Some of the biggest challenges facing modern game development can be found in open-world game design: how to build large, vibrant and interesting locales for players to explore. Artificial intelligence can often by adopted to address this challenge by creating interesting and dynamic environments that enhance the overall experience for the player. In this article, we take a look at the methods and design decisions behind the ever increasing game worlds in Ubisoft's Far Cry series. Far Cry is renowned for an open approach towards problem solving: allowing players to explore the world in a manner that suits them. Originally starting out as an open -- albeit linear -- gameplay experience, the series has became increasingly more adventurous in its design; with maps not only increasing in size but also with the introduction of more interactive environments and wildlife.

DeepMind's AlphaStar AI bot has reached Grandmaster level at StarCraft II, a popular battle strategy computer game, after ranking within the top 0.15 per cent of players in an online league. StarCraft II is a complex game and has a massive following with its own annual professional tournament - StarCraft II World Championship Series - that involves the best international teams competing over a prize pot over $2m. AlphaStar, however, isn't quite good enough to compete in that competition. Instead it set its eyes on a much smaller contest on Battle.net, the game's official online league hosted by China-friendly gaming biz Blizzard Entertainment. Researchers at Google-stablemate DeepMind entered its bot AlphaStar into a series of blind games, where its opponents had no idea it was playing against a computer.

Machine learning (ML) is an application of artificial intelligence (AI) wherein the system looks at observations or data, such as examples, direct experience, or instruction, figures out patterns in data and predicts events in the future based on the examples that we provide. Machine learning is seeing more and more use across industries for various reasons: vast amounts of data are being captured and made available digitally; processing of large amounts of data has become cost-effective due to the increased computing power now available at affordable prices; and various open source frameworks, toolkits and libraries are available that can be used to build and execute ML applications. Specifically in healthcare, ML has led to exciting new developments that could redefine cancer diagnosis and treatment in the years to come. ML can increase access to treatment in developing countries which don't have enough specialist doctors that can treat certain diseases, it can improve the sensitivity of detection, add more value in treatment decisions, and it can help personalize treatment so that each patient gets the treatment that's best for them. In many cases they can even add to workflow efficiency in hospitals.

The Pentagon says artificial intelligence will help the US military become still more powerful. On Thursday, an advisory group including executives from Google, Microsoft, and Facebook proposed ethical guidelines to prevent military AI from going off the rails. The advice came from the Defense Innovation Board, created under the Obama administration to help the Pentagon tap tech industry expertise, and chaired by Eric Schmidt, Google's former CEO and chairman. Last year, the department asked the group to develop ethical principles for its AI projects. On Thursday, the group released a set of proposed principles in a report that praises the power of military AI while also warning about unintended harms or conflict.

Recently, Malaysia was ranked first in the best healthcare in the world category of 2019 International Living Annual Global Retirement Index. It was also ranked first for its sophisticated healthcare infrastructure by the International Living website. Malaysia has also identified nine hospitals to boost medical tourism in the country. While this spells good news for hospitals, one cannot discount the fact that there will be a lot of competition among small and big players to attract patients. To remain a step ahead of the competition, hospitals need to offer the best care and experience to the patients.

Justice Sharad Arvind Bobde, who will be succeeding Chief Justice of India Ranjan Gogoi has proposed the usage of high-end technology including Artificial Intelligence in courts. Justice Bobde who will be the 47th Chief Justice of India has asserted that there may be a need for some minor changes in the justice system of the country by the inclusion of the use of technology such as artificial intelligence. "Justice delivery system is good, it might require some minor changes, including the use of technology like artificial intelligence. It's a good system, you need to use some other things," Justice Bobde told ANI. He said the justice delivery system is good, but also pressed on the need to introduce some long term and short-term measures to make the justice delivery system better.

Some amazing--as well as some downright freaky--innovations in artificial intelligence and machine learning were detailed at the recent Decoded Future NYC Summit, presented by Stylus. Take, for example, technology that will watch consumer faces as they shop online, recording smiles, frowns, or other gestures to measure interest in a product. In the near future, consumers could also be interacting "face-to-face" with virtual assistant machines that have lifelike personalities, emotional responses and character. While those advances may be a few years away, AI and machine learning have already become customary among brands and retailers who are looking to track the right trends in style, color, and pricing. The major players have been taking advantage of this technology for years.

Although Neo4j is often used by application developers, there's a growing trend of data scientists using graphs to help with their work. In this session, we'll look at how to combine Neo4j and the Cypher query language with the Python data science stack including libraries such as Pandas and matplotlib. We'll look at how to do exploratory data analysis as well as find insights into networked datasets using the newly released graph algorithms package through the use of hands-on tutorials. You will need your own laptop. Please download and install Neo4j and Python prior to the session.

Google today announced the preview launch of TensorBoard.dev "You'll now be able to host and track your ML experiments and share them publicly, no setup required. Simply upload your logs and share the URL so that others can see the experiments and what you're doing with TensorBoard," Google VP of engineering Megan Kacholia said onstage today at TensorFlow World in Santa Clara, California. TensorFlow Enterprise is made to deliver an optimized version of its open source machine learning framework TensorFlow for large businesses. It works with Google's AI Platform and Kubernetes Engine as well as optimized versions of Deep Learning VMs and Deep Learning Containers. The service is made to supply up to 3x improvements in data reading -- the result of changes to how TensorFlow reads and caches files -- and up to 3 years of support for security patches and select bug fixes.

Nationwide Building Society, a finance firm based in the United Kingdom, has just announced they will be investing in a "behavioral analytics startup," known as Scaled Insights. According to Nationwide, Scaled Insight's speech analysis AI will be used to build individual profiles for their clientele, in order to tailor the bank's communications to fit each customer's needs -- or "linguistic personality," as they're calling it. The mainstream media is reporting on how a hospital in Leeds is already using this technology to help patients, perhaps in order to present this new AI technology as benevolent. But the truth is that no large corporation ever makes a large investment without expecting an even larger return. Nationwide is expected to pump $5.31 billion into new technologies over the next five years.