If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
A team of researchers at Cornell University has developed a new method enabling autonomous vehicles to create "memories" of previous experiences, which can then be used in future navigation. This will be especially useful when these self-driving cars can't rely on sensors in bad weather environments. Current self-driving cars that use artificial neural networks have no memory of the past, meaning they are constantly "seeing" things for the first time. And this is true regardless of how many times they've driven the exact same road. Killian Weinberger is senior author of the research and a professor of computer science.
VISTA 2.0 is an open-source simulation engine that can make realistic environments for training and testing self-driving cars. Hyper-realistic virtual worlds have been heralded as the best driving schools for autonomous vehicles (AVs), since they've proven fruitful test beds for safely trying out dangerous driving scenarios. Tesla, Waymo, and other self-driving companies all rely heavily on data to enable expensive and proprietary photorealistic simulators, since testing and gathering nuanced I-almost-crashed data usually isn't the most easy or desirable to recreate. To that end, scientists from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) created "VISTA 2.0," a data-driven simulation engine where vehicles can learn to drive in the real world and recover from near-crash scenarios. What's more, all of the code is being open-sourced to the public.
VISTA 2.0 builds off of the team's previous model, VISTA, and it's fundamentally different from existing AV simulators since it's data-driven -- meaning it was built and photorealistically rendered from real-world data -- thereby enabling direct transfer to reality. While the initial iteration supported only single car lane-following with one camera sensor, achieving high-fidelity data-driven simulation required rethinking the foundations of how different sensors and behavioral interactions can be synthesized. Enter VISTA 2.0: a data-driven system that can simulate complex sensor types and massively interactive scenarios and intersections at scale. With much less data than previous models, the team was able to train autonomous vehicles that could be substantially more robust than those trained on large amounts of real-world data. "This is a massive jump in capabilities of data-driven simulation for autonomous vehicles, as well as the increase of scale and ability to handle greater driving complexity," says Alexander Amini, CSAIL PhD student and co-lead author on two new papers, together with fellow PhD student Tsun-Hsuan Wang.
IoT has seen steady adopted across the business world over the past decade. Businesses have been built or optimized using IoT devices and their data capabilities, ushering in a new era of business and consumer technology. Now the next wave is upon us as advances in AI and machine learning unleash the possibilities of IoT devices utilizing "artificial intelligence of things," or AIoT. Consumers, businesses, economies, and industries that adopt and invest in AIoT can leverage its power and gain competitive advantages. IoT collects the data, and AI analyzes it to simulate smart behavior and support decision-making processes with minimal human intervention.
But how will AI and 5G most affect our everyday business lives? What are 5G and AI use cases? Convergence makes 5G and AI use cases exciting: 5G could unleash the artificial intelligence revolution, moving it into a different league and creating new AI use cases. When Apple launched the iPhone, few people understood its significance. There was a reason for this.
LAGUNA HILLS, CA / ACCESSWIRE / June 19, 2022 /BrainChip Holdings Ltd (ASX:BRN)(OTCQX:BRCHF)(ADR:BCHPY), the world's first commercial producer of neuromorphic AI IP, and Prophesee, the inventor of the world's most advanced neuromorphic vision systems, today announced a technology partnership that delivers next-generation platforms for OEMs looking to integrate event-based vision systems with high levels of AI performance coupled with ultra-low power technologies. Inspired by human vision, Prophesee's technology uses a patented sensor design and AI algorithms that mimic the eye and brain to reveal what was invisible until now using standard frame-based technology. BrainChip's first-to-market neuromorphic processor, Akida, mimics the human brain to analyze only essential sensor inputs at the point of acquisition, processing data with unparalleled efficiency, precision, and economy of energy. Keeping AI/ML local to the chip, independent of the cloud, also dramatically reduces latency. "We've successfully ported the data from Prophesee's neuromorphic-based camera sensor to process inference on Akida with impressive performance," said Anil Mankar, Co-Founder and CDO of BrainChip.
DUBAI: Six years after the Dubai Roads and Transportation Authority laid the roadmap for driverless vehicles by 2030, smart mobility has swept the landscape with intelligent concepts that are changing the region's social infrastructure. The move has already spurred sustainable cities into high gear with smart transportation such as autonomous shuttles, e-bikes and e-buggies set to own the roads. An excellent example of a fully-integrated residential project is Sharjah Sustainable City. This eco-friendly concept is powering a net-zero energy community with energy-efficient villas that promise to offer sustainable living at no extra cost. Developed by Sharjah Investment and Development Authority in partnership with Diamond Developers, the sustainable city will host the best green technology, including solar-powered smart homes, bio-domes for vertical farming, electric vehicle chargers, driverless shuttles and a biogas plant. "The UAE is the first country in the Gulf Cooperation Council to commit to net-zero by 2050; all growth and development must align with that commitment, which means we have to do our bit," Karim El-Jisr, chief sustainability officer, SSC, told Arab News.
Automakers reported nearly 400 crashes over a 10-month period involving vehicles with partially automated driver-assist systems, including 273 with Teslas, according to statistics released Wednesday by U.S. safety regulators. The National Highway Traffic Safety Administration cautioned against using the numbers to compare automakers, saying it didn't weight them by the number of vehicles from each manufacturer that use the systems, or how many miles those vehicles traveled. Automakers reported crashes from July of last year through May 15 under an order from the agency, which is examining such crashes broadly for the first time. "As we gather more data, NHTSA will be able to better identify any emerging risks or trends and learn more about how these technologies are performing in the real world," said Steven Cliff, the agency's administrator. Tesla's crashes happened while vehicles were using Autopilot, "Full Self-Driving," Traffic Aware Cruise Control, or other driver-assist systems that have some control over speed and steering.
US car manufacturers reported nearly 400 crashes involving cars with partially autonomous driver assistance systems, according to a new report from a US car-safety regulator released on Wednesday. Tesla, which has about 830,000 vehicles on the road with driver-assist programmes that have partial control over speed and steering, reported 273 crashes, about 70 percent of the total, according to The Associated Press. Companies caution that drivers must remain prepared to intervene and take control of driving at all times, even in cars with partially autonomous systems. The National Highway Traffic Safety Administration (NHTSA) collected reports of such crashes from manufacturers from July 2021 through May 2022, the first broader report of its kind. The NHTSA said the report provided "crucial data necessary for research and for the development of policies to enhance the safety of these technologies".
A Tesla owner charges his vehicle in April 2021 at a charging station in Topeka, Kan.. Tesla reported 273 crashes involving partially automated driving systems, according to statistics released by U.S. safety regulators on Wednesday. A Tesla owner charges his vehicle in April 2021 at a charging station in Topeka, Kan.. Tesla reported 273 crashes involving partially automated driving systems, according to statistics released by U.S. safety regulators on Wednesday. Automakers reported nearly 400 crashes of vehicles with partially automated driver-assist systems, including 273 involving Teslas, according to statistics released Wednesday by U.S. safety regulators. The National Highway Traffic Safety Administration cautioned against using the numbers to compare automakers, saying it didn't weight them by the number of vehicles from each manufacturer that use the systems, or how many miles those vehicles traveled. Automakers reported crashes from July of last year through May 15 under an order from the agency, which is examining such crashes broadly for the first time.