track or catch them. Despite the blockchain network is completely transparent and all transactions are traceable, it doesn't matter as long as the parties conducting the transaction remain anonymous.