Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. In preparation for Sunday's World Cup final between France and Croatia, ETH Zurich and ANYbotics decided to teach their quadruped robots some soccer moves, which included head shots, bicycle kicks, and the required fake injury (0:07): Alphabet's advanced tech division X has graduated a couple of flying robot projects recently: Loon and Wing. We posted earlier this week about Toyota AI Ventures' call for mobile manipulation startups, and here's a follow-up video with a bit more detail than was in the press release.

We've all heard the headlines: Video games cause addiction, violence, and distress. Ludectrophobia (a fear of video games - but we all knew that) has evolved since the 1980s as each decade brought new concerns. "Gaming disorder" is now even an official medical condition. Video game producer Johnny Chiodini says it's important to look at the good done by games. His YouTube series Low Batteries examines how video games help players cope with their mental health struggles.

Passage AI, a leader in AI-powered conversational interfaces, announced it has extended its natural language understanding/processing (NLU/P) capabilities to support over 150 languages natively, including simplified and traditional Chinese, French, German, Portuguese, Japanese and Spanish. Companies can now offer near instant responses to customers around the globe in their native tongue. "Passage AI-powered chatbots now enable 24/7 customer service responses for routine questions in all major languages, delivering a superior customer experience for consumers regardless of the language they speak," said Ravi N. Raj, CEO and co-founder of Passage AI. "The world is flat, so it is not surprising that our customers, some of the largest brands in the world, want support for multiple languages. Our customers have reported 95 percent or higher accuracy in field tests, which analysts have said is the leading benchmark for AI-powered chatbots in any industry, but particularly important for customer-facing interfaces." Market research firm Vanson Bourne, in a survey sponsored by Teradata, found that 80 percent of organizations are currently investing in AI, and on average each company has spent $6-8 million so far.

Technology has changed the game in nearly all industries over the last 20 years, shifting the focus away from traditional methods of getting things done. With the help of advanced software, hardware, and an ever-connected world through the Internet, companies of all shapes and sizes have been forced to implement fresh ideas and follow or create innovative ways of doing business. The most heavily impacted sectors include financial services, transportation, and e-commerce, but healthcare is starting to experience the disruption of technology thanks in part to artificial intelligence. The change could not have come at a more pressing time for some of the worldâ s largest health organisations, including the U.K.'s NHS (National Health Service). A quick search of NHS online produces hundreds of thousands of opinion pieces and research pointing to its struggle over the last decade in keeping up with demand from a growing patient population in the UK.

By and large the behavior of stochastic gradient is regarded as a challenging problem, and it is often presented in the framework of statistical machine learning. This paper offers a novel view on the analysis of on-line models of learning that arises when dealing with a generalized version of stochastic gradient that is based on dissipative dynamics. In order to face the complex evolution of these models, a systematic treatment is proposed which is based on energy balance equations that are derived by means of the Caldirola-Kanai (CK) Hamiltonian. According to these equations, learning can be regarded as an ordering process which corresponds with the decrement of the loss function. Finally, the main results established in this paper is that in the case of quasi-periodic environments, where the pattern novelty is progressively limited as time goes by, the system dynamics yields an asymptotically consistent solution in the weight space, that is the solution maps similar patterns to the same decision.

Humans are ingenious: We have unique abilities to predict the consequences of observed actions, remember the most relevant experiences from the past, and transfer knowledge from previous observations in order to adapt to novel situations. The episodic memory which encodes contextual, spatial and temporal experiences during development plays a vital role to introduce such cognitive abilities in humans. A core challenge in cognitive robotics is compact and generalizable mechanism which allow for encoding, storing and retrieving spatiotemporal patterns of visual observations. Such mechanisms would enable robots to build a memory system, allowing them to efficiently store gained knowledge from past experiences and both recalling and applying such knowledge in new situations. Inspired by infants that learn by observing and memorizing what adults do in the same visual setting, we investigate in this paper how to extend cognitive abilities of robots to autonomously infer the most probable behavior and ultimately adapt it to the current scene. Considering the situation of the humanoid robot ARMAR-IIIa standing in front of a table with a juice carton (see Figure 1) one can ask what the most suitable action is and how it would best be performed. To achieve this goal, we introduce a novel deep neural network architecture for encoding, storing, and recalling past action experiences in an episodic memory-like manner.

Alejandro Saucedo (Founder @ Exponential Technologies) and Donald Whyte (Software Engineer @ Engineers Gate) @ Moscow Python Conf 2017 "There is a lot of hype about deep learning and everything AI, however behind all the noise there is a set of solid concepts and algorithms that have massive potential if used in the right way and with the right data. In this talk we will provide you with the key concepts you will need to build a solid understanding around the core of Machine Learning. We will also cover key Deep Learning concepts and examples using Tensorflow that will help you understand the real potential of Deep Learning in practical applications. This talk will provide a theoretical overview that will then be put in practice in the Deep Learning workshop". Slides: https://conf.python.ru/python-ai-all-... Note: On 7.37 - 7.47 Alejandro says: "The hard part is how do we learn the hyperparameters of the function itself m and c, that is what ML is about.

A team of scientists from Imperial College London and the University of Göttingen have teamed up to create a'next generation' bionic hand. This bionic hand is special because it uses artificial intelligence to improve its functionality. A schematic of the bionic hand the team have built.University of Göttingen The work carried out by the team and published in Science Robotics, shows that with the help of machine learning, fluid motion of prosthetics can be achieved. At the moment, movement of prosthetics is controlled by motors that are stimulated with external signals from surrounding muscles in the amputee. In the new bionic hand, however, the patient's intentions are interpreted by a human-machine interface which then sends signals to the prosthetic.

Buzzwords like "big data" and "artificial intelligence" have become commonplace in many of today's business conversations, but what exactly do they mean--and what do they mean for the luxury consumer? The Chinese government's "Next Generation Artificial Intelligence Development Plan" was established in 2017, making artificial intelligence (AI) a national priority for China. Simply put, today's high-net-worth buyers still want a traditional tailor-made buying experience, but they want it fast and hassle-free. Artificial intelligence and big data are what will help give them that. Big data is a term for the huge volume of varied and unstructured data (sounds, images, texts, messages, transactions, videos, social networks, etc.) that companies collect both online and off, from employee counts to weather histories.

Alzheimer's disease affects millions of people each year. According to the Alzheimer's Association, it's the 6th leading cause of death in the United States, killing more seniors than breast cancer and prostate cancer combined. It's also expensive -- early diagnosis could save an estimated $7.9 trillion in medical and care costs. Researchers at Unlearn.AI, a startup that designs software tools for clinical research, think that artificial intelligence has a valuable role to play in personalizing diagnosis and treatment. In a paper ("Using deep learning for comprehensive, personalized forecasting of Alzheimer's Disease progression") published on the preprint server Arvix.org,