Virtualitics Inc., a Pasadena-based advanced analytics and AI company, has launched AI software that aims to help enterprises and government agencies make reliable business decisions faster. In a statement, the company said the Virtualitics AI Platform, launched Wednesday, makes use of clear, explainable no-code AI modeling, with patented technology based on over 11 years of research at Caltech and NASA's Jet Propulsion Laboratory. The platform makes it easy for businesses to embed AI in their operations, allowing customers to Explore, Predict, Prescribe and Act, the statement said. "Enterprises today struggle to implement AI successfully and embed it into the flow of work," Michael Amori, Founder and CEO of Virtualitics, said. "One of the big reasons for this is because business users and analysts can't understand the output of AI applications and therefore don't trust it. Virtualitics AI Platform solves this problem by making AI both understandable and accessible to anyone in the business."

In early spring 2020, Smithfield, Tyson, and other industrial food suppliers warned that upwards of millions of pounds of meat could disappear from the U.S. supply chain as a result of the coronavirus. Although it now appears these fears were overblown or possibly a ploy to bolster exports (excepting pork products like pepperoni), tens of thousands of slaughterhouse workers around the world have tested positive for COVID-19, and more than 90 of them have died from the virus. As the health crisis stretches on, the threat to meatpacking, meat processing, and distribution center employees has researchers hunting for a new production model. Even with physical distancing protocols and personal protective equipment like face shields and masks, plant closures are looming -- and the idea of automation is rapidly gaining ground. The U.S. meatpacking industry employed nearly 600,000 workers -- a large portion of whom are immigrants -- at wages averaging $15.92 an hour in 2019.

Over 100 Guyanese students will benefit from the Spark Programme – an artificial intelligence and leadership initiative – aimed at equipping them to grow their technological skills and create economic opportunities. The programme is in collaboration with two overseas-based Guyanese, Professor and Scientist at the University of Michigan, Jason Mars and Denise Hilliman, a former science educator and the Chief Executive Officer of Lead Mindset – leadership curriculum. The programme is being facilitated by the Ministry of Education. Mars and Hilliman will be sharing their knowledge of artificial intelligence, technology and leadership with students here. "We have come together to do something for our people and to bring the successes we have in the diaspora and come back home to spark the pathway to ignite innovation and perhaps a transformation in technology and economic prosperity by working on what is on the minds of our young people," Mars said at the launch of the programme at the National Centre for Educational Resource Development (NCERD), Kingston, Georgetown.

We propose a unified data-driven reduced order model (ROM) that bridges the performance gap between linear and nonlinear manifold approaches. Deep learning ROM (DL-ROM) using deep-convolutional autoencoders (DC-AE) has been shown to capture nonlinear solution manifolds but fails to perform adequately when linear subspace approaches such as proper orthogonal decomposition (POD) would be optimal. Besides, most DL-ROM models rely on convolutional layers, which might limit its application to only a structured mesh. The proposed framework in this study relies on the combination of an autoencoder (AE) and Barlow Twins (BT) self-supervised learning, where BT maximizes the information content of the embedding with the latent space through a joint embedding architecture. Through a series of benchmark problems of natural convection in porous media, BT-AE performs better than the previous DL-ROM framework by providing comparable results to POD-based approaches for problems where the solution lies within a linear subspace as well as DL-ROM autoencoder-based techniques where the solution lies on a nonlinear manifold; consequently, bridges the gap between linear and nonlinear reduced manifolds. We illustrate that a proficient construction of the latent space is key to achieving these results, enabling us to map these latent spaces using regression models. The proposed framework achieves a relative error of 2% on average and 12% in the worst-case scenario (i.e., the training data is small, but the parameter space is large.).

