Videantis, which provides automotive deep learning, computer vision and video coding solutions, has announced that it will partner with the Fraunhofer Institute for Integrated Circuits IIS, Infineon and other leading companies and universities to develop an artificial intelligence (AI) ASIC and software development tools specifically for intelligent autonomous vehicles. The Videantis AI multi-core processor platform and tool flow has been selected for the KI-Flex autonomous driving chip project. Autonomous driving relies on fast and reliable processing and merging of data from several lidar, camera and radar sensors in the vehicle. This data can provide an accurate picture of the traffic conditions and environment to allow the vehicle to make intelligent decisions when driving. The process of intelligently analysing these volumes of sensor data requires high-performance, efficient, and versatile compute solutions.
When science and technology meet social and economic systems, you tend to see something akin to what the late Stephen Jay Gould called "punctuated equilibrium" in his description of evolutionary biology. Something that has been stable for a long period is suddenly disrupted radically--and then settles into a new equilibrium.1 1.See Stephen Jay Gould, Punctuated Equilibrium, Cambridge, MA: Harvard University Press, 2007. Gould pointed out that fossil records show that species change does not advance gradually but often massively and disruptively. After the mass extinctions that have occurred several times across evolutionary eras, a minority of species survived and the voids in the ecosystem rapidly filled with massive speciation. Gould's theory addresses the discontinuity in fossil records that puzzled Charles Darwin.
Cities around the world are getting smarter. Already, street lights in places like San Diego are turning off, and conserving energy, when vehicles and pedestrians aren't around. Soon, connected garbage cans will tell waste haulers when they need to be emptied, optimizing collection routes. Smart buildings will notify maintenance staff of impending repair needs. And parking spots will find you, instead of the other way around.
Artificial intelligence (AI) is probably today's hottest tech growth trend. Spending on AI systems will soar from $37.5 billion in 2019 to $97.9 billion in 2023 -- that's a 28.4% compound annual growth rate -- according to estimates by research firm IDC. So it makes great sense for investors to want some exposure to AI in their portfolios. To help you cut through the many investment choices, we asked three Motley Fool contributors who cover the AI space to name their top AI stock pick for 2020 and beyond. The kicker here is that they needed to love their stock pick enough to own it.
John McCarthy was the son of a penniless Irish immigrant from Kerry and maybe the most important Irish American you never heard of. He died in 2011 aged 84. He was an American computer scientist pioneer and inventor and is known as the father of artificial intelligence (AI) after playing the key role in the development of intelligent machines we now call computers. He won the Turing Prize, one step below the Nobel, in 1971. He coined the term artificial intelligence for a 1955 Dartmouth College conference he chiefly organized which was the first-ever AI conference.
The European Commission is considering measures to impose a temporary ban on facial recognition technologies used by both public and private actors, according to a draft white paper on Artificial Intelligence obtained by EURACTIV. If implemented, the plans could throw current AI projects off course in some EU countries, including Germany's wish to roll out automatic facial recognition at 134 railway stations and 14 airports. France also has plans to establish a legal framework permitting video surveillance systems to be embedded with facial recognition technologies. The Commission paper, which gives an insight into proposals for a European approach to Artificial Intelligence, stipulates that a future regulatory framework could "include a time–limited ban on the use of facial recognition technology in public spaces." The document adds that the "use of facial recognition technology by private or public actors in public spaces would be prohibited for a definite period (e.g. More generally, the draft White Paper, the completed version of which the Commission should publish towards the end of February, features five regulatory options for Artificial Intelligence across the bloc. A Voluntary Labelling framework could consist of a legal instrument whereby developers could "chose to comply, on a voluntary basis, with requirements for ethical and trustworthy artificial intelligence." Should compliance in this area be guaranteed, a'label' of ethical or trustworthy artificial intelligence would be granted, with binding conditions. Option two focuses on a specific area of public concern – the use of artificial intelligence by public authorities – as well as the employment of facial recognition technologies generally. In the former area, the paper states that the EU could adopt an approach akin to the stance taken by Canada in its Directive on Automated Decision Making, which sets out minimum standards for government departments that wish to use an Automated Decision System. As for facial recognition, the Commission document highlights provisions from the EU's General Data Protection Regulation, which give citizens "the right not to be subject of a decision based solely on automated processing, including profiling." In the third area which the Commission is currently priming for regulation, legally binding instruments would apply only "to high–risk applications of artificial intelligence.
When referring to how workplace related awareness can make a potential difference in worker behavior, a recent study of that phenomena gained national interest. The study examined the opioid drug crisis occurring in the United States. There are many thousands of deaths each year due to opioid overdoses and an estimated nearly 2 million Americans that are addicted to opioids. According to the study, part of the reason that opioid use has vastly increased over the last two decades is as a result of prescribing opioids for pain relief and for similar purposes. Apparently, medical doctors had gotten used to prescribing opioids and did so without necessarily overtly considering the downsides of becoming possibly addicted to it.
Since a few years, organisations have been investing heavily in the autonomous driving space. The reason behind this spending is expected to reshape the ways of the transport network in a positive way. According to reports, the global autonomous vehicle market is expected to witness an accelerated CAGR of 62.86% to reach $41.24 billion by 2024. In this article, we list down ten popular datasets for autonomous driving projects. The list is in alphabetical order.
The companies racing to deploy autonomous cars on the world's roads took a reality check in the 2010s, but multimillion-dollar development efforts remain ongoing across the automotive and tech industries. German supplier Bosch is notably moving full speed ahead with its quest to make driverless cars a reality. Kay Stepper, Bosch's senior vice president of automated driving, sat down with Digital Trends to talk about the state of autonomous driving in 2020, and what's next for the artificial intelligence technology that powers the prototypes it's testing. Bosch has never made a car, so it brings its innovations to the market through partnerships with automakers. It chose Mercedes-Benz parent company Daimler to test autonomous technology in real-world conditions via a ridesharing pilot program in San Jose, California, close to one of the company's research centers.
AI varies from industry to industry. There are just as many use cases for AI as there are companies. For healthcare organizations, AI is playing a role in monitoring equipment, while retailers see AI as a way to better understand customers. Transportation executives are banking on AI to drive autonomous vehicles. The common denominator across all industry groups is the rate that AI is changing the way things get done.