These strong AI foundations were built with the help of companies such as Google, Amazon, IBM, and Microsoft which started their ascendance early. But that gap could close soon: China's tech trinity BAT is also building its AI ecosystems. There is Baidu's AI assistant/platform DuerOS, self-driving platform Apollo and deep learning platform Paddle Paddle. Alibaba has its Platform of Artificial Intelligence (PAI 2.0), the Tmall Genie voice assistant, and customer service chatbot Dian Xiaomi. Tencent has developed a cloud service, an open-source computing platform called Angel, Wechat AI, and robot reporter Dreamwriter.

On this week's Tech Tent we hear why China's determination to be a leading player in artificial intelligence could lead to tensions with the United States. We have two other reports on this week's programme. Her victory is being seen as a key moment in the battle against the internet scourge known as revenge porn. And in a report from Rahul Tandon in Kolkata, we find out why India's new Aadhaar biometric identity card scheme has become mired in controversy. For millions of people who have struggled to open a bank account or get access to government services without proof of identity, it has proved life-changing.

The average salary of a Machine Learning Engineer in the US is $166,000! By the end of this course, you will have a Portfolio of 12 Machine Learning projects that will help you land your dream job or enable you to solve real life problems in your business, job or personal life with Machine Learning algorithms. Come learn Machine Learning with Python this exciting course with Anthony NG, a Senior Lecturer in Singapore who has followed Rob Percival's "project based" teaching style to bring you this hands-on course. With over 18 hours of content and more than fifty 5 star rating, it's already the longest and best rated Machine Learning course on Udemy! You'll go from beginner to extremely high-level and your instructor will build each algorithm with you step by step on screen.

From Siri and Alexa to driverless cars and robots, artificial intelligence and the many devices AI inhabits are well integrated into our everyday lives. But as the technology advances, ethical and moral questions arise. Ten Years Hence, an annual lecture series sponsored by the University of Notre Dame's Mendoza College of Business, will explore advances in AI and the potential implications for the human community. The series "Automation, Robotics and Artificial Intelligence: The Decade Ahead" takes place on select Fridays from 10:40 a.m. to 12:10 p.m. in Mendoza's Jordan Auditorium. The Ten Years Hence speaker series explores issues, ideas and trends likely to affect business and society over the next decade.

Elon Musk is CEO of Tesla and SpaceX, has plans to colonize Mars, and thinks AI may turn humans into its pets. But beyond the hype and his enormous net worth and Twitter presence, here's how Musk's companies are actually taking on ... virtually every industry. Elon Musk thinks and acts on a larger, more cosmic scale than we're accustomed to from entrepreneurs. Elon Musk has become a household name synonymous with the future. Whether he's working on electric vehicles (Tesla) or sending rockets into space (SpaceX), his larger-than-life reputation attracts its fair share of hero-worship. Musk can get a hundred breathless reporters to write about him and his companies with little more than a concept drawing and a tweet. His main projects take on almost every major industry and global problem conceivable, and imagine a disruptive fundamental rewiring of that space or sector. Whether he can deliver on his vast promises is often beside the point. And Musk himself is more than happy to feed into this hype machine. We've decided to take a different kind of look into the Musk ecosystem. Rather than assess Elon Musk and his companies on promises and hype, we wanted to look at the ways in which his companies are or are not transforming the industries in which they live -- with numbers, hard evidence, and concrete demonstrations of disruption. Read on for a deep dive into just how the money, invention, and ingenuity of Elon Musk and his companies are transforming these vital industries. First with SolarCity and now with Tesla, eliminating our dependence on fossil fuels and instead drawing energy from the "giant fusion reactor in the sky" aka the sun has been one of Musk's priorities for more than a decade. SolarCity, his first attempt to make solar power mainstream and ubiquitous, was at the forefront of the early 2000s "solar gold rush." In some ways it was a failure, but it remains important to understand its trajectory to understand how Musk and Tesla plan to take on the problem of renewable energy. SolarCity grew to become the country's largest provider of residential solar, then suffered some very public financial problems before being purchased by Musk's other company, Tesla, for $2 billion. That 2016 acquisition was controversial, with many observers calling it a "thinly veiled bailout." And yet Tesla's continuation of SolarCity's work has helped make a stronger case for solar than SolarCity was ever able to make on its own. Elon Musk originally suggested the concept for the company that became SolarCity to his cousins, Peter and Lyndon Rive, in 2004. The concept for SolarCity emerged out of a simple realization: the clock was running low on fossil fuels. The need for a replacement was emerging fast. "If they started now," as Men's Journal reports Musk telling Lyndon in 2004, "They might rule the market."

