The ubiquity of embodied gameplay, observed in a wide variety of animal species including turtles and ravens, has led researchers to question what advantages play provides to the animals engaged in it. Mounting evidence suggests that play is critical in developing the neural flexibility for creative problem solving, socialization, and can improve the plasticity of the medial prefrontal cortex. Comparatively little is known regarding the impact of gameplay upon embodied artificial agents. While recent work has produced artificial agents proficient in abstract games, the environments these agents act within are far removed the real world and thus these agents provide little insight into the advantages of embodied play. Hiding games have arisen in multiple cultures and species, and provide a rich ground for studying the impact of embodied gameplay on representation learning in the context of perspective taking, secret keeping, and false belief understanding. Here we are the first to show that embodied adversarial reinforcement learning agents playing cache, a variant of hide-and-seek, in a high fidelity, interactive, environment, learn representations of their observations encoding information such as occlusion, object permanence, free space, and containment; on par with representations learnt by the most popular modern paradigm for visual representation learning which requires large datasets independently labeled for each new task. Our representations are enhanced by intent and memory, through interaction and play, moving closer to biologically motivated learning strategies. These results serve as a model for studying how facets of vision and perspective taking develop through play, provide an experimental framework for assessing what is learned by artificial agents, and suggest that representation learning should move from static datasets and towards experiential, interactive, learning.

There are over 15 distinct communities that work in the general area of sequential decisions and information, often referred to as decisions under uncertainty or stochastic optimization. We focus on two of the most important fields: stochastic optimal control, with its roots in deterministic optimal control, and reinforcement learning, with its roots in Markov decision processes. Building on prior work, we describe a unified framework that covers all 15 different communities, and note the strong parallels with the modeling framework of stochastic optimal control. By contrast, we make the case that the modeling framework of reinforcement learning, inherited from discrete Markov decision processes, is quite limited. Our framework (and that of stochastic control) is based on the core problem of optimizing over policies. We describe four classes of policies that we claim are universal, and show that each of these two fields have, in their own way, evolved to include examples of each of these four classes.

Eivind Meyer is currently working on his Master's thesis, completing his five-year integrated Master's degree in Cybernetics and Robotics at the Norwegian University of Science and Technology (NTNU) in Trondheim. Having specialized in Real Time Systems, his research interests focus on adopting state-of-the-art Artificial Intelligence methods for Autonomous Vehicle Control. Haakon Robinson is a PhD candidate at the Norwegian University of Science and Technology (NTNU). He received a Bachelors degree in Physics in 2015 and completed a Masters degree in Cybernetics and Robotics in 2019, both at NTNU. His current work investigates the overlap between modern machine learning techniques and established methods within modelling and control, with a focus on improving the interpretability and be-E Meyer et al.: Preprint submitted to Elsevier Page 15 of 16 Taming an ASV for path following and collision avoidance using DRL havioural guarantees of hybrid models that combine first principle models and data-driven components.

I covered The AI Summit in New York last week because I wanted to learn more about AI and Machine Learning. According to Tractica, AI is being implemented globally. AI and Machine Learning used in many verticals and processes. For example, when I compose an email using GMAIL, I received suggestions on how to finish a sentence. To use the GMAIL suggestion, I can tap the right arrow button on my keyboard.

Demonstrating how far artificial intelligence (AI) reaches industrial manufacturing, general purpose graphics processor unit (GPU) and edge computing provider, Aetina has partnered with customised equipment supplier, Ke Cheng to bring AI computing into original automated visual inspection (AVI) equipment to raise the accuracy ratio of detection to 90 per cent. The result is faster operation, adds the company. In the past, AVI equipment performance could be affected by colour differences and height. Ke Cheng brought system integration and vision recognition expertise to upgrade the original AVI equipment with the Aetina Jetson AI computing platform. Ke Cheng focuses on metal inspection, customised system integration services and the development and optimisation of vision inspection software.

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, industry partnerships, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz. Our intent is to provide you a one-stop source of late-breaking news to help you keep abreast of this fast-paced ecosystem. We're working hard on your behalf with our extensive vendor network to give you all the latest happenings. Be sure to Tweet Above the Trend Line articles using the hashtag: #abovethetrendline.

SAN FRANCISCO, Dec. 17, 2019 (GLOBE NEWSWIRE) -- Holberton School, the two-year tuition-deferred college alternative educating the next generation of digital workers, announced the launch of their brand new Machine Learning curriculum which will be available at all eight world-wide Holberton campuses. The announcement was made at the flagship San Francisco campus featuring Grammy award-winner NE-YO, Black Girls Code founder and CEO Kimberly Bryant and representatives from Google (Tensorflow) and IBM. "Machine Learning, and by extension Artificial Intelligence, are increasingly dominating how we interact with technology at all levels, and the need for diversity has never been so urgent," said Gabriela de Queiroz, founder, AI Inclusive and R-Ladies. "Having programming skills isn't enough -- we need people who are aware of the ethical implications of AI, who can bring their diverse backgrounds, experiences, and perspectives to the workplace and incorporate them into the algorithms that will increasingly play a major role in healthcare, safety, and every other element of our lives." Machine Learning, which gives computers the capability to learn without being explicitly programmed, is already in use across the globe and is rapidly supplementing, and even replacing, traditional software development.

By Padmaja Ruparel 2019 saw the Indian entrepreneurial ecosystem make a paradigm shift. The country's startup landscape saw the emergence of seven new unicorns and value creation of $90 billion. Little wonder, then, that India is globally ranked third in its number of startups, behind only the US and China. The first half of 2019 saw $3.9 billion invested across 292 domestic investment deals, marking an increase of more than 44% over the same period in 2018. Emerging startups also benefited from the windfall.

Fuelled by unprecedented international investment, groundbreaking advances in artificial intelligence and inclusive immigration policies, Canada's innovation economy has seen explosive growth. In fact, over the last five years, the Greater Toronto Area's tech sector grew by more than 50 per cent. Now with more than 241,000 employees, the GTA has become an innovation powerhouse on par with cities like New York and Seattle. And VC investment in Canadian startups reached record levels (in the first half of 2019 alone, nearly $3.3 billion investments were made), and the Deutsche Bank ranked Canada as the best country in the world for social entrepreneurship. But while things might be looking up here at home, the world faces unprecedented challenges as we head into the next decade.

The Mayor, a green cube with a top hat, goes "kaboom" in Wattam. The Mayor, a green cube with a top hat, goes "kaboom" in Wattam. The video game designer Keita Takahashi is best known for Katamari Damacy, released in 2004. It's about a god named the "King of All Cosmos" who, while drunk, accidentally destroys the stars in the sky. His son "The Prince" is left to clean up his mess by rolling up objects on Earth into sticky masses that grow so large they become new stars.