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) …
Uber Eats is launching not just one but two autonomous delivery pilots today in Los Angeles, TechCrunch has reported. The first is via an autonomous vehicle partnership with Motional, originally announced in December, and the second is with sidewalk delivery firm Serve Robotics, a company that spun out of Uber itself. The trials will be limited, with deliveries from just a few merchants including the Kreation juicery and organic cafe. Serve will do short delivery routes in West Hollywood, while Motional will take care of longer deliveries in Santa Monica. "We'll be able to learn from both of those pilots what customers actually want, what merchants actually want and what makes sense for delivery," an Uber spokesperson told TechCrunch.
Every year, it gets harder to keep up with technology updates in convenience services. For many industry players, the pandemic put some projects on hold, but the surging interest in contactless transactions accelerated expansion of technology innovation. An early morning session, "Trending Technologies in Convenience Services," gave attendees a chance to unpack the key tech innovations at the National Automatic Merchandising Association show at Chicago's McCormick Place. "The pandemic has given us a lot of new terms, and it's also accelerated the digital transformation of the industry," session moderator Michael Kasavana, Ph.D., the NAMA endowed professor emeritus, observed at the outset. The well attended session provided updates on artificial intelligence services for convenience services, contactless payments and ways to prevent the growing cybercrime threat.
Artificial intelligence (AI) is now transforming the manufacturing industry. AI can extend the sheer reach of potential applications in the manufacturing process from real-time equipment maintenance to virtual design that allows for new, improved, and customized products to a smart supply chain and the creation of new business models. Artificial intelligence (AI) in the manufacturing industry is being used across a variety of different application cases. It is being used as a way to enhance defect detection through sophisticated image processing algorithms that can then automatically categorize defects across any industrial object that it sees. The term artificial intelligence is used because these machines are artificially incorporated with human-like to perform tasks as we do.
We are presently living in an age of "artificial intelligence" -- but not how the companies selling "AI" would have you believe. According to Silicon Valley, machines are rapidly surpassing human performance on a variety of tasks from mundane, but well-defined and useful ones like automatic transcription to much vaguer skills like "reading comprehension" and "visual understanding." According to some, these skills even represent rapid progress toward "Artificial General Intelligence," or systems which are capable of learning new skills on their own. Given these grand and ultimately false claims, we need media coverage that holds tech companies to account. Far too often, what we get instead is breathless "gee whiz" reporting, even in venerable publications like The New York Times.
Eileen Yu began covering the IT industry when Asynchronous Transfer Mode was still hip and e-commerce was the new buzzword. Currently an independent business technology journalist and content specialist based in Singapore, she has over 20 years of industry experience with various publications including ZDNet, IDG, and Singapore Press Holdings. Two companies are collaborating to help data centres in Singapore measure their carbon footprint and improve their operational efficiencies towards greater sustainability. The partnership is touted to include services, powered by artificial intelligence (AI) and machine learning, to track and forecast greenhouse gas emissions of critical dana centre systems. The partnership between MetaVerse Green Exchange (MVGX) and Red Dot Analytics (RDA) would aim to "verifiably measure and offset" the carbon footprint of data centres in tropical environments, the two companies said in a joint statement Wednesday.
Arrikto, the leader in machine learning on Kubernetes, participated in the announcement of Kubeflow 1.5, the latest version of the open source MLOps platform, with contributions from Google, Arrikto, IBM, Twitter and Rakuten, alongside numerous other contributors. Kubeflow 1.5 delivers lower infrastructure costs, and helps simplify the operation of the end-to-end machine learning platform. Originally developed by Google, Kubeflow is a complete MLOps toolkit, including integrated components for model development, model training, multi-step pipelines, AutoML, serving, monitoring, artifact management, and experiment tracking. Running production machine learning workflows at scale is notoriously expensive due to outsized requirements on CPUs, GPUs, storage, and memory. Kubeflow 1.5 introduces several key features to reduce these costs.
South Korean startup Seadronix wants to reduce the issue of marine accidents, 75% of which are caused by human error, according to a 2019 Allianz safety and shipping report. The company just secured a $5.8 million Series A extension to scale its AI-based ship berthing monitoring and navigation systems to help cargo ships navigate safely and assist port operators anchoring their vehicles at harbor. The fresh funds, led by SoftBank Ventures Asia, bring Seadronix's the total round up to $8.3 million. Seadronix will use the capital to grow its team beyond the current headcount of 30 employees and enter global markets, including Singapore and Europe, where its "smart ports" are located, Byeolteo Park, CEO and co-founder, said in an interview with TechCrunch. A smart port uses technologies including AI, big data, Internet of Things and 5G to provide more security and save energy by digitalizing the way huge ships enter docks and handle logistics at the ports.
There is a lot of buzz these days around autonomous aerial vehicles (AAV) and all of the ways that they can benefit us in our everyday lives. From express deliveries to disaster management, search and rescue operations, and mapping of inaccessible locations, the list of potential applications goes on and on. But when was the last time a drone dropped off an online order at your home? If you are like most people, the answer is "never." While the potential of UAVs to transform our lives in many ways is real, the reason that relatively few of us have experienced that stems from a number of problems that have yet to be solved. One of these problems is the difficulty of executing safe and precise flight maneuvers under windy conditions.
Good data--and lots of it--is key to making artificial intelligence/machine learning (AI/ML) production, inspection and packaging systems work without a hitch, plus well written algorithms to analyze the data and make decisions that will help people and machines function more intelligently. In fact, 3-D vision systems are usually the "eyes" robots use to guide them as they sort and package products or load pallets--3-D because it provides much more data to make intelligent decisions quickly. Processors are keenly interested in getting their products perfect before packaging, and AI/ML can play a part in production monitoring. "I think we will begin seeing a lot more utilization of AI/ML to improve product quality and consistency," says Jason Prince, Golden State Foods director of operations, protein products. "For instance, adjusting product pressure automatically to achieve a very specific product thickness or weight, given a set of ever-changing variables such as product temperature and density. This would ensure that the finished product is consistent over time, despite changing raw material characteristics. Adjustments will be able to be made in near real time and eliminate the time required for a quality check to be completed and then an operator adjustment to be made."
Working as an aerospace engineer in Malaysia, Chee How Lim dreamed of building a startup that could really take off. Today his company, Tapway, is riding a wave of computer vision and AI adoption in Southeast Asia. A call for help in 2019 with video analytics led to the Kuala Lumpur-based company's biggest project to date. Malaysia's largest operator of toll highways, PLUS, wanted to reduce congestion for its more than 1.5 million daily travelers. A national plan called for enabling car, taxi, bus and truck traffic to flow freely across multiple lanes -- but that posed several big challenges.