In a key step toward making large-scale optical neural networks practical, researchers have demonstrated a first-of-its-kind multilayer all-optical artificial neural network. Generally, this type of artificial intelligence can tackle complex problems that are impossible with traditional computational approaches, but current designs require extensive computational resources that are both time-consuming and energy intensive. For this reason, there is great interest developing practical optical artificial neural networks, which are faster and consume less power than those based on traditional computers. In Optica, The Optical Society's journal for high-impact research, researchers from The Hong Kong University of Science and Technology, Hong Kong detail their two-layer all-optical neural network and successfully apply it to a complex classification task. "Our all-optical scheme could enable a neural network that performs optical parallel computation at the speed of light while consuming little energy," said Junwei Liu, a member of the research team.

Nominate graduate students and early-career professional colleagues for the opportunity to participate -- free of charge -- in the Women's Early Career Accelerator. This by-invitation-only training and networking event takes place on Monday, November 4. The day-long program, designed for women just getting started in deep learning, will introduce the fundamentals through a hands-on workshop and connect them with women doing important work in the field. The ideal candidate is a developer, data scientist, engineer, researcher, or student in a technical field who wants a hands-on introduction to deep learning and computer vision. Participants should be familiar with basic programming fundamentals like functions and variables, but no prior experience with deep learning is necessary. These sponsored registrations are available to a limited number of people.

The UK's Department of Transport has announced plans to share data on roadworks taking place during public holidays. The government agency hopes that the datasets will be used by navigation companies like Garmin, Here and Waze – many of which rely on AI technologies – to optimize the flow of traffic. "Today's announcement will help open up data, reducing congestion, pollution and frustration for road users," said George Freeman, Minister for the Future of Transport. The government collects information on upcoming roadworks through Traffic Regulation Orders (TROs) – tools which allow local authorities to restrict, regulate or prevent the use of any public road. Under proposed legislative changes, tech companies would be able to gain access to this treasure trove of data and come up with solutions to potential traffic jams, months in advance.

Don't block the airflow of your fridge or put too much soap in your washing machine, or LG's app will yell at you. LG calls the feature "Proactive Customer Care," and plans to debut it at the IFA Tech Showcase in Berlin next week. A new part of LG's ThinQ app, the feature uses artificial intelligence to monitor compatible appliances for potential problems like temperature drops or poor air flow. LG Proactive Customer Care will roll out to Europe first on new front-load washing machines and bottom-freezer refrigerators -- next year, LG plans to bring it to the US, too. The intelligence behind the service is specifically designed to help you maximize the lifespan of your appliances, and it might scold you about how you're using them to help. The service specifically looks for examples of misuse, malfunction or needed maintenance.

Automatic speech recognition systems like those at the core of Alexa convert speech into text, and one of their components is a model that predicts which word will come after a sequence of words. They're typically n-gram based, meaning they suss out the probability of next words given the past n-1 words. But architectures like recurrent neural networks, which are commonly used in speech recognition because of their ability to learn long-range dependencies, are tough to incorporate into real-time systems and often struggle to ingest data from multiple corpora. That's why researchers at Amazon's Alexa research division investigated techniques to make such AI models more practical for speech recognition. In a blog post and accompanying paper ("Scalable Multi Corpora Neural Language Models for ASR") scheduled to be presented at the upcoming Interspeech 2019 conference in Graz, Austria, they claim they can reduce word recognition error rate by 6.2% over the baseline.

Atos, a global leader in digital transformation, announced the delivery of Quantum-Learning-as-a-Service (QLaaS) to Xofia to help develop quantum-powered artificial intelligence solutions for the enterprise. Xofia is a startup based in Houston that combines artificial intelligence with quantum-based algorithms to implement problem-solving strategies to create a futuristic platform for the enterprise. Engaging Atos' QLaaS model, Xofia's research and development team will access a remote Atos Quantum Learning Machine, a stand-alone appliance that provides access to an evolutive quantum programming environment and simulates the behavior of any kind of quantum computing technology. Atos will also support Xofia's efforts by providing quantum consulting, training and system administration services. Read More: Splunk Decides to Buy AIOps Start-Up SignalFx for $1.05 Billion "Our collaboration with Xofia is part of our strategy to support a large ecosystem of startups in the quantum computing field. With Xofia we will help create quantum-powered AI solutions that have scalability, high performance and the ultimate power of simulation that is needed to solve future big data challenges that are inevitable within the enterprise," said Ludovic Sauvage, Head of Big Data, High Performance and Quantum Computing, Atos North America.

St. Petersburg Resident's Newly Patented, Cutting-edge Tool Combines Psychology of Operant Learning with Artificial Intelligence to Help Mitigate Relapse Risk Factors St. Petersburg, FL--In recognition of 2019 National Recovery Month in September, PerfectCoaches seeks to partner with alcohol/drug treatment practitioners and experts nationwide to support those battling the scourge of addiction. As a first step, PerfectCoaches is calling for input and feedback from subject matter experts on our needs assessment and proposed mitigation strategies. Participants/partners will receive a number of benefits, including a unique opportunity to differentiate themselves from other providers by expanding their service offerings. We will also publicly recognize contributors via our social media platforms. PerfectCoaches represents a breakthrough in behavioral change and skill development, both for individuals and organizations.

The Artificial Intelligence industry is currently booming. The major competitors are the United States, China and the European Union, each of which is attempting to attain a large share of the international market for AI technology. The EU wants to distinguish itself by investing in AI that it trustworthy and ethical: AI that meets societal needs and expectations, obeys legal requirements, and supports human values. In this presentation, we will discuss and critique the European approach. In doing so, we will present results of the SIENNA project, an EU-funded project that studies ethical and human rights aspects of AI.

Let me start by thanking Antti [Kaikkonen, Minister of Defence of Finland] and all the Finnish colleagues for an excellent couple of days – 24 hours - of this informal meeting of the European Union Member States' Defence Ministers. It has been extremely productive and intense. Our agenda has been very heavy – heavy in terms of content, but light in terms of the kind of approach and relations we have had. The wonderful Helsinki sun has helped establishing a friendly atmosphere and I would say that the exchanges have been extremely consensual, productive and positive. Thank you for that, because your hospitality has contributed to set a positive and constructive tone.

In this photo taken on Friday, July 26, 2019, and distributed by Roscosmos Space Agency Press Service, the Fedor robot is displayed before being loaded into a Soyuz capsule that was launched Thursday Aug. 22, 2019, from the launch pad at Russia's space facility in Baikonur, Kazakhstan. A Russian space capsule carrying a humanoid robot has failed to dock as planned with the International Space Station. A statement from the Russian space agency Roscosmos said the failure to dock on Saturday Aug. 24, 2019, was because of problems in the docking system, but didn't give details.