The major theme of the report is the ever-closing gap between virtual and physical reality. Gartner said technology will become more human-centric to the point it will "introduce transparency between people, businesses and things", as technology becomes adaptive, contextual and fluid in the workplace and home. It listed the connected home, gesture control, 4D printing, brain computer interfaces (BCI), and human augmentation among other technologies that will blur the lines between physical and virtual worlds. Augmented reality and virtual reality, which remain a part of this group, are in Gartner's'trough of disillusionment' and the'slope of enlightenment' – the twin phases after the'peak hype' has passed. Virtual reality remains a niche sector, despite Nokia expanding distribution and slashing prices for its professional virtual reality kit, and Intel proclaiming a new era of'merged reality'.

I seem to recall an academic paper from some years ago which used machine learning (possibly genetic or evolutionary programming) to predict whether a Turing Machine would halt. By predict, I mean the standard notion in ML: minimize the error on some validation set. For simplicity, let's assume that the ML is a binary classifier, (although AFAIK the actual paper may have framed it as a regression problem). The notion is then not'solving' the Halting Problem (which we know is impossible), but rather using ML to agree with an Oracle that knows the answer on the training (and validation) set. However, I haven't been able to find anything so far.

After robot cars and robot rescue workers, US research agency Darpa is turning its attention to robot hackers. Best known for its part in bringing the internet into being, the Defence Advanced Research Projects Agency has more recently brought engineers together to tackle what it considers to be "grand challenges". These competitions try to accelerate research into issues it believes deserve greater attention - they gave rise to serious work on autonomous vehicles and saw the first stumbling steps towards robots that could help in disaster zones. Next is a Cyber Grand Challenge that aims to develop