This is because workers would be able to shift to taking on more varied and higher-level tasks, and factories could produce a greater variety of products. That's the idea behind a prototype smartphone app Purdue University researchers have developed that allows a user to easily program any robot to perform a mundane activity, such as picking up parts from one area and delivering them to another. The setup could also take care of household chores -- no more plants dying because you forgot to water them. Purdue researchers present their research on the embedded app, called VRa, on June 23 at DIS 2019 in San Diego. The platform is patented through the Purdue Research Foundation Office of Technology Commercialization, with plans to make it available for commercial use.

PayPal is no stranger to fraud. As one of the Internet's first online payment services, PayPal has been exposed to every type of wire fraud imaginable (and some beyond imagination). Sometimes the fraudsters had the upper hand, but now, thanks to deep learning (DL) models running on high performance computing (HPC) infrastructure, PayPal is leveraging its vast repository of fraud data to keep the fraudsters on the run. PayPal is one of the classic success stories of the Internet era. Founded during the dot-com heyday of 1998, the company carved out a lucrative niche – facilitating secure payments online -- early in the Internet's development.

Imagine a scenario where you need your car's onboard navigation system to place an emergency call, but it won't. Or arriving extra early for every international flight because airport security scanners never recognize your face. For many people--especially people of color and women--these scenarios can be a frustrating reality. That's because the AI that's supposed to make life easier for us all doesn't include diverse enough data to work for everyone. This is a big problem, but one that can be fixed.

Children on the autism spectrum often suffer from other medical conditions. As many as one-fifth of those diagnosed with the neurodevelopmental disorder, which affects communication and behavior, have epilepsy, for example, according to research on the subject. Probably Genetic, which recently graduated from the startup accelerator Y Combinator, wants to test the DNA of children with autism to provide them early diagnoses of more than 15 severe genetic diseases that are often grouped under the initial autism diagnosis. Using machine learning and direct-to-consumer DNA tests, Probably Genetic hopes to provide families of children on the spectrum with more complete and correct diagnoses and a path to appropriate treatment and therapy. "There is really low awareness still in the medical community for a lot of these diseases," Probably Genetic co-founder and chief executive officer Lukas Lange tells TechCrunch.

"Zero Hunger" is one of the 17 UN SDGs expected to be achieved by 2030. According to the United Nations, up to 80% of food consumed in most developing countries are produced by smallholder farmers who, however, account for approximately 50% of the 815 million people suffering from hunger worldwide. At the Summit's session on AI and Agriculture, Justin Gong, Co-founder and Vice President of XAG, together with other panel experts from Microsoft, Tata Group and Connecterra has proposed projects and initiatives to exploit new possibilities of AI technology to improve food security and end hunger. Artificial Intelligence, through continuously analysing massive data related to climate, lands, crop growing, etc., while automatically designing and optimising algorithms for decision-making, can help farmers diagnose plant diseases, predict natural disasters and employ appropriate resources to close the yield gap. At XAG, AI-powered intelligent devices such as drones and sensors have been leveraged to establish digital farming infrastructure in rural areas and enable precision agriculture which, for example, accurately target pesticides, seeds, fertilisers and water to wherever it is needed.

There seems to be a general consensus that AI will by no means make the work done by financial professionals redundant since results produced by AI models still require human interpretation, says the writer. Artificial intelligence (AI) is nothing new. It has been around since the 50s. It is only now that we possess the processing power to utilise it properly. It is already embedded in many people's lives.

Published today in the peer-reviewed journal Radiology, an IBM Research team created a new artificial intelligence (AI) model that can predict breast cancer malignancy and identify normal digital mammography exams as accurately as radiologists. Mammography, a low-dose x-ray procedure to image breasts, is considered the best breast cancer screening test available according to the American Cancer Society. However, mammograms are not always accurate. According to a U.S. 10-year study published in the New England Journal of Medicine, 23.8 percent of study participants had at least one false positive mammogram where breast cancer was not actually present. Furthermore, the American Cancer Society estimates that one in five screening mammograms are false-negatives that fail to detect existing breast cancer.

In this episode of the Inside the Strategy Room podcast, senior partner Michael Bender sits down with Sean Brown to tease out the real meaning of digital-analytics transformations. They also talk through the role CFOs can take on to drive successful change efforts. Welcome to Inside the Strategy Room. Today, we're joined by Michael Bender, a senior partner in our Chicago office and the global coleader of McKinsey Digital and Analytics. We sat down with Michael in London, where he had just presented to our Global CFO Forum on the role CFOs can play in driving digital transformations. We also covered the nature of digital transformations more generally, how digital and analytics go hand in hand, and the challenges companies can face when working to adopt both. Michael, tell us just a little bit more about what is digital? What is a digital transformation? Michael Bender: Sean, it's interesting that we get this question all the time.

Companies and entire industries are looking to harness data analytics to make more accurate and effective decisions, within and across organizations. Such real-time and accurate insights have enabled boards and their management to be more effective in conducting their duties. Artificial intelligence (AI) mimics the learning function of the human brain, which means it could be deliberately or accidently corrupted and even adopt human biases, potentially resulting in mistakes and unethical decisions. Control of AI systems by the wrong hands is also a concern. Any AI system failure could have profound ramifications on security, decision-making and credibility, and may lead to costly litigation, reputational damage, regulatory scrutiny, and reduced stakeholder trust and profitability.