Munich – 17 September 2019 – Artificial intelligence (AI) and neural networks are becoming a key factor in developing safer, smart and eco-friendly cars. In order to support AI-driven solutions with its future automotive microcontrollers, Infineon Technologies has started a collaboration with Synopsys, Inc. Next generation AURIX microcontrollers from Infineon will integrate a new high-performance AI accelerator called Parallel Processing Unit (PPU) that will employ Synopsys' DesignWare ARC EV Processor IP. AI and neural networks are fundamental building blocks for future automated driving applications such as object classification, target tracking, or path planning. Furthermore, they play an important role in optimizing many other automotive applications, helping to reduce the cost of ECU systems, improving their performance and accelerating time-to-market.

You are in a black sedan parked in a dimly-lit alley at night. In the passenger seat a female, dressed in white top and jeans, asks if you want to share some meth. She lights up and smoke fills the interior. The scenario may sound real enough but it is an immersive virtual reality (VR) experience designed to determine how prone the participant is to drug use by tracking their pulse, brainwaves and the electrical conductance of the skin. Using artificial intelligence that combines the responsive patterns from over 10,000 addiction cases, the system generates a drug craving score, according to Li Dai, founder and chief executive of Beijing-based start-up WonderLab, developer of the technology. The company is working with rehabilitation centers in more than 10 Chinese provinces and municipalities including Shandong, Sichuan, Yunnan, Beijing and Chongqing, to apply the AI-enabled assessment as a follow-up to addiction treatment.

Uber will begin testing its self-driving cars in Dallas, Texas in November, the company announced Tuesday. The vehicles will be operated by human drivers in downtown Dallas to start out, collecting mapping data and capturing driving scenarios which Uber's engineers will then reproduce in simulation. This doesn't mean Uber is planning to offer trips in its self-driving cars or even perform self-driving tests in Dallas. "The data we collect will inform our next steps -- we may not look to test our self-driving system in Dallas immediately following this first round of data gathering," Austin Geidt, head of Uber ATG strategy, said in a Medium post. "While we are certainly excited by this possibility, we are also committed to ensuring that every mile we drive on public roads contributes meaningfully to our development work."

Hah! That's funny, I was just looking for information about this project too. However, I was one of the guys involved (in Robokoneko project, more specifically). Explaining what actually went wrong is a bit lengthy process and goes deeply into philosophy of mind, so to put this as short as possible: what do you think could be achieved in terms of understanding human mind by randomly evolving neural networks? If a being was created, fully aware of its existence, would you be able to tell what led to forming its consciousness? Their goals were absolutely pointless.

We believe that automation and artificial intelligence (AI) will have a profound impact on our organisation which employs over 270,000 employees globally. Our people are highly educated professionals dealing with huge amounts of big data, therefore we want to ensure that we are in control of the disruptive forces of these technologies on our own terms. We also advise companies and governments who want to understand how this will impact them, so we have undertaken comprehensive analysis and research. We used our team of economists and analysts to model the susceptibility of jobs to be automated by the effects of tech such as AI. The headline figure suggests that up to 30% of existing jobs could become highly susceptible to automation by the mid-2030s, with some variability across industry sectors, by education, gender and geography.

UTSA will design data driven approaches and AI to better identify and mitigate cyber threats for IOT devices including smart meters. Through the strategic alliance between the Texas Sustainable Energy Research Institute (TSERI) at UTSA and CPS Energy, three new projects totaling approximately $750,000 will focus on improving grid security and resilience, solar energy generation and more efficient technology for power generation. "We are thrilled to embark on these three new projects that aim to contribute to CPS Energy's position as a key player in the new energy economy," said Krystel Castillo, TSERI Director. "We have been able to build knowledge and grow innovation through our partnership with UTSA over the past decade," said Cris Eugster, CPS Energy's Chief Operating Officer. "We expect these new projects to also bring new insights that will help us plan for the future of energy."

Join us for a cyber security community event with your fellow Check Point customers at the Croton Reservoir Tavern in Manhattan on 19th September 2019 from 11am to 2pm Eastern Time! We guarantee that you'll leave this event having learned something new that you can use to improve your security posture. In addition, this event provides an opportunity to meet your fellow Check Point customers in the region.

Have you ever faced challenges while creating user-oriented digital security algorithms? Designing a more efficient solution to replace the creation and maintenance of paperwork for numerous employees is certainly beneficial. However, even it the era of Data Science and Artificial Intelligence, reinventing security-related services is no easy task. Let's see the approach to develop software solutions with deep learning Optical Character Recognition (OCR) for processing US driver's licenses and IDs. This technology began with the scanning of books, text recognition and hand-written digits (NIST dataset).

When some people think of artificial intelligence (AI), they think of humanoid robots turning against their creators in an apocalyptic science fiction movie. In reality, AI is already playing an increasing role in many existing and evolving technologies, from driverless cars to translation software, virtual assistance devices and monitoring agriculture and biodiversity. Satellite images provided by AI can assist policymakers in finding solutions to problems of hunger, drought and climate change, to name only a few. Audrey Azoulay, Director-General of the United Nations Educational, Scientific and Cultural Organization (UNESCO), says that promoting AI in Africa is a top priority for the organization. "Artificial intelligence can help us advance more rapidly towards the achievement of the SDGs by allowing better risk assessment, enabling more accurate forecasting and faster knowledge sharing, by offering innovative solutions in the fields of education, health, ecology, urbanism and the creative industries and by improving standards of living and our daily well-being," Ms. Azoulay explains.

This is a typical computer-generated dark matter map used by the researchers to train the neural network. A team of physicists and computer scientists at ETH Zurich has developed a new approach to the problem of dark matter and dark energy in the universe. Using machine learning tools, they programmed computers to teach themselves how to extract the relevant information from maps of the universe. Understanding how our universe came to be what it is today and what will be its final destiny is one of the biggest challenges in science. The awe-inspiring display of countless stars on a clear night gives us some idea of the magnitude of the problem, and yet that is only part of the story. The deeper riddle lies in what we cannot see, at least not directly: dark matter and dark energy.