Samsung made the announcement in a Korean press release this week. The company told Reuters it will be operating the research lab as a joint venture between two of its businesses. Samsung's mobile and consumer electronics arms will both use the facility to help develop new technologies. Samsung's use of AI was fairly limited until earlier this year. The launch of the company's Bixby digital assistant marked Samsung's intentions to gain a position in consumer AI, an increasingly competitive segment of the technology market.

A Bangalore-based startup is claimed to have become the first company in the world to successfully complete a difficult 20-part challenge in Artificial Intelligence created by Facebook in 2015. Using a unique approach, DataVal Analytics successfully completed all 20 tasks of the test, known as the (20) QA bAbi Tasks, with 100 per cent accuracy. The test, hosted by Facebook AI Research (FAIR), assesses the ability of AI-based programs to perform text understanding and reasoning. According to a media release, DataVal Analytics, which has its head office in Chicago but operations office in Bangalore, has been founded by veterans from the Indian Army – Lt Col Shashi Kiran (Veteran) and Lt Col Naveen Xavier (Veteran). The team is mentored by the leading entrepreneur, innovator, policy maker and development thinker, Sam Pitroda as chairman.

AWS IoT 1-Click, AWS IoT Device Management, AWS IoT Device Defender, AWS IoT Analytics, Amazon FreeRTOS, and AWS Greengrass ML Inference make getting started with IoT as easy as one click, enable customers to rapidly onboard and easily manage large fleets of devices, audit and enforce consistent security policies, and analyze IoT device data at scale. Amazon FreeRTOS is an operating system that extends the rich functionality of AWS IoT to devices with very low computing power, such as lightbulbs, smoke detectors, and conveyor belts. And, AWS Greengrass ML Inference is a new capability for AWS Greengrass that allows machine learning models to be deployed directly to devices, where they can run machine learning inference to make decisions quickly, even when devices are not connected to the cloud. To get started, visit: https://aws.amazon.com/iot "AWS IoT Device Management has helped streamline our device onboarding, which has enabled us to meet our planned production throughput for connected devices. With AWS doing the undifferentiated heavy lifting for our IoT platform, we can spend more time on our customers than on our infrastructure."

Newswire) Veritone, Inc. (NASDAQ: VERI), a leading provider of artificial intelligence (AI) insights and cognitive solutions, today announced that it has achieved Amazon Web Services (AWS) Machine Learning (ML) Competency status. This designation recognizes Veritone for offering solutions that enable prescriptive and predictive capabilities within customer workflows and applications. AWS ML Competency status designates Veritone as an AWS Partner Network (APN) member that has built solutions that help organizations solve their data challenges, enable machine learning and data science workflows or offer SaaS/API-based capabilities that enhance end applications with machine intelligence. Attaining the AWS ML Competency demonstrates to Veritone's customers that the company has ML expertise on AWS. "Achieving AWS ML Competency status recognizes Veritone's proven track record of making AI accessible and actionable to institutions and organizations by combining the most advanced processing engines across major cognitive functions with a suite of powerful applications and a proprietary orchestration layer informed by machine learning," said Chad Steelberg, chairman and chief executive officer of Veritone.

Teradata has announced today that Danske Bank, a financial services leader in the Nordics, has worked with Think Big Analytics, a Teradata company, to create and launch a state-of-art, AI-driven fraud detection platform that is already expected to meet 100 percent ROI in its first year of production. The engine uses machine leaning to analyze tens of thousands of latent features, scoring millions of online banking transactions in real-time to provide actionable insight regarding true, and false, fraudulent activity. By significantly reducing the cost of investigating false-positives, Danske Bank increases its overall efficiency and is now poised for substantial savings. "Application fraud is a critical, top of the agenda issue for banks, and there is evidence that criminals are becoming savvier by the day; employing sophisticated machine learning techniques to attack, so it's critical to use advanced techniques, such as machine learning to catch them," said Nadeem Gulzar, Head of Advanced Analytics, Danske Bank. "The bank understands that fraud is set to get worse in the near and long-term future due to the increased digitization of banking and the prevalence of mobile banking applications. We recognize the need to use cutting-edge techniques to engage fraudsters not where they are today, but where they will be tomorrow. Using AI, we've already reduced false positives by 50 percent and as such have been able to reallocate half the fraud detection unit to higher value responsibilities."

