For Google it was a historic announcement: a declaration that it had won the race to achieve "quantum supremacy" – the moment that a futuristic quantum computer performed a task that stumped even the most powerful standard computer in the world. But for all the fanfare, which saw Google's CEO Sundar Pichai compare the feat to building the first rocket to reach space, the claim has sparked a bunfight. The tech firm's rival, IBM, was swift to dismiss the excitement. Google has not, it asserts, achieved the highly prized goal of quantum supremacy. Google published its claim in the journal Nature on Wednesday after an earlier report on the work appeared briefly on a Nasa website last month. The paper describes how a team led by John Martinis, leader of the research team working on quantum supremacy, built a superconducting quantum processor named Sycamore that harnesses the weirdness of quantum physics to crunch through thorny problems.

The MLOps Conference took place earlier this week at Hudson Mercantile in New York City. Experts from the New York Times, Twitter, Netflix and Iguazio, the host company, spoke about best practices and machine learning implementation throughout a variety of different organizations. I learned of the technological void that exists when data scientists want to implement machine learning. With this new context in mind, I can approach conversations with our data team from a new perspective, and take the time to understand how we can implement new models on our team. Machine learning as a technology has been around for more than 50 years, beginning with Arthur Samuel's pioneering work at IBM where his program helped the computer improve with each game of checkers it played in 1952.

Last March, Google took the wraps off of Coral, a collection of hardware development kits and accessories intended to bolster the development of machine learning models at the edge. It launched in select regions in beta, but the tech giant today announced that it's graduating to a "wider" and global release. All Coral products -- including the $150 Coral Dev Board, the $74.99 Coral USB Accelerator, and the $24.99 5-megapixel camera accessory -- are available for sale at electronics retailer Mouser and for large-volume sale through Google's sales team. The company says that by the end of the year, it'll expand distribution into new markets including Taiwan, Australia, New Zealand, India, Thailand, Singapore, Oman, Ghana, and the Philippines. Coinciding with Coral's general availability, the Coral website -- which now lives at Coral.ai -- has been revamped with better organization for docs and tools, testimonials, and "industry-focused" pages. Additionally, it links to a new set of examples aimed at providing solutions to common AI problems, such as image classification, object detection, pose estimation, and keyword spotting.

To highlight these largely unsung benefits, gaming PC maker HP Omen and creative agency Wieden Kennedy Shanghai created a demonstration using a tool called The Gamewaves Scanner at ChinaJoy, China's largest digital entertainment expo. The exhibit used cutting-edge technology to measure brain activity in real time, showcasing how people respond to moments that require teamwork, responsiveness, mental stamina, focus and memory. The experience was titled Achieving Gamefulness, and it was the start of an integrated campaign set to launch across China. To synthesize their findings for a wider audience, HP Omen and W K Shanghai created a trio of 30-second shorts: "Achieve Mental Stamina," "Achieve Teamwork" and "Achieve Focus." The arc features a troop of gamers being led by supreme humans called The Masters as they hope to achieve the highest level of enlightenment.

DUBLIN--(BUSINESS WIRE)--Public-service executives in Europe are optimistic and enthusiastic about the impact of artificial intelligence (AI) on government operations and services but face challenges implementing the technology, according to a study issued today by Accenture (NYSE: ACN). The study -- based on a survey of 300 government leaders and senior information technology (IT) decision-makers in Finland, France Germany, Norway and the U.K.-- found that the vast majority (90%) of respondents believe that AI will have a high impact on their organizations over the coming years. In addition, nearly the same number (86%) said that their organization plans to increase its spending on AI next year. Customer service and fraud & risk management are the two operational areas favored most for public service AI deployments, cited by 25% and 23% of respondents, respectively. In addition, respondents most often cited increased efficiencies, cost or time savings, and enhanced productivity as the greatest anticipated benefits from their AI investments.

The future of computing is one of the strongest transformational forces on our planet. Everything we touch has built-in computing capabilities and is generating tremendous volumes of data. The impact is not only speeding up our daily lives, but also more traditional industrial sectors, including chemistry. Last year at the ACS Fall Meeting 2018 in Boston, IBM Research released IBM RXN for Chemistry, a cloud-based app that takes the idea of relating organic chemistry to a language. The magic behind the app is a state-of-the-art neural machine translation method, which can predict the most likely outcome of a chemical reaction using sequence-to-sequence (seq2seq) models.

Ottawa-based MindBridge Analytics announced, on Wednesday, a partnership with the Bank of Canada that will see the FinTech and AI startup participate in a proof-of-concept project to track payment transactions. "Working alongside a leading central bank accelerates MindBridge's capabilities in delivering impactful solutions." Through the partnership, Bank of Canada will utilize MindBridge's AI platform, which analyzes large datasets to detect deviating patterns of activity and errors. The financial institution is hoping to develop an AI solution that can spot abnormalities in payment transactions. A core function of the Bank of Canada is to provide funds-management services to the Government of Canada, as well as other customers.

Machine learning could become a new weapon in the fight against Medicare fraud. Machine learning could become a useful tool in helping to detect Medicare fraud, according to a new study, potentially reclaiming anywhere from $19 billion to $65 billion lost to fraud each year. Researchers from Florida Atlantic University's College of Engineering and Computer Science recently published the world's first study using Medicare Part B data, machine learning and advanced analytics to automate fraud detection. They tested six different machine learners on balanced and imbalanced data sets, ultimately finding the RF100 random forest algorithm to be most effective at identifying possible instances of fraud. They also found that imbalanced data sets are more preferable than balanced data sets when scanning for fraud.

In July of 2016, I left Tampa, Florida, to go on a life journey exploring coworking spaces around the world. I started this coworking exploration to experience, first hand, the management and culture variations in different offices and to learn how each community's culture is created and maintained. So far I have worked remotely in 16 states, 2 provinces, 3 countries, and over 30 coworking spaces.

Three years ago, artificial intelligence pioneer Geoffrey Hinton said, "We should stop training radiologists now. It's just completely obvious that within five years, deep learning is going to do better than radiologists." Today, hundreds of startup companies around the world are trying to apply deep learning to radiology. Yet the number of radiologists who have been replaced by AI is approximately zero. At least for the short term, that number is likely to remain unchanged.