In Shenzhen, even kindergartners have homework. You can see it in the workbook-laden backpacks weighing them down as they waddle through the school gates at 8 a.m. and back out again at 5 p.m. Many are not headed home yet. There are dance classes, piano lessons, English tutors, kung-fu sessions to get to. After classes, after dinner, it is time to tackle that homework.

If your garden is your pride and joy, then you'll know that it takes a lot of work to maintain. It doesn't have to be this way, though. The lawn is the jewel of any impressive garden. There really is something special about a perfectly manicured lawn, especially when you know the owner has probably put hours into its upkeep. You can cut that time considerably with a robotic lawn mower.

When making a start in a new field it is common to feel overwhelmed. You may lack confidence or feel as though you are not good enough or that you are lacking some prerequisite. You will explore these issues in this post and learn that such feelings can lead to actions that can consume a lot of time and resources and leave you feeling disappointed in yourself. You will learn that there are many paths through the field of machine learning and that like programming, it is a meritocracy. Feeling like you are not good enough or that you are lacking some skill that you think you must have before you can make a start in machine learning is dangerous thinking.

If you're a full-time employee and the business isn't in direct conflict or competition with your employer, it may not be a problem. But you'd need to make a formal disclosure to your employer to be sure. Questions like this seldom have yes or no answers, but the details should be in the employer's code of ethics and conduct. "Like most large companies, Kimberly-Clark maintains dozens of policies, procedures, and instructions to guide employees," says Ronnie Kann, director of global ethics and compliance at Kimberly-Clark. "These are only effective if employees know there is a policy, where to find that policy, and what the policy requires."

The UK government has announced £13m ($16.7m) in funding to support 40 artificial intelligence (AI) and data analytics projects to enhance productivity and improve customer service. The projects include an online "bot" for quick legal advice, voice recognition technology to detect fraudulent insurance claims, and AI software to review business expenses. Being developed by Intelligent Voice, Strenuus and the University of East London, the AI solution will combine AI and voice recognition technology to detect and interpret emotion and linguistics to assess the credibility of insurance claims. Insurance fraud cost the UK £3bn in 2017, which is equal to £10,400 per fraudulent claim, and costing consumers an additional £50 per policy. Another project is an analysis tool, which uses a 3D image recognition system to evaluate images captures by drone.

Best known for its IT solutions for the digital enterprise, BMC has expanded its partnership with IBM, building on a cognitive collaboration introduced in 2017, where AI technologies from IBM Watson were seamlessly integrated into BMC Helix, BMC's cognitive service management solution. The BMC Helix solution is expanding with the addition of an insight engine from IBM and additional clouds of choice, including the IBM Cloud. "The most powerful outcome of BMC Helix is choice," said Nayaki Nayyar, president of Digital Service Management at BMC. "With BMC Helix, you gain the ability to choose the cloud that you want, and by combining the power of IBM Watson, deliver cognitive service experiences of the future," he commented. With the addition of an insight engine from IBM, BMC is extending and enriching the cognitive capabilities of its solution. By offering BMC Helix on the IBM Cloud platform, enterprises can run the product on their cloud of their choice – including IBM Cloud, Azure, AWS, and BMC Cloud – significantly improving operational efficiencies to deliver speed, scale, and cost savings.

Facebook wants to create its own chips to deliver the type of computing speeds necessary to take the next leap forward in artificial intelligence, according to a report in the Financial Times. The company also wants to make a digital assistant – similar to Apple's Siri or Amazon's Alexa – that can have conversations with users and that has "common sense." Yann LeCun, the company's chief AI scientist and a pivotal figure in modern AI, said the company also wants to use AI to help monitor video in real time and assist human moderators with content selection. Though the company is working with chip companies like Intel on the new chips, it is not ruling out the possibility of developing its own. "Facebook has been known to build its hardware when required -- build its own ASIC, for instance. If there's any stone unturned, we're going to work on it," LeCun said.

In this tutorial, you will learn how to train a Keras deep learning model to predict breast cancer in breast histology images. Back 2012-2013 I was working for the National Institutes of Health (NIH) and the National Cancer Institute (NCI) to develop a suite of image processing and machine learning algorithms to automatically analyze breast histology images for cancer risk factors, a task that took trained pathologists hours to complete. Back then deep learning was not as popular and "mainstream" as it is now. For example, the ImageNet image classification challenge had only launched in 2009 and it wasn't until 2012 that Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton won the competition with the now infamous AlexNet architecture. To analyze the cellular structures in the breast histology images we were instead leveraging basic computer vision and image processing algorithms, but combining them in a novel way.

Want to expand your knowledge of the AI world? Make sure you're following these industry leaders on Twitter. The world of artificial intelligence (AI) and robotics is evolving all the time, with job opportunities and new products springing up constantly. It's never been a better time for someone interested in building a career in AI. While the jobs, companies and skills may vary, the wider industry trends are always worth keeping an eye on if you're serious about an AI career.

AI and Games is a crowdfunded show and needs your support. You can help fund this series on Paypal, KoFi and Patreon (where you can get access to additional content). You can follow AI and Games on Facebook and Twitter: http://www.facebook.com/AIandGames I take a look at the potential MOBAs have to become the next big thing in AI research and some of the work that's already been achieved in academia and corporate R&D. "Varus As We Fall" from the League of Legends Soundtrack "Pre-Game" from the DOTA2 Soundtrack "Legends Never Die" from the League of Legends Soundtrack