The Gluon interface currently works with Apache MXNet and will support Microsoft Cognitive Toolkit (CNTK) in an upcoming release. With the Gluon interface, developers can build machine learning models using a simple Python API and a range of pre-built, optimized neural network components. This makes it easier for developers of all skill levels to build neural networks using simple, concise code, without sacrificing performance. AWS and Microsoft published Gluon's reference specification so other deep learning engines can be integrated with the interface.

Deep learning tech is making itself at home in hospitals by helping radiologists examine medical scans for just a buck per image. Now, GE Healthcare is bringing that AI tech directly to the scanners, thanks to partnerships with NVIDIA and Intel. It announced that it will update 500,000 of its medical devices around the world with NVIDIA AI tech, most notably its Revolution Frontier CT scanner (below). The tech "is expected to deliver better clinical outcomes in liver lesion detection and kidney lesion characterization because of its speed," GE wrote in a press release. The tech will also be used in GE's advanced ultrasound imaging devices to provide visualization and quantification of data. "NVIDIA's GPUs accelerate reconstruction and visualization of blood flow and improve 2D and 4D imaging for ... interventional deployments," the company said.

POINT ROBERTS, WA--(Marketwired - November 20, 2017) - Investorideas.com, a global news source covering leading sectors including artificial Intelligence and robotics issues a sector snapshot and video showcasing companies using the technology, including Amazon.com, Apple co-founder Steve Wozniak also discusses the history and future of AI at Money20/20 and how he views the current state of the technology including self-driving cars (Tesla Motors). According to CBinsights.com over $15B has been poured into AI companies in the last 5 years. All the big companies are investing in AI and machine learning technology as a path to the future; Apple, Google, IBM, Intel, Microsoft, NVidia, Qualcomm, Tesla Motors, Square and Amazon are amid an ever-growing list of players. Research and Markets says "The global artificial intelligence market is expected to reach USD 35,870.0 million by 2025 from its direct revenue sources, growing at a CAGR of 57.2% from 2017 to 2025, whereas it is expected to garner around USD 58,975.4 million by 2025 from its enabled revenue arenas. The North American region is expected to dominate the industry due to the availability of high government funding, the presence of leading players, and strong technical base."

Silicon Valley investment giant Sequoia Capital has pumped $50m (£38m) into Bristol-headquartered artificial intelligence chip producer Graphcore – a major vote of confidence in the UK's booming startup scene. Sequoia is best known as an early investor in some of the technology sectors' most prominent names – including Apple, Oracle, Yahoo, Google, YouTube, PayPal, Instagram, WhatsApp and Airbnb. Nigel Toon, chief executive officer of Graphcore, said that Sequoia was a suitable fit for his company because of its understanding of the importance of machine learning and how this will "reshape computing". "We're not obsessed with raising money, we're obsessed with who we work with – our customers, our team, our partners and our investors," Mr Toon said. The cash injection will help Graphcore, which was founded last year, to accelerate growth to meet the expected global demand for its machine-intelligence processor, the company said.

A religion based around artificial intelligence is in the news again, this time helmed by Anthony Levandowski, a former member of Google's self-driving car team. His argument is that humans will eventually create AI that is more intelligent than we are, making it functionally god-like, so we might as well start planning for that eventuality. His thinking about the rise of super intelligent machines runs parallel to that of Elon Musk, who has been trumpeting the risks of artificial superintelligence on Twitter and in public appearances. But while talking about an AI god grabs headlines, we have more pressing problems to consider. The AI experts I get to speak with aren't concerned about an artificial superintelligence suddenly cropping up in the next few months and taking over the world. Meanwhile, there's plenty to be concerned about when it comes to immediate and unintended consequences of the machine learning techniques already available.