Resonance, a powerful and pervasive phenomenon, appears to play a major role in human interactions. This article investigates the relationship between the physical mechanism of resonance and the human experience of resonance, and considers possibilities for enhancing the experience of resonance within human–robot interactions. We first introduce resonance as a widespread cultural and scientific metaphor. Then, we review the nature of “sympathetic resonance” as a physical mechanism. Following this introduction, the remainder of the article is organized in two parts. In part one, we review the role of resonance (including synchronization and rhythmic entrainment) in human cognition and social interactions. Then, in part two, we review resonance-related phenomena in robotics and artificial intelligence (AI). These two reviews serve as ground for the introduction of a design strategy and combinatorial design space for shaping resonant interactions with robots and AI. We conclude by posing hypotheses and research questions for future empirical studies and discuss a range of ethical and aesthetic issues associated with resonance in human–robot interactions.

Genevieve Carlton holds a Ph.D. in history from Northwestern University. After earning her doctorate in early modern European history, Carlton worked as an assistant professor of history. Computer science majors work as software developers, security analysts, and web developers. But what if you want something a little different? The most badass jobs in computer science will push the field's boundaries and challenge you.

Have you ever ignored a seemingly random LinkedIn solicitor and been left with a weird feeling that something about the profile just seemed…off? Well, it turns out, in some cases, those sales reps hounding you might not actually be human beings at all. Yes, AI-generated deepfakes have come for LinkedIn and they'd like to connect. DiResta, who made a name for herself trudging through torrents of Russian disinformation content in the wake of the 2016 election, said she became aware of a seeming phenomenon of fake, AI computer-generated LinkedIn profile images after one particularly strange-looking account tried to connect with her. The user, who reportedly tried to pitch DiResta on some unimportant piece of software, used an image with strange incongruities that stood out to her as odd for a corporate photo.

Taipei, Taiwan – China and Europe may not be in a cold war, but bilateral relations are increasingly chilly. China's failure to condemn Russia's invasion of Ukraine, considered an existential threat to European security, is the latest and gravest in a series of challenges by Beijing to the rules-based order on which the European Union professes to operate. Reflecting a bilateral relationship centred on economics, Europe has often taken disagreements with its top trading partner China in stride. However, China's support for Russia – rooted in Chinese leader Xi Jinping's close relationship with Russian President Vladimir Putin – has altered European calculations. "The sense of urgency to protect Europe from authoritarian threats wasn't as strong before as it is now. Russia's invasion of Ukraine is a game-changer," Zsuzsa Anna Ferenczy, an assistant professor at Taiwan's National Dong Hwa University and a former political adviser in the European Parliament, told Al Jazeera.

Craig Martell, Head of Machine Learning at Lyft, is set to head the Pentagon's AI efforts. Breaking Defense first broke the news after learning Martell was destined to be named as the Pentagon's new chief digital and AI officer. Martell has significant AI industry experience – leading efforts at not just Lyft but also Dropbox and LinkedIn – but has no experience navigating public-sector bureaucracy. The Pentagon is going to be very much "in at the deep-end" for Martell in that regard, something which he fully acknowledges. "I don't know my ways around the Pentagon yet and I don't know what levers to pull," said Martell to Breaking Defense.

The workshop was conducted by Anshu Aneja, Director of Ansh Infotech and Kriti Bhatia - AI and ML expert. During the course of interaction in the workshop the students were made aware of various practical concepts of artificial intelligence and its types. The workshop focused not just on theoretical knowledge but also drew the attention and interest of the students through practical demonstration of various machine learning and deep learning models. The experts explained the hand gesture recognition software through computer vision, automated search preferences, tumour detection algorithm etc. The students freely interacted with the experts and also tried their hands at the experiments by participating in the projects personally.

AI developers are keen on DA imaging analysis, and the only secret is more AI. The Israel-based company has already received some FDA approvals for AI technology executives and is now planning to use Intel's own detailed learning plan to enhance its software analytics capabilities. In a collaboration announced this week, DIA announced that it will use Intel's OpenVINO toolkit to reduce processing time for its Lvvo seamless echocardiography platform. Using an AI solution like LVivo, Cardiac Ultrasound automatically moves to a hospital server, "behind the scenes" for visual selection and measurement. Includes multiple manual and visual procedures DIA CEO and co-founder Hila Goldman Aslan.

IoT-enabled Agricultural (IoTAg) monitoring is smart, connected agriculture's fastest-growing ... [ ] technology segment projected to reach $4.5 billion by 2025, according to PwC. AI, machine learning (ML) and the IoT sensors that provide real-time data for algorithms increase agricultural efficiencies, improve crop yields and reduce food production costs. According to the United Nations' prediction data on population and hunger, the world's population will increase by 2 billion people by 2050, requiring a 60% increase in food productivity to feed them. In the U.S. alone, growing, processing and distributing food is a $1.7 trillion business, according to the U.S. Department of Agriculture's Economic Research Service. AI and ML are already showing the potential to help close the gap in anticipated food needs for an additional 2 billion people worldwide by 2050.

Supercomputers help researchers study the causes and effects--usually in that order--of complex phenomena. However, scientists occasionally need to deduce the origins of scientific phenomena based on observable results. These so-called inverse problems are notoriously difficult to solve, especially when the amount of data that must be analyzed outgrows traditional machine-learning tools. To better understand inverse problems, a team from the US Department of Energy's (DOE's) Oak Ridge National Laboratory (ORNL), NVIDIA, and Uber Technologies developed and demonstrated two new techniques within a widely used communication library called Horovod. Developed by Uber, this platform trains deep neural networks (DNNs) that use algorithms to imitate and harness the decision-making power of the human brain for scientific applications. Because Horovod relies on a single coordinator to provide instructions to many different workers (i.e., GPUs in this case) to complete this process, large-scale deep-learning applications often encounter significant slowdowns during training.

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. When it comes to climate change and greenhouse gas emissions (GHGs), the United States is moving backwards, according to a report released earlier this year by the Rhodium Group, an independent research organization. The report says, "… progress in reducing U.S. GHG emissions was reversed in 2021, moving from 22.2% below 2005 levels in 2020 to only 17.4% in 2021, putting the U.S. even further off track from achieving its 2025 and 2030 climate targets." The U.S. Securities and Exchange Commission (SEC) took on the trend and recently detailed newly proposed rules that would require companies -- both foreign and domestic that are registered with the SEC -- to report climate impact and emissions information. The proposal aims to bring standardization via policy to what has, until now, been largely optional -- unlike the EU, which established similar reporting requirements in 2014.