SAN FRANCISCO, Oct. 24, 2019 (GLOBE NEWSWIRE) -- MICRON INSIGHT -- Micron Technology, Inc. (Nasdaq: MU), today announced a powerful new set of high-performance hardware and software tools for deep learning applications with the acquisition of FWDNXT, a software and hardware startup. When combined with advanced Micron memory, FWDNXT's (pronounced "forward next") artificial intelligence (AI) hardware and software technology enables Micron to explore deep learning solutions required for data analytics, particularly in IoT and edge computing. With this acquisition, Micron is integrating compute, memory, tools and software into a comprehensive AI development platform. This platform in turn provides the key building blocks required to explore innovative memory optimized for AI workloads. "FWDNXT is an architecture designed to create fast-time-to-market edge AI solutions through an extremely easy to use software framework with broad modeling support and flexibility," said Micron Executive Vice President and Chief Business Officer Sumit Sadana.

LOS ALAMOS, N.M., Oct. 22, 2019--A probabilistic artificial intelligence computer model developed at Los Alamos National Laboratory provided the most accurate state, national and regional forecasts of the flu in 2018, beating 23 other teams in the Centers for Disease Control and Prevention's FluSight Challenge. The CDC announced the results last week. "Accurately forecasting diseases is similar to weather forecasting in that you need to feed computer models large amounts of data so they can'learn' trends," said Dave Osthus, a statistician at Los Alamos and developer of the computer model, Dante. "But it's very different because disease spread depends on daily choices humans make in their behavior--such as travel, hand-washing, riding public transportation, interacting with the healthcare system, among other things. Those are very difficult to predict."

SAN FRANCISCO, Oct. 24, 2019 (GLOBE NEWSWIRE) -- MICRON INSIGHT -- Micron Technology, Inc. (MU), today announced a powerful new set of high-performance hardware and software tools for deep learning applications with the acquisition of FWDNXT, a software and hardware startup. When combined with advanced Micron memory, FWDNXT's (pronounced "forward next") artificial intelligence (AI) hardware and software technology enables Micron to explore deep learning solutions required for data analytics, particularly in IoT and edge computing. With this acquisition, Micron is integrating compute, memory, tools and software into a comprehensive AI development platform. This platform in turn provides the key building blocks required to explore innovative memory optimized for AI workloads. "FWDNXT is an architecture designed to create fast-time-to-market edge AI solutions through an extremely easy to use software framework with broad modeling support and flexibility," said Micron Executive Vice President and Chief Business Officer Sumit Sadana.

Over the last four years, more than 50,000 participants have developed and submitted over 114,000 artificial intelligence (AI) algorithms to improve everything from detection of lung cancer and heart disease, to monitoring ocean health and helping accelerate life-saving medical research as part of the annual Data Science Bowl . In partnership with PBS KIDS, this year's competition will look at advancements in early childhood education. The results will lead to better designed games and improved learning outcomes, empowering children, parents, caregivers and educators across the globe with insights into how young children learn through media and which approaches work best to help them build on foundational learning skills. The 90-day Data Science Bowl competition will award winning participants with a share of $160,000 in cash prizes. Research shows much of the most critical brain development in children takes place before they even reach kindergarten.

Businesses know that rich analytics capabilities are critical to remain competitive in today's reality. While Canadian executives may feel challenged by the immense amount of data they already have access to, they plan to continue investing in new and expanded data sources to enable them to better mitigate risk – and meet constantly shifting consumer expectations,

