We present MILABOT: a deep reinforcement learning chatbot developed by the Montreal Institute for Learning Algorithms (MILA) for the Amazon Alexa Prize competition. MILABOT is capable of conversing with humans on popular small talk topics through both speech and text. The system consists of an ensemble of natural language generation and retrieval models, including template-based models, bag-of-words models, sequence-to-sequence neural network and latent variable neural network models. By applying reinforcement learning to crowdsourced data and real-world user interactions, the system has been trained to select an appropriate response from the models in its ensemble. The system has been evaluated through A/B testing with real-world users, where it performed significantly better than many competing systems. Due to its machine learning architecture, the system is likely to improve with additional data.

Can you tell us a little bit about your background and why you set up Artificial Lawyer? About 10 years ago, I started working at a large US consultancy as a strategy consultant to law firms. I then worked for a smaller boutique consultancy in the City of London. Two years ago, I set up my own business, Tromans Consulting, and I've been advising law firms on strategy and business decisions since. It became quite clear to me about 18 months ago that AI was going to have a profound impact as it evolves and spreads through the market, and I needed to take this into account when advising my clients.

The boss of a Manchester-based data analytics and artificial intelligence firm believes it has the potential to become a tech unicorn. Richard Potter is the chief executive of Peak, which secured £2.5 million in a Series A funding round led by London-based venture capital firm MMC Ventures in September. The firm has since unveiled a new website and brand identity which places a stronger focus on its AI and machine learning offering. In an interview with BusinessCloud, Potter said the company's ambition is to be a global technology champion in the AI and data analytics-as-a-service space. "Specifically for what we do, we think it's a nascent market with no other operators in this space because we're offering a service powered by our own technology platform," he said.

So, what's Yann LeCun talking about when he says "he's ready to throw Probability Theory under the bus"? This article attempts to explore this sentiment. The problem with Probability Theory has to do with its efficacy in making predictions. It's obvious that the distributions are different, unfortunately the statistical measures are identical! Said differently, if the basis of your predictions are expectations calculated from probability distributions, then you can very easily be fooled.

Most of us followed the exciting introduction of the new iPhone X, and there you also saw in the press conference, it's all about machine learning now for face recognition, applied also, machine learning in face recognition to unlock your phone. So, I think we all experience it already with our smartphones, and going forward, we'll see much more of it. Michael Chui: What we're starting to see is these AI technologies underpinning a lot of the things, all the online and mobile services that we're now increasingly taking advantage of. So, for instance, in e-commerce or media, when systems are providing you with suggestions for things you might be interested in, things you might be interested in reading or things you might be interested in buying--the next-product-to-buy use case, as we describe it--increasingly, those types of systems are powered not only by statistical methods, but by some of these AI technologies as well, hopefully bringing consumers closer to the things that they'd be most interested in. Simon London: I'm going to throw one more into the pot there. I'm lucky enough to live in the city of Mountain View in Silicon Valley. There are a surprising number of self-driving cars out on the road.

Renowned physicist Prof Stephen Hawking has said robots will eventually completely replace humanity. Prof Hawking said that he believes artificial intelligence (AI) will eventually reach a level where it will essentially be a "new form of life that will outperform humans" in an interview with WIRED magazine. He said: "I fear that AI may replace humans altogether. If people design computer viruses, someone will design AI that improves and replicates itself. This will be a new form of life that outperforms humans."

People might have had to wait a whole year for the iPhone X -- if Apple had stuck to its original plan. Executives of the Cupertino company revealed in an interview with Mashable Apple had initially intended to release the new iPhone X next year. Dan Riccio, Apple's SVP of hardware engineering, said the iPhone X with facial recognition technology and edge-to-edge OLED was supposed to release next year, but "with a lot of hard work, talent, grit, and determination" the company was able to offer the device to consumers this fall. It was also a risky move, since Apple was on a tight deadline. "We all knew where we were going," said Craig Federighi, Apple SVP of software engineering, "but there were a dozen things we knew we had to solve, and any one of them could have failed to come together."

The 49th Sveriges Riksbank prize in economic sciences – commonly referred to as the Nobel Prize for economics – has been awarded to Richard H Thaler for his contributions to behavioural economics. He was a key proponent of the idea that humans do not act entirely rationally and is primarily known for his often misunderstood concept of Nudge Theory. Attributed to Richard Thaler and Cass Sunstein in their book "Nudge: Improving Decisions about Health, Wealth, and Happiness," a "Nudge" can change the behaviour or decision that a human will make. The basis of Nudge theory is to apply an understanding of predicted behaviours to shape and influence that automated process. Leveraging a variety of different strategies, such as default settings, information as an incentive and right context, companies have proven the ability to change someone's behaviour through a successful Nudge.

We hear a lot these days about how AI is changing the marketing technology landscape, helping us sell products and services in the 21st century. But during my two-week journey through Israel's startup scene, it was a medtech company that struck a nerve with me -- a deep learning imaging analytics startup called Zebra Medical Vision. Using AI to recommend related products, build a million split tests, or determine the optimal time to push a discount voucher may be effective from a marketing standpoint, but these applications are hardly life-changing. And they wouldn't have helped save my dad's life. He passed away from lung cancer in February this year, and there is a good chance that an early and accurate diagnosis could have given him a better chance at beating "the big C." Zebra's technology is making it possible to catch misdiagnosed diseases, early-stage cancers, and other life-threatening ailments, and the company today announced a significant change in its business model that makes its AI-powered medical scan recognition for hospitals more affordable.

Yann LeCun is one of AI's most accomplished minds, so when he says that even recent advances in the field aren't taking us closer to super-intelligent machines, you need to pay attention. LeCun has been working in AI for decades, and is one of the co-creators of convolutional neural networks -- a type of program that's proved particularly adept at analyzing visual data, and powers everything from self-driving cars to facial recognition. Now, as head of Facebook's AI research facility FAIR, he helps AI make the journey from the lab to the real world. His team's software automatically captions photos for blind users and performs 4.5 billion AI-powered translations a day. "We had a bigger impact on products than Mark Zuckerberg expected," LeCun told The Verge over Skype recently.