China is shaping up to be the first real test of Big Tech's ambitions in the world of carmaking, with giants from Huawei Technologies Co. to Baidu Inc. plowing almost $19 billion into electric and self-driving vehicle ventures widely seen as the future of transport. While Apple Inc. has long had plans for its own car and Alphabet Inc. has Waymo, its autonomous driving unit, the size -- and speed -- of the move by China's tech titans puts them at the vanguard of that broader push. The lure is an industry that's becoming increasingly high tech as it pivots away from the combustion engine, with sensors and operating systems making cars more like computers, and the prospect of autonomy re-envisioning how people use will them. As the world's biggest market for new-energy cars, China is a key battlefield. Established automakers like Volkswagen AG and General Motors Co. are already slogging it out with local upstarts such as market darling Nio Inc. and Xpeng Inc.

PHILADELPHIA--(BUSINESS WIRE)--The Business Intelligence Group today announced that Bright Machines was named a winner in its Artificial Intelligence Excellence Awards program. Bright Machines is a full-stack technology company offering a new approach to AI-enabled manufacturing. The company's flagship solution, Bright Machines Microfactories, combines intelligent software and adaptive robotics to automate repetitive assembly and inspection tasks, enabling manufacturers to quickly deploy autonomous assembly lines that can scale based on market demand. In less than three years, they have achieved strong momentum across multiple industry verticals, particularly with customers seeking to re-shore manufacturing and accelerate product innovation. "Our mission from day one has been to enable our customers to increase the speed, scalability, and flexibility of their manufacturing process. By applying advanced machine learning, computer vision, 3D simulation, and cloud computing to the factory floor, we can bring new levels of innovation and productivity to their operations," said Amar Hanspal, Bright Machines CEO and co-founder.

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Mumbai (Maharashtra) [India], May 7 (ANI/NewsVoir): Since the dawn of the 2000s, Artificial Intelligence (AI) has been making waves through its penetration into various sectors. While AI helps increase efficiency and speed in a system, the lack of feedback when faced with errors has been a glaring concern. Recently developed Explainable Artificial Intelligence (XAI) technology tackles this issue by analyzing data to provide users with explanations for given issues and activities. Utilizing this technology to create investment strategies, Elystar aims to increase net returns by reducing machine/AI-made errors and thereby successfully leveraging the superior insights provided by AI. "Artificial Intelligence in finance is a relatively new concept that is still being explored and experimented upon. While few of the firms experimenting are sparingly using it for short-term trading, we have spent the past 15 months developing models to use it for long-term investments. One simple way to look at this concept is to compare it with Microsoft Excel. While Excel is used in different fields and by different people, it is used in various ways and forms. Similarly, AI has a number of variations in which it can be utilized, so no two approaches may be completely the same. AI not only helps us scale and analyze data rapidly, but the integration of Explainable AI allows us to understand and eliminate unwarranted biases to create a sound investment strategy," said Dr Satya Gautam Vadlamudi, Founder and CEO of Elystar.

ElectrifAi, one of the world's leading companies in practical artificial intelligence (AI) and pre-built machine learning (ML) models, today announced that it has achieved Amazon Web Services (AWS) Machine Learning Competency status in the new Applied Artificial Intelligence (Applied AI) category. This designation recognizes that ElectrifAi has demonstrated deep experience and expertise in building or integrating practical ML solutions on AWS. AWS Partners recognized as part of the AWS Machine Learning Competency expansion help customers take advantage of intelligent solutions to drive business optimization, customer revenue growth and cost reduction. This is done by creating, automating, and managing end-to-end ML workflows with machine intelligence. The AI and ML driven applications are maturing rapidly and creating new demands on enterprises.

Procore Technologies, Inc., a leading provider of construction management software, today announced it has acquired INDUS.AI, makers of an artificial intelligence-powered analytics platform for the construction industry. This acquisition adds computer vision capabilities to the Procore platform, helping owners, general contractors, and specialty contractors realize greater efficiencies, safety, and profitability. Terms of the transaction are not being disclosed. This press release features multimedia. This acquisition adds computer vision capabilities to the Procore platform, helping owners, general contractors, and specialty contractors realize greater efficiencies, safety, and profitability.

If you're a parent or often find yourself needing to wrangle a group of people in your household, Google's latest Assistant update might be helpful. It's expanding the Broadcast tool that was previously limited to its smart speakers and displays to iPhones and Android devices. The company also announced a set of new features for the Assistant, including stories, games, songs and a Mother's Day surprise. Broadcast lets you send a message to all compatible devices at once, and you can create groups to specify who you want to reach. Google allows you to set up a Family group for up to six of your relatives, and the expansion being announced today will let you reach these members on their phones too. Just as they already could from a Nest speaker or display, your contact can now reply to your message from their Android or iPhone.

The 2021 Cadillac Escalade is available with the latest version of GM's hands-free Super Cruise highway driving aid. Fox News Autos Editor Gary Gastelu lets it take him for a ride. General Motors is developing autonomous vehicles through its Cruise division, which is already testing the vehicles on the streets of San Francisco without a driver behind the wheel, but you won't be able to buy one. The vehicles are intended for use in a ride-hailing service the company is hoping to launch in select cities soon, including Dubai where it recently signed a deal to become the city's exclusive self-driving taxi service. The Cruise Origin is a fully autonomous electric taxi GM plans to begin producing soon.

Game theory is known to be a useful tool in the study of Machine Learning (ML) and Artificial Intelligence (AI) Multi-Agent interactions. One basic component of these ML and AI systems is the exploration-exploitation trade-off, a fundamental dilemma between taking a risk with new actions in the quest for more information about the environment (exploration) and repeatedly selecting actions that result in the current maximum reward or (exploitation). However, the outcome of the exploration-exploitation process is often unpredictable in practice and the reasons behind its volatile performance have been a long-standing open question in the ML and AI communities. Dr Stefanos Leonardos and Assistant Professor Georgios Piliouras, researchers from the Singapore University of Technology and Design (SUTD), applied analytical tools from the theory of dynamical systems in the study of multi-agent systems and established a deep connection between exploration-exploitation and Catastrophe Theory (Figures 1 and 2). The latter is a branch of mathematics that formally explains phase transitions in all kinds of natural systems ranging from the transition from water to ice and disease outbreaks to collapses of financial markets.

LOS ALAMOS, N.M., April 22, 2021--A new machine-learning model that generates realistic seismic waveforms will reduce manual labor and improve earthquake detection, according to a study published recently in JGR Solid Earth. "To verify the efficacy of our generative model, we applied it to seismic field data collected in Oklahoma," said Youzuo Lin, a computational scientist in Los Alamos National Laboratory's Geophysics group and principal investigator of the project. "Through a sequence of qualitative and quantitative tests and benchmarks, we saw that our model can generate high-quality synthetic waveforms and improve machine learning-based earthquake detection algorithms." Quickly and accurately detecting earthquakes can be a challenging task. Visual detection done by people has long been considered the gold standard, but requires intensive manual labor that scales poorly to large data sets.