Non-degradable plastic waste stays for decades on land and in water, jeopardizing our environment; yet our modern lifestyle and current technologies are impossible to sustain without plastics. Bio-synthesized and biodegradable alternatives such as the polymer family of polyhydroxyalkanoates (PHAs) have the potential to replace large portions of the world's plastic supply with cradle-to-cradle materials, but their chemical complexity and diversity limit traditional resource-intensive experimentation. In this work, we develop multitask deep neural network property predictors using available experimental data for a diverse set of nearly 23000 homo- and copolymer chemistries. Using the predictors, we identify 14 PHA-based bioplastics from a search space of almost 1.4 million candidates which could serve as potential replacements for seven petroleum-based commodity plastics that account for 75% of the world's yearly plastic production. We discuss possible synthesis routes for these identified promising materials. The developed multitask polymer property predictors are made available as a part of the Polymer Genome project at https://PolymerGenome.org.

Throughout my career as an unwavering advocate of AI and AI for good, I've had the pleasure of meeting, connecting with, and absorbing wisdom from a variety of individuals. As part of my 10-Part Series of The 9 Inspirational Women Leaders In AI Shaping The 21st Century, I was honored to converse with Linda Avery. Linda is the strategic voice, and visionary for data and analytics at Verizon, focused on using the power of data and AI across the enterprise. Linda joined Verizon in September 2019 and has grown the AI & Data organization to approaching 1,000 contributors by the end of 2021, including teams dedicated to Data Governance, Data Architecture and Engineering, and an AI Center, covering a broad range of disciplines from AI Ethics to Industrialization and Digital Twins. NEW YORK, UNITED STATES - 2020/10/15: Verizon store front displays the 5G network near Grand Central ... [ ] Terminal.

The Ukraine defense ministry announced that it is now using facial recognition technology from an American startup to combat misinformation, identify the dead, and expose Russian assailants. The technology, which is like a search engine for faces that aggregates data from millions of social media users across the open web, had previously stirred controversy due to privacy complaints. After the war broke out, the American-based artificial intelligence company Clearview reached out to Ukraine's government, offering its services free of charge. This week, the collaboration became official and Clearview's facial recognition tech is now claimed to be used for security purposes, such as vetting people of interest at checkpoints. Clearview claims that it has amassed a database of over 10 billion photos posted publically on the internet from sites like Facebook, Instagram, Flickr, and Getty Images.

When the robots rise up, they won't take your life. They'll take your job, particularly those in fields primed for automation, like manufacturing, trucking, and customer service. Technologists, economists, and policymakers believe this future is all but inevitable, and say it's time to begin thinking seriously about how to ensure artificial intelligence advances humanity--and improves the economy, without leaving the middle class behind. Two economists who recently left Washington say the answer lies in ensuring the government provides enough of a safety net to help middle class Americans navigate the coming transition. Jason Furman and Gene Sperling--former chief economic advisors to President Obama--prefer to think of it as a bridge, not a net, that will help people reach the future.

A China Eastern flight carrying 132 people crashed Monday. A domestic Chinese flight with 132 passengers plummeted into the mountains of southern China on Monday, likely leaving all passengers dead and investigators launching a probe into the cause. Chinese President Xi Jinping has instructed the country's emergency services to "organize a search and rescue" operation and "identify the causes" of the Boeing 737-800 crashing, according to state media. Former chairman of the National Transportation Safety Board Jim Hall told Fox News Digital on Monday that it would be "irresponsible" to speculate what caused the crash so soon after the incident, but described how the NTSB carries out investigations into major commercial crashes. This screen grab taken from video from The Paper and received via AFPTV on March 21, 2022 shows ambulances turning off onto a side road upon arrival after a China Eastern reportedly crashed in Teng County in Wuzhou City, Guangxi province.

An artificial intelligence model was able to create 40,000 chemical weapons compounds in just six hours, after being given the task by researchers. A team of scientists were using AI to look for compounds that could be used to cure disease, and part of this involves filtering out any that could kill a human. As part of a conference on potentially negative implications of new technology, biotech startup Collaborations Pharmaceuticals, from Raleigh, North Carolina, 'flipped a switch' in its AI algorithm, and had it find the most lethal compounds. The team wanted to see just how quickly and easily an artificial intelligence algorithm could be abused, if it were set on a negative, rather than positive task. Once in'bad mode' the AI was able to invent thousands of new chemical combinations, many of which resembled the most dangerous nerve agents in use today, according to a report by The Verge.