Nvidia has announced the launch of EGX Edge Supercomputing Platform designed to let organisations easily deploy the hardware and software necessary for high-performance, low-latency AI workloads. Instead of being deployed inside big data centres, an EGX deployment is designed to sit at the edge of the cloud which, Nvidia believes, makes it ideal for the next generation of use cases. "We've entered a new era, where billions of always-on IoT sensors will be connected by 5G and processed by AI," Jensen Huang, Nvidia founder and CEO, said at a keynote ahead of MWC Los Angeles earlier this week. "Its foundation requires a new class of highly secure, networked computers operated with ease from far away. "We've created the Nvidia EGX Edge Supercomputing Platform for this world, where computing moves beyond personal and beyond the cloud to operate at planetary scale," he added. The EGX stack includes an Nvidia driver, Kubernetes plug-in, Nvidia container runtime, and GPU monitoring tools, delivered through the Nvidia GPU Operator, which allows you to standardise and automate the deployment of all necessary components for provisioning GPU-enabled Kubernetes systems. Nvidia will certify hardware as'NGC Ready for Edge' that customers will be able to buy from partners such as Advantech, Altos Computing, ASRock RACK, Atos, Dell Technologies, Fujitsu, GIGABYTE, Hewlett Packard Enterprise, Lenovo, MiTAC, QCT, Supermicro, and TYAN. Nvidia says EGX is already being used by customers. At Walmart's Intelligent Retail Lab in Levittown, New York, for example, EGX enables real time processing of more than 1.6 terabytes of data generated each second to "automatically alert associates to restock shelves, open up new checkout lanes, retrieve shopping carts, and ensure product freshness in meat and produce departments." The EGX platform features software to support a wide range of applications, including Nvidia Metropolis, which can be used to power smart cities and build intelligent video analytics applications. The city of Las Vegas, for example, is using EGX to capture vehicle and pedestrian data to make its streets safer. San Francisco's Union Square Business Improvement District is using EGX to capture real-time pedestrian counts for local retailers. "We use our smartphones sporadically -- we type into it, or watch a movie now or then -- and frankly there are only seven and a half billion of us," Huang said. "In the case of sensors, it will be streaming all the time.

British startup FiveAI has today announced the launch of commuter research trials for its self-driving car technology, alongside motor insurance giant Direct Line. As part of the Streetwise Consortium, which also includes TRL, a 19km self-driving research route featuring human passengers will be launched in Croydon and Bromley to test out the technology. The invite-only trial will take place during the next two months, in which participants will be asked for insight on their experiences. Ultimately, the government-backed consortium hopes to provide data for a shared self-driving service for future London commuters. Transport secretary Grant Shapps said the trial is "a major step to rolling out the next phase of the UK's transport revolution".

My Ally, the world's only Talent Lifecycle Management (TLM) software provider for fast-growth companies and enterprise businesses, will be showcasing the Artificial Intelligence enabled Source-to-Retain platform at the Gartner ReimagineHR Conference, taking place October 28-30, 2019 in Orlando, Florida. As Talent Acquisition and HR Teams continue to report pains associated with finding, hiring, and onboarding the best talent quickly, the costs for these critical functions in organizations continue to rise. The Society for Human Resource Management states that the average cost to hire an employee in the United States is $4,129, with an average of about 42 days to fill a position. "We started My Ally with the vision of transforming the way companies all over the world discover, hire, and retain talent," said Deepti Yenireddy, CEO and Founder of My Ally. "We know there is a lot of efficiencies and improvements that AI can offer, and we believe Human Resources should be leaders in ushering in the AI assistants and bots to their organizations. We believe AI needs HR, not the other way around."

In recent years, machine learning and artificial intelligence have made a way into all areas of homes, lives and businesses. Today, the technology is becoming increasingly ubiquitous such as from AI assistants like Alexa or Siri, speech translator, GPS finding location, smart devices etc. These days, you can find exciting evidence of machine learning innovation in marketing today as it is applied to pay-per-click, created more intelligent email campaigns and chatbots. Here, GoodFirms has conducted a survey based on AI and Machine Learning for PCC Campaign Management. In this research, PPC Gurus (Duane Brown, Ed Leake, Gianluca Binelli, Jeff Sauer, Kirk Williams, Larry Kim, Luca Senatore, Martin Roettgerding, Navah Hopkins, Patrick Gilbert) were contacted that are experts in digital marketing.

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.