Personal Note: I'm really honored to share this conversation. I really hope you enjoy listening to it as much as I enjoyed talking to Dr. Marc Lanctot. In this interview, they talk all about Research at DeepMind, Deep Learning Research, AlphaGo. They also talk all about Swift For Tensorflow and OpenSpiel. Dr. Marc Lanctot is a research scientist at Google DeepMind.

Computer scientists from the University of Edinburgh and Adobe Research have come up with a novel solution to the problem of making the movements of video game characters look natural. Scientists at the University of Edinburgh in the U.K. and Adobe Research used deep learning neural networks to help digital characters in video games move more realistically. The team trained a neural network on a database of motions by a live performer on a soundstage which they recorded and digitized. The network can adapt what it learned from the database to most scenarios or settings so characters move in natural-looking ways. The network is filling the gaps between a digital character's various poses and motions, intelligently and seamlessly stitching together these elements into a whole.

So how do we program a computer to translate human language? The simplest approach is to replace every word in a sentence with the translated word in the target language. This is easy to implement because all you need is a dictionary to look up each word's translation. But the results are bad because it ignores grammar and context. So the next thing you might do is start adding language-specific rules to improve the results.

Artificial intelligence (AI) has permeated enterprise operations to the point that it now determines an organization's success, including in the area of project management. In a report, Project Management Institute (PMI) examines how six AI technologies are affecting today's project managers and will affect project management operations in the future. PMI's AI Innovators: Cracking the Code on Project Performance (2019) found that in the next three years, project professionals expect overall AI usage to jump from 23% to 37% and the majority of respondents (81%) said their organizations are currently being affected by AI technologies. SEE: The ethical challenges of AI: A leader's guide (free PDF) (TechRepublic) "Project leaders are in the earliest stages of adopting AI to streamline--and improve--project work. AI technologies are already contributing to higher productivity and better quality," said Mark Broome, chief data officer at PMI. "For example, technology is decreasing the amount of time project managers need to spend on activities like monitoring progress and managing documentation--they can rely on AI for these more administrative tasks. The time saved can then be repurposed to more strategic and creative tasks and planning."

Scientists have developed artificial intelligence that can identify 200 species of birds from just a single photo, offering another way to quickly and cheaply monitor bird populations than the traditional in-person counts often used today. The technique, created by scientists at Duke University, uses deep learning, algorithms based on the way the human brain works. The researchers fed nearly 12,000 photos of birds into the computer program. The system analyzed the images, learning in-depth the physical traits of 200 species. The program was then able to examine a photo, determine the exact species, and explain how it came to that conclusion. It's a hooded warbler, and here are the features -- like its masked head and yellow belly -- that give it away," a Duke press release explained.

Deep generative models for graphs have shown great promise in the area of drug design, but have so far found little application beyond generating graph-structured molecules. In this work, we demonstrate a proof of concept for the challenging task of road network extraction from image data introducing the Generative Graph Transformer (GGT): a deep autoregressive model based on state-of-the-art attention mechanisms. In road network extraction, the goal is to learn to reconstruct graphs representing the road networks pictured in satellite images. A PyTorch implementation of GGT is available here. The proposed GGT model is designed for the recurrent generation of graphs, conditioned on other data such as an image, by means of the encoder-decoder architecture outlined in Figure 1.

As artificial intelligence (AI) and autonomous machines become more common in agriculture, the industry is going through enormous changes. Ofir Schlam, CEO and co-founder of Taranis, a leading precision agriculture intelligence platform, recently shared more information about these changes in an interview. Taranis is an AI-powered agriculture intelligence platform that was selected to be part of John Deere's startup collaborator. It uses sophisticated computer vision, data science and deep learning algorithms to enable farmers to make informed decisions. The platform is capable of monitoring fields and finding early symptoms of uneven emergence, weeds, nutrient deficiencies, disease or insect infestations, water damage and equipment issues.

Applications are invited for a PhD studentship, to be undertaken at Imperial College London (Electrical and Electronic Engineering Department). This studentship will form part of a newly established International Centre for Spatial Computational Learning http://spatialml.net, and a supervisory team will be allocated based on the student's interest from the Imperial College supervisors participating in the Centre. This is an exciting cutting-edge project involving close collaboration between Imperial College (UK), the University of California Los Angeles (USA), the University of Toronto (Canada), and the University of Southampton (UK). The successful candidate will be based at Imperial but will have the opportunity to travel frequently to America to attend research meetings and for a placement period at either UCLA or Toronto. Traditional deep learning has been based on the idea of large-scale linear arithmetic units, effectively computing matrix-matrix multiplication, combined with nonlinear activation functions.

IBM announced a new slate of four free conferences throughout November designed to help developers interested in AI and cloud services. In a statement, the company said the conferences are designed to address "the unique needs of coders." The Digital Developer Conferences will be held in North America, Nov. 2, in India, Nov. 9, in Europe, Nov. 14, and in Asia, Nov. 23. "At this free online conference, get hands-on experience and engage with expert developers who will share insights on topics ranging from AI/ML innovation from IBM AI Research, open-source deep learning, model bias identification, multicloud best practices, cloud security with DevSecOps and getting the most out of cloud native development," the company wrote on the conference landing page. "See client stories and how technology is being deployed to address some of the biggest issues facing developers today."

DeepMind says it has created the first artificial intelligence to reach the top league of one of the most popular esport video games. It says Starcraft 2 had posed a tougher AI challenge than chess and other board games, in part because opponents' pieces were often hidden from view. Publication in the peer-reviewed journal Nature allows the London-based lab to claim a new milestone. But some pro-gamers have mixed feelings about it claiming Grandmaster status. DeepMind - which is owned by Google's parent company Alphabet - said the development of AlphaStar would help it develop other AI tools which should ultimately benefit humanity.