Diagnosing rare genetic disorders is difficult. Because cases are few and far between, it makes it harder to train medical professionals in what to look for. This is precisely the kind of activity that artificial intelligence can make easier. A new app called Face2Gene is giving doctors a second opinion on their diagnoses, using machine learning and neural networks. It looks for certain tell-tale facial features and presents doctors with a likely list of congenital and neurodevelopmental disorders.

Amazon Web Services (AWS) launched general availability of its fully-managed Lake Formation platform designed to help organizations better manage their data lakes. The service helps with the building, securing, and managing of those data repositories. Lake Formation, which was initially announced at the AWS re:Invent show late last year, is built on AWS' Glue extract, transform, and load (ETL) service. It automates the provisioning and configuring of storage; crawls the data to extract schema and metadata tags; automatically optimizes the partitioning of the data; and transforms the data into formats like Apache Parquet and ORC for easier analytics. Data can be ingested from different sources using pre-defined templates.

The insurance industry, after the trade market, is another sector where it is hard to predict the next big paradigm shift. Given the tentative stability and natural catastrophes, insurance companies often stand on a trembling ground and confront massive challenges, even when i comes to adopting seamless and intuitive digital solutions such as Artificial Intelligence in Insurance. Research N Reports has added a report, titled "Global Artificial Intelligence in Insurtech Market Size, Status and Forecast 2025," which provides an overview of the various factors enabling growth in the market. The statistical report offers a prime wellspring of applicable information for global business progress. What will be the market size and growth rate in the forecast year?

In a provocative op-ed in the New York Times last week, PayPal and Palantir founder Peter Thiel argued that artificial intelligence is "a military technology." So, he asks, why are companies like Google and Microsoft, which have opened research labs in China to recruit Chinese researchers for their cutting-edge AI research, "sharing it with a rival"? Thiel's op-ed caused a big splash in the AI community and frustrated experts in both AI and US-China relations. An outspoken Trump backer, Thiel has been a leading voice pushing for tech to be more aligned with what he sees as America's defense interests -- and his messages have been influential among conservative intellectuals. Critics pointed out that Thiel had failed to disclose that his company, Palantir, has defense contracts with the US government totaling more than $1 billion, and that he might benefit from portraying AI as a military technology (a characterization of AI that experts dispute).

Understanding big data and artificial intelligence is not something reserved for computer scientists, said Kirk Borne, principal data scientist for the international consulting firm, Booz Allen Hamilton. Manipulating massive amounts of data that are becoming available will affect every form of intellectual and business pursuit. "Data literacy is a way of thinking, not a thing to think about," Borne told attendees of BDA Edcon, the International Big Data and Analytics Education Conference hosted by University of Maryland University College on June 3 and 4. The conference explored how the convergence of big data analytics, artificial intelligence and cognitive computing can be implemented into teaching and learning experiences today to meet industry demand. The two-day event included the final judging and presentation of awards for the annual Global Analytics Competition. Data literacy is "a way of business, a way of doing whatever we do in the world. It really is for everyone, not just for data scientists," according to Borne.

By carrying out advanced experiments on neuronal cultures and large scale simulations, a group of scientists from Bar-Ilan University in Israel claims to have created a new type of ultra-fast artificial intelligence algorithm. This algorithm is based on the dynamics of the human brain, which, despite computing at a much slower rate than modern computers, is extremely fast and efficient. In an article published today in the journal Scientific Reports, researchers claim to be rebuilding the bridge between neuroscience and advanced artificial intelligence algorithms that, they say, has taken a backseat for almost 70 years. "The current scientific and technological viewpoint is that neurobiology and machine learning are two distinct disciplines that advanced independently," the study's lead author, Prof. Ido Kanter, of Bar-Ilan University's Department of Physics and Gonda (Goldschmied) Multidisciplinary Brain Research Center said in a press release. "The absence of expectedly reciprocal influence is puzzling."

During your stay in a hospital, computer systems are collecting and analyzing all sorts of data about you. In the background of all the beeping and gadgetry, an electronic medical record contains thousands of bits of information about your medical history, vital signs and laboratory results. Sentara Healthcare is now deploying artificial intelligence to use that data to stop patients from contracting life-threatening sepsis. Earlier this year the system launched a sepsis prediction tool that alerts doctors and nurses when a patient is at risk of developing the deadly infection. The tool "looks at relationships in order to predict what might happen in the future," said Dr. David Mohr, Sentara's vice president of clinical informatics and transformation.

It may not help you get through the airport faster, but artificial intelligence (AI) can now give you information on wait times at Pittsburgh International Airport security checkpoints in real time. The airport recently announced a partnership with Zensors, a Pittsburgh-based company that applies AI to feeds from airport security cameras to estimate wait times at the airport's three Transportation Security Administration (TSA) checkpoints on a minute-by-minute basis. Wait-time information is then posted on the airport's information screens and website, including predictions about whether wait times will increase or decrease. Zensors' AI observes passenger volume and also includes factors like time of day and TSA staffing levels to make its estimates. "We know security can be a frustration for travellers and having accurate wait estimates can help set expectations and aid in planning trips," said Pittsburgh International Airport CEO Christina Cassotis.

At a conference on the future challenges of intelligence organizations held in 2018, former Director of National Intelligence Dan Coats argued that he transformation of the American intelligence community must be a revolution rather than an evolution. The community must be innovative and flexible, capable of rapidly adopting innovative technologies wherever they may arise. Intelligence communities across the Western world are now at a crossroads: The growing proliferation of technologies, including artificial intelligence, Big Data, robotics, the Internet of Things, and blockchain, changes the rules of the game. The proliferation of these technologies – most of which are civilian, could create data breaches and lead to backdoor threats for intelligence agencies. Furthermore, since they are affordable and ubiquitous, they could be used for malicious purposes.

In recent years, the number of biomedical publications freely available in the literature has grown enormously, resulting in a rich source of untapped new knowledge. However, most biomedical data is buried in the form of unstructured text, and their exploitation requires expert knowledge and time-consuming manual curation of published articles. Hence the development of novel methodologies that can automatically analyze textual sources, extract facts and knowledge, and produce summarized representations that capture the most relevant information in a timely fashion. INtERAcT represents a novel approach to infer interactions between molecular entities extracted from the literature using an unsupervised procedure that leverages recent developments in automatic text mining and analysis. INtERAcT implements a new metric that acts on the vector space of word representations to estimate an interaction score between two molecules.