Motional's driverless Ioniq 5 is entering service earlier than expected. On Tuesday, the company and Lyft announced that the vehicle is ready to begin offering rides to the public, starting with residents and visitors to Las Vegas. With today's announcement, the Ioniq 5 is the first fully electric autonomous vehicle to join Lyft's network. In Las Vegas, Motional, a joint venture between Hyundai and Aptiv, had been testing autonomous vehicles without safety drivers since 2020. With its public launch, the Ioniq 5 is fully integrated into Lyft's software.

When you drop into every arena in "Rollerdrome," you're faced with waves of enemies perched in various parts of each skate park. The game is all about forward momentum. Once you give Kara a first push of the analog stick you don't have to tell her to keep skating. She'll do it on her own. So, it can get frustrating when certain parts of the maps feel just out of reach.

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Professor Park Sang-Hyun of the Department of Robotics and Mechatronics Engineering has led a research team in developing a weakly supervised deep learning model that can accurately locate cancer in pathological images based only on data where the cancer is present. Existing deep learning models needed to construct a dataset to specify the cancer site whereas the model developed in this study improved efficiency. It is hoped that it will make a significant contribution to the relevant research field. Generally, locating the cancer site involves zoning which is time-consuming and increases cost so the new AI model looks to be promising. The weakly supervised learning model that zones cancer sites with only rough data such as'whether the cancer in the image is present or not' is under active study.

Artificial intelligence (AI) is often touted as the cure-all for financial services firms' ability to deal with the looming data onslaught stemming from environmental, social & governance (ESG) regulation. Yet ESG also poses an existential threat to the financial services industry's use of AI The European Union's Sustainable Finance Disclosure Regulation has required asset management firms to begin collecting millions of data points from the companies in which they invest, and the forthcoming Corporate Sustainable Reporting Directive will only add to the volume of data points. Further, there is the data being collected under the Task Force on Climate-Related Financial Disclosures (TCFD) initiative and the International Sustainability Standards Board's plans to create a baseline for ESG reporting. Taken all together and it becomes clear that AI-enabled systems will be essential to firms' efforts to make sense of -- and profit from -- all these requirements. The carbon footprint from storing and processing data is enormous and growing, algorithms have already been shown to discriminate against certain groups in the population, and a lack of technology skills in both senior management ranks and the general workforce leave firms vulnerable to mistakes.

A new artificial intelligence language-processing tool could potentially help detect cognitive impairment and mental degenerative diseases like Alzheimer's, researchers at Boston University say. Their findings, which were published in The Journal of the Alzheimer's Association, suggest that a machine-learning computational model could identify cognitive decline through audio recordings of neuropsychological tests. "It can form the basis of an online tool that could reach everyone and could increase the number of people who get screened early," said Ioannis Paschalidis, a professor of engineering and one of the researchers at Boston University, in a news release. The computational model, which does not require in-person assessments, could ultimately help clinicians triage the urgency of patients' symptoms more efficiently, allowing them to allocate resources without replacing follow-up processes for diagnosis, she said. Using automated speech recognition software, the program transcribes interviews and, by encoding them into numbers, detects patterns that assess the likelihood and severity of a patient's cognitive impairment.

In industrial manufacturing systems, failures of machines caused by faults in their key components greatly influence operational safety and system reliability. Many data-driven methods have been developed for machinery diagnostics and prognostics. However, there lacks sufficient labeled data to train a high-performance data-driven model. Moreover, machinery datasets are usually collected from different operation conditions and mechanical components, leading to poor model generalization. To address these concerns, cross-domain transfer learning methods are applied to enhance the feasibility and accuracy of data-driven methods for machinery diagnostics and prognostics.

Finance organisations are increasingly turning to artificial intelligence in pursuit of competitive advantage. However, although many firms are achieving successful results from AI projects, scaling up enterprise-wide often remains elusive. Rob Smith, CTO of award-winning cloud services provider Creative ITC, explains how the growing trend of as-a-Service IT models is accelerating digital transformation across the finance sector and enabling IT leaders to unlock greater ROI. Uptake of artificial intelligence (AI) and machine learning (ML) is continuing to rise as financial organisations progress their digital transformation plans. These new technologies offer banking and finance firms new ways to accelerate and improve decision-making and customer service.

The description of "artificial intelligence in high school" may conjure up a science fiction novel where robots stand around chatting at their lockers. The reality, at Seckinger High School in Gwinnett County, Ga., looks more like this: A social studies teacher pauses a lesson on the spread of cholera in the 19th century to discuss how data scientists use AI tools today to track diseases. A math class full of English-language learners uses machine learning to identify linear and non-linear shapes. The simplest explanation of this technology is that it trains a machine to do tasks that simulate some of what the human brain can do. That means it can learn to do things like recognize faces and voices (helpful for radiology, security, and more), understand natural language, and even make recommendations.