Value functions are crucial for model-free Reinforcement Learning (RL) to obtain a policy implicitly or guide the policy updates. Value estimation heavily depends on the stochasticity of environmental dynamics and the quality of reward signals. In this paper, we propose a two-step understanding of value estimation from the perspective of future prediction, through decomposing the value function into a reward-independent future dynamics part and a policy-independent trajectory return part. We then derive a practical deep RL algorithm from the above decomposition, consisting of a convolutional trajectory representation model, a conditional variational dynamics model to predict the expected representation of future trajectory and a convex trajectory return model that maps a trajectory representation to its return. Our algorithm is evaluated in MuJoCo continuous control tasks and shows superior results under both common settings and delayed reward settings.

When the Amazon Prime Day deals roll into town in July, it's a no-brainer that the Amazon Echo Dot will get a big discount like it does every year. The thing is, it'll be nowhere near as good as this one - and it ends at 9am tomorrow. This is a UK-only deal, but we've rounded up the latest top deals in the US over on our Memorial Day sales page. UK readers, be sure to check out the Bank Holiday sales this weekend too. We're expecting Prime Day to bring the Echo Dot down to £29.99 as per usual, or £24.99 at the very best if Google aggressively price cuts the Google Home Mini as the search giant can't help but wind Amazon up any chance it gets with its line of rival smart speakers.

I have seen several posts in this subreddit asking for resources for learning Machine Learning as part of their CS Career. I have listed some of my Python Machine Learning videos below and I hope that people with an interest in Python and learning MI would find it useful. Please feel free to give feedback as I'm always looking to improve my Computer Science skills.

Google AI has introduced a deep learning based approach that generates depth prediction from videos where both camera and subject are in motion. Humans are very good at making sense of the 3D world through 2D projections. Even in complex environments with objects in motion we can still form a fairly sound understanding of where everything is. Computer vision however does not do so well in this regard. Researchers in the field have long sought to develop a mechanism capable of achieving 3D world understanding by reconstructing geometry and depth ordering from 2D image data via computation.

Artificial Intelligence (AI) is the new electricity of our times. That's what Chris Duffey, creative technologist says about this incredible technology revolutionizing industries the world over. His new book Superhuman Innovation showcases how AI will supercharge the workforce, the world of work, and can be harnessed to deliver powerful change. It is a practical guide to how AI and Machine Learning are impacting not only how businesses, brands, and agencies innovate, but also what they innovate: products, services and content. In this world of product and pricing parity, the delivery of superior service experience has become the new marketing, and the new real competitive edge. Superhuman Innovation discusses how AI will serve the superstar innovators of tomorrow by enabling them to see deeper insights and set sail for higher goals.

Transcribing content from structural images, e.g., writing notes from music scores, is a challenging task as not only the content objects should be recognized, but the internal structure should also be preserved. Existing image recognition methods mainly work on images with simple content (e.g., text lines with characters), but are not capable to identify ones with more complex content (e.g., structured symbols), which often follow a fine-grained grammar. To this end, in this paper, we propose a hierarchical Spotlight Transcribing Network (STN) framework followed by a two-stage "where-to-what" solution. Specifically, we first decide "where-to-look" through a novel spotlight mechanism to focus on different areas of the original image following its structure. Then, we decide "what-to-write" by developing a GRU based network with the spotlight areas for transcribing the content accordingly. Moreover, we propose two implementations on the basis of STN, i.e., STNM and STNR, where the spotlight movement follows the Markov property and Recurrent modeling, respectively. We also design a reinforcement method to refine the framework by self-improving the spotlight mechanism. We conduct extensive experiments on many structural image datasets, where the results clearly demonstrate the effectiveness of STN framework.

Art generated by Artificial Intelligence (AI), or more accurately Machine Learning (ML) is increasingly making not only technology news, but also being reported in the mainstream mass media. As the final season of Game of Thrones continues, this is a timely glance at the application of Machine Learning (ML) and Artificial Intelligence (AI) to both the books and the plots of the TV shows. In a previous post the potential disruption to employment opportunities and work routines was discussed, with reference to the increasing utilisation of Machine Learning in the work place. Now, for those who fear this development, there is a handy tool to determine the likelihood of this impacting upon you. The late and great Terry Pratchett encapsulated the difficulty of discussing aspects of Quantum Physics, (let alone quantum computing and machine learning) when he wrote: 'It's very hard to talk quantum using a language originally designed to tell other monkeys where the ripe fruit is.' (Terry Pratchett, Night Watch, … Much of the mainstream coverage of MWC19 focused on the products, innovations and devices that will be more familiar to the average consumer.

UK media coverage of artificial intelligence is dominated by industry products, announcements and research, according to a new study by the Reuters Institute for the Study of Journalism. The factsheet, An Industry-Led Debate: How UK Media Cover Artificial Intelligence, is based on an analysis of eight months of reporting on AI, in six mainstream UK news outlets. The report's lead author, J. Scott Brennen, said AI coverage has been developing against a background of economic disruption in the media industry, with cuts to speciality reporting, including science and technology journalism. "Despite these challenges, mainstream news outlets remain a key space for, and influence on, public discussion. "However, by amplifying industry's self-interested claims about AI, media coverage presents AI as a solution to a range of problems that will disrupt nearly all areas of our lives, often without acknowledging ongoing debates concerning AI's potential effects.

The Game of Thrones ended this week and with it potentially tons of HBO Now subscriptions as well. That was clearly the morning-after chatter on Twitter. Why continue paying now that the show is history? To pay or not to pay and why do I have to subscribe to so many services I rarely watch are also huge questions in households that are being deluged with offers for more and more subscription services. This year alone, we'll see new ones from Apple and Disney, with others down the pike from WarnerMedia and NBCUniversal.

BENGALURU: Mission Admission 2019, a two-day higher education seminar and expo conducted by The Times of India to equip students with skills to make informed career choices, will kick off on Saturday at White Orchid Convention Centre, near Manyata Tech Park, Nagawara. From counsellors who will guide students on how to crack competitive examinations such as CET and ComedK UGET, to speakers who will guide those looking to pursue higher studies in art, design, visual effects, acting and photography, Mission Admission will be a one-stop shop for students looking for guidance. Entry for the event is free. Kannada filmmaker Indrajit Lankesh, who is making his Bollywood debut soon, said: "I am looking forward to interacting with students and speak about filmmaking as a career, especially in the context of the digital content boom." Tapping technologies With Bengaluru being the startup capital and entrepreneurship being the flavour of the season, the expo will help students understand careers in areas such as Artificial Intelligence, Machine Learning and Big Data.