We've been using TensorFlow in daily research and engineering since it was released almost six months ago. We've learned a lot of things along the way. Because there are many subjective articles on TensorFlow and not enough helpful documentation, I've sprinkled in examples, tutorials, docs, and code snippets wherever possible. When it comes to machine learning, it is easy to focus on the tech (features, capabilities, benchmarks, etc). But good programmers know it is much harder to write code that humans will use, versus code that a machine can compile and execute. So my favorite thing about TensorFlow is the simple fact that everyone in the machine learning community is aware of it, most are open to trying it, and hopefully, enough of us will use it to make useful things.

In this talk, Mike Williams, Research Engineer at Fast Forward Labs, looks at how supervised machine learning has the potential to amplify power and privilege in society. Using sentiment analysis, he demonstrates how text analytics often favors the voices of men. Mike discusses how bias can inadvertently be introduced into any model, and how to recognize and mitigate these harms.

With all this talk about chatbots from Facebook and Microsoft, teaching artificial intelligence to be smarter has become a central topic of the tech world. But what about what AI can teach us? Ashok Goel, a computer science professor at Georgia Tech, put that question to the test when he added "Jill Watson" – and chatbot powered by IBM's Watson technology– to his list of of teaching assistants for an online course. The chatbot was so good at answering questions that students did not notice their TA was made of silicon until after they'd turned in their finals. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May.

Google has open sourced its language parsing model, SyntaxNet, calling the English version Parsey McParseface. The system understands human language with an incredible degree of accuracy, but attention has centred around its choice of name, which comes after people voted to name a science research ship Boaty McBoatface - it was in fact named after Sir David Attenborough. The open sourcing of Google's parsing model means that the broader community can employ the tool to up the game of artificial intelligence (AI). This means that machines could understand sentences from a standard database of English language journalism, the first step in their journey to take over the world. "At Google, we spend a lot of time thinking about how computer systems can read and understand human language in order to process it in intelligent ways," explained Google senior staff research scientist, Slav Petrov.

Nvidia's (NVDA) AI technology with Facebook (FB), Alphabet (GOOGL) and Microsoft (MSFT) is powering "superhuman" levels of inference, or artificial intelligence, Nvidia CEO Jen-Hsun Huang said Thursday, after the Tesla Motors (TSLA) partner blasted Q1 views on record deep-learning sales. "The truth is that nobody really knows how big this deep-learning market is going to be," Huang said on the company's earnings conference call. He referred specifically to gains that customer Microsoft was making with AI and deep learning. "The work that recently was done at Microsoft Research, they've achieved superhuman levels of inferencing … of image recognition and voice recognition that's really kind of hard to imagine," he said, "and these networks are now huge." In midday trading on the stock market today, Nvidia stock was up more than 14% and hit an all-time high at 40.30.

Last October, when Elon Musk gave Nvidia's CEO the 7th Tesla Model X delivery, we knew it was time to watch their stock (NVDA). In addition, we have been looking for investments that capitalize on autonomous cars, and/or hedge the major trends in artificial intelligence and automation. Today, strong earnings and optimism for Nvidia's "miracle" deep learning chip enabled their stock to break its all-time high from 2007. NVDA is now up by over 20% year-to-date, after gaining 66% last year. ETF PM currently has long positions in Nvidia (NVDA).

Apprehending criminals on the run proves to be a tricky task, especially in a big city. With several exit strategies readily available, criminals can escape on foot or via public transport (such as via bus or subway), or by driving a car. On top of this, there are shops, alleyways, and intersections galore. Of course, there are also a ton of other people. All of this creates a high risk of failure for police.

The boom in AI promises to enrich our lives. AI assistants keep our schedules in order; robot "crew" members help us on cruises; and "swarm AI" even offers the chance for us to win big in the gambling world. But there's a dark side of the coin as well: AI that can cause great harm. While much thought has been devoted to the dangers of AI, and centers like the Future of Life Institute in Cambridge, Ma., and the Future of Humanity Institute at Oxford University are focusing resources on how to support the creation of'safe' AI, few have attempted to intentionally create malevolent AI. Go with TechRepublic's Steve Ranger on an inside look at the gold-plated gadget market that's received a big boost from Apple.

In a rare move, Apple has invested 1 billion in popular Chinese ride sharing service Didi Chuxing. The investment gives Apple an opportunity to learn more about its second-largest market, CEO Tim Cook said. "We are making the investment for a number of strategic reasons, including a chance to learn more about certain segments of the China market," Cook said in an interview with Reuters. "Of course, we believe it will deliver a strong return for our invested capital over time as well." The move also comes after billionaire investor Carl Icahn sold his position in Apple, largely due to the company's lagging performance in the region.