Getting the'side-eye' look from your dog can certainly make it seem like they are judging you, and a new study suggests they really could be. Researchers at the University of Vienna found that pooches can tell when we dangle a treat out of their reach to be cruel, or when it is just an accident. What's more, they also act differently towards us depending on our perceived intention, as they appear more patient with the clumsy than the mean. Only a few animals have previously been shown to be able to make social evaluations of humans in this manner, including chimpanzees, capuchin monkeys and African grey parrots. The team recruited 96 pet dogs for the experiment, and each was presented with one of two scenarios.
Pet dogs know when you intend to give them a treat, even if you drop it where they can't get to it Dogs can understand when humans mean well, even if they don't get what they want from us. Prior to this work, the ability to distinguish between a human being unwilling or unable to perform a task had only been found in non-human primates. The close social bond between humans and canines is well established, but researchers have a limited understanding of if and how dogs comprehend human intent. To see if pet dogs can distinguish between intentional and accidental actions by strangers, Christoph Völter at the University of Veterinary Medicine Vienna in Austria and his colleagues ran tests with humans offering dogs food while the animals' body movements were tracked using eight cameras. Each dog and human were separated by a transparent plastic panel with holes that a slice of sausage could be passed through.
Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology's impact on society. This episode we talk with Mark Coeckelbergh about AI as a story about machines and where are we heading in creating human level intelligence, moral standing and robot-animal interfaces, technology determinism, environmental impacts of robots and AI, energy budgets, politics and AI, self-regulation and global governance for global issues. Mark Coeckelbergh is Professor of Philosophy of Media and Technology at the University of Vienna and author of more than 15 books including AI Ethics (MIT Press), The Political Philosophy of AI (Polity Press), and Introduction to Philosophy of Technology (Oxford University Press). Previously he was Vice Dean of the Faculty of Philosophy and Education, and President of the Society for Philosophy and Technology (SPT). He is also involved in policy advise, for example he was member of the High Level Expert Group on AI of the European Commission.
Are passionate about contributing to solutions that benefit science and business at the same time; Are able to communicate with university and business stakeholders; Have knowledge of several of the following techniques: mathematical programming, dynamic programming, reinforcement learning, supervised learning, simulation, business analytics, heuristics, etc.; Can code in one or more of the following programming languages: Python, Java, C, Delphi, Matlab, and R; Have, or will shortly acquire, an MSc degree in Industrial Engineering, Operations Research, Applied Mathematics, or related programme; Possess excellent communication skills and are proficient in English.
The 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJACI-ECAI 2022) took place from 23-29 July, in Vienna. The title of her talk was "Engineering sociality and collaboration in AI systems". Robots are widely used in industrial settings, but what happens when they enter our everyday world, and, specifically, social situations? Ana believes that social robots, chatbots and social agents have the potential to change the way we interact with technology. She envisages a hybrid society where humans and AI systems work in tandem.
The 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJACI-ECAI 2022) took place from 23-29 July, in Vienna. In this post, we continue our round-up of the invited talks, summarising the presentation by Ana Paiva, University of Lisbon and INESC-ID. The title of her talk was "Engineering sociality and collaboration in AI systems". Robots are widely used in industrial settings, but what happens when they enter our everyday world, and, specifically, social situations? Ana believes that social robots, chatbots and social agents have the potential to change the way we interact with technology.
The 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJACI-ECAI 2022) took place from 23-29 July, in Vienna. As part of the conference there were eight fascinating invited talks. The title of her talk was "Panning for insights in medicine and beyond: New frontiers in machine learning interpretability". Mihaela began by explaining why the field of medicine is so complex. Differences between individuals, due to factors such as genetic background, environmental exposure, and life-style, lead to variations in symptoms, disease trajectories, and responses to treatments.
PriceHubble is a PropTech company with over 220 employees, set to radically improve the understanding and transparency of real estate markets based on data-supported insights. We aggregate and analyze a wide variety of large scale datasets, and apply state-of-the-art machine learning to generate high-quality valuations and predictive analytics for the real estate market. We are headquartered in Zürich, with offices in Berlin, Hamburg, Paris, Vienna, Prague, Amsterdam and Tokyo. We work on international markets and we are backed by world-class investors. We have a startup environment, low bureaucracy, and an international team and business. You will be part of the Data Products team, heading a team of experienced ML and software engineers who build PriceHubble's Data and ML Platform.
The International Conference on Machine Learning (ICML) received nearly 5,000 submissions for its 2020 conference and accepted 1,088 papers. Machine Learning Center at Georgia Tech (ML@GT) researchers authored nine accepted papers. The papers explore topics like privacy, semantics in predictive agents, data science, and artificial intelligence. One paper, Boosting Frank-Wolfe by Chasing Gradients, proposes a new state-of-the-art algorithm for constrained optimization, an area already addressed in work accepted in 2019. "I think we're going to see a lot more work moving in the direction of general artificial intelligence, especially work that is trying to combine learning and reasoning," said Le Song, an associate director at ML@GT.