After years of failed attempts to curb surveillance technologies, Baltimore is close to enacting one of the nation's most stringent bans on facial recognition. But Baltimore's proposed ban would be very different from laws in San Francisco or Portland, Oregon: It would last for only one year, police would be exempt, and certain private uses of the tech would become illegal. City councilmember Kristerfer Burnett, who introduced the proposed ban, says it was shaped by the nuances of Baltimore, though critics complain it could unfairly penalize, or even jail, private citizens who use the tech. Last year, Burnett introduced a version of the bill that would have banned city use of facial recognition permanently. When that failed, he instead introduced this version, with a built-in one year "sunset" clause requiring council approval to be extended.

As artificial intelligence (AI) for applications in medicine and healthcare undergoes increased regulatory analysis and clinical adoption, the data used to train the algorithms are undergoing increasing scrutiny. Scrutiny of the training data is central to understanding algorithmic biases and pitfalls. These can arise from datasets with sample-selection biases -- for example, from a hospital that admits patients with certain socioeconomic backgrounds, or medical images acquired with one particular type of equipment or camera model. Algorithms trained with biases in sample selection typically fail when deployed in settings sufficiently different from those in which the trained data were acquired1. Biases can also arise owing to class imbalances -- as is typical of data associated with rare diseases -- which degrade the performance of trained AI models for diagnosis and prognosis.

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A stealthy autonomous underwater robot that can track elusive underwater creatures without disturbing them could help us better understand the largest daily migration of life on Earth. Mesobot, a 250-kilogram robot that operates either unconnected to a power source or tethered with a lightweight fibre-optic cable, is able to move around below the surface unobtrusively. The ocean's twilight zone – known more formally as the mesopelagic zone – lies between about 200 metres and 1 kilometre in depth. It is the site of the diel vertical migration (DVM), a daily phenomenon during which deep-dwelling animals come closer to the surface to feed on the more plentiful food supplies found there, while dodging predators. The DVM is seen by biologists as a very important way in which nutrients – and carbon dioxide captured via photosynthesis – can be rapidly transported to depth, where carbon can be stored for the long term.

The Association for the Advancement of Artificial Intelligence's 2021 Spring Symposium Series was held virtually from March 22-24, 2021. There were ten symposia in the program: Applied AI in Healthcare: Safety, Community, and the Environment, Artificial Intelligence for K-12 Education, Artificial Intelligence for Synthetic Biology, Challenges and Opportunities for Multi-Agent Reinforcement Learning, Combining Machine Learning and Knowledge Engineering, Combining Machine Learning with Physical Sciences, Implementing AI Ethics, Leveraging Systems Engineering to Realize Synergistic AI/Machine-Learning Capabilities, Machine Learning for Mobile Robot Navigation in the Wild, and Survival Prediction: Algorithms, Challenges and Applications. This report contains summaries of all the symposia. The two-day international virtual symposium included invited speakers, presenters of research papers, and breakout discussions from attendees around the world. Registrants were from different countries/cities including the US, Canada, Melbourne, Paris, Berlin, Lisbon, Beijing, Central America, Amsterdam, and Switzerland. We had active discussions about solving health-related, real-world issues in various emerging, ongoing, and underrepresented areas using innovative technologies including Artificial Intelligence and Robotics. We primarily focused on AI-assisted and robot-assisted healthcare, with specific focus on areas of improving safety, the community, and the environment through the latest technological advances in our respective fields. The day was kicked off by Raj Puri, Physician and Director of Strategic Health Initiatives & Innovation at Stanford University spoke about a novel, automated sentinel surveillance system his team built mitigating COVID and its integration into their public-facing dashboard of clinical data and metrics. Selected paper presentations during both days were wide ranging including talks from Oliver Bendel, a Professor from Switzerland and his Swiss colleague, Alina Gasser discussing co-robots in care and support, providing the latest information on technologies relating to human-robot interaction and communication. Yizheng Zhao, Associate Professor at Nanjing University and her colleagues from China discussed views of ontologies with applications to logical difference computation in the healthcare sector. Pooria Ghadiri from McGill University, Montreal, Canada discussed his research relating to AI enhancements in health-care delivery for adolescents with mental health problems in the primary care setting.

The task is incredibly challenging--even expert human lip readers are actually pretty poor at word-for-word interpretation. In 2018, Google subsidiary Deepmind published research unveiling its latest full-sentence lip-reading system. The AI achieved a word error rate (the percent of words it got wrong) of 41 percent on videos containing full sentences. Human lip readers viewing a similar sample of video-only clips had word error rates of 93 percent when given no context about the subject matter and 86 percent when given the video's title, subject category, and several words in the sentence. That study was conducted using a large, custom-curated dataset.

Between his mom's place in Manhattan, his dad in Queens, and his high school in the Bronx, Noah Getz is on the subway a lot. It gives him time to read and to think. Our first coronavirus summer was waning, and he'd been wrestling with a weighty science problem: using machine learning to hunt down tiny molecules that may help treat Alzheimer's. Thus far, his AI had been spitting out results that were "almost comically bad." The problem was that the algorithms Getz was using did their best when they had massive amounts of data to sift through and discover patterns in. Getz' data set was far smaller; he was working with one lab at Mount Sinai, not a multinational pharmaceutical company with a galaxy-sized drug library.

The Artificial Intelligence and Machine Learning Market research report is an in-depth analysis of the latest developments, market size, status, upcoming technologies, industry drivers, challenges, regulatory policies, with key company profiles and strategies of players. The research study provides market overview, Artificial Intelligence and Machine Learning market definition, regional market opportunity, sales and revenue by region, manufacturing cost analysis, Industrial Chain, market effect factors analysis, Artificial Intelligence and Machine Learning market size forecast, market data Graphs and Statistics, Tables, Bar & Pie Charts, and many more for business intelligence. The up-to-date report of Artificial Intelligence and Machine Learning market presents an in-depth evaluation of all the crucial factors such as key growth drivers, impediments, and opportunities to understand the industry behavior. Moving ahead, insights into competitive landscape with regards to the top firms, emerging contenders, and new entrants is taken into account. Moreover, the document sheds light on the effects of COVID-19 pandemic on this marketplace and puts forth various strategies for effective risk management and strong profits in the upcoming years.

Could NFTs become a fixture in video games? At least one publisher, Mythical Games, is betting on it. The Los Angeles-based game maker already has some big names including luxury clothier Burberry and DJ deadmau5 ready to create special high-tech playable collectibles in its new online multiplayer game "Blankos Block Party" this summer. "Blankos Block Party" is an colorful art-filled open-world game where you can explore an ever-growing variety of racing, tag, collection and shooting levels, build your own levels and create competitive mini-parties with friends. Mythical announced early access for the free PC game Monday at the Electronic Entertainment Expo (E3) – go to blankos.com

From the Sojourner rover, which landed on Mars in 1997, to Perseverance, which touched down in February, the robots of the Red Planet share a defining feature: wheels. Rolling is far more stable and energy efficient than walking, which even robots on Earth still struggle to master. After all, NASA would hate for its very expensive Martian explorer to topple over and flail around like a turtle on its back. The problem with wheels, though, is that they limit where rovers can go: To explore complicated Martian terra like steep hills, you need the kinds of legs that evolution gave animals on Earth. So a team of scientists from ETH Zurich in Switzerland and the Max Planck Institute for Solar System Research in Germany have been playing around with a small quadrupedal robot called SpaceBok, designed to mimic an antelope known as a springbok.