Artificial intelligence, particularly its applications in health, finance and the automotive sector, attracted US$12 billion of investment from venture capitalists globally last year, double the volume in 2016, according to a report by KPMG. AI pushed total venture capital (VC) investment in China to a record high of US$40 billion in 2017, up 15 per cent from the previous year. China accounted for five of the world's 10 biggest venture capital investments in the fourth quarter, the data released on Thursday shows. And more of the companies receiving the financing are electing to plough that money into AI development. Didi-Chuxing, China's top ride-hailing company, received US$4 billion in a round of fundraising led by Softbank in December, in part to enhance their AI capabilities. That was the largest venture capital investment globally in the fourth quarter.

Growing investment and greater access to data about people is giving China the edge in the race to develop artificial intelligence, according to news reports Thursday. "The Chinese government's thoughtful investment in AI is a huge accelerator," Andrew Ng, a former Google executive who now runs an AI start-up company, told The Wall Street Journal. Western concerns about privacy and "the ethics of letting machines make important decisions" have led to new policies over collecting personal data and deploying AI, the Journal reports. "Ultimately, AI advances are inextricably founded on the broad use of data to train machines as they go about learning," said Brad Smith, Microsoft's president and chief legal officer. "The question is whether privacy laws will constrict AI development or use in some parts of the world," he added.

More melted fuel has been found at the bottom of the Fukushima power planet, seven years after Japan's worst nuclear disaster. Tokyo Electric Power Company (TEPCO), the operator of Japan's crippled nuclear plant, says a long telescopic probe has successfully captured images of the fuel inside the plant's Unit 2 primary containment vessel. The images showed that at least part of the fuel breached the core, falling to the vessel's floor. TEPCO says that that the status inside the primary containment vessel is still stable, and that there are no changes in radiation levels at the site boundaries of Fukushima Daiichi's Nuclear Power Plant. A massive earthquake and tsunami in 2011 caused three reactors at the Fukushima plant to melt.

Check out the session "AI in personal finance: More than just chatbots" at the Artificial Intelligence Conference in New York, April 29-May 2, 2018. Hurry--best price ends February 2. Here's what we'll be watching in the coming year. AI is sweeping across all industry sectors, including financial services. AI touches customer interactions (voice services like Siri and dialog systems), fraud detection, trading, and risk management (machine learning), and is being used to automate many back-office tasks (robotic process automation). AI technologies are also giving rise to new fintech startups that use techniques like computer vision to unlock new datasets (e.g., aerial images).

China has been producing almost twice as many papers on artificial intelligence as the next highest-placed country in terms of publication volume for the field, a data analysis for Times Higher Education has shown. Data from Elsevier's Scopus database provided to THE illustrate China's huge drive on research in the area, with researchers in the nation notching up just over 41,000 publications from 2011 to 2015. In terms of publication volume, the US was second during the period with almost 25,500 publications while Japan was in third place (about 11,700) and the UK in fourth (about 10,100). However, although China scored high in terms of volume, it was only 34th in terms of field-weighted citation impact (which allows for differences in citations according to subject and year), suggesting that most of the papers were not of the same quality as those coming from the US (fourth for citation impact), for instance. Leading the world on this measure was Switzerland, with a citation impact score of 2.71, followed by Singapore (2.24) and Hong Kong (2.00), although all three of these produced fewer than 2,500 publications on AI over the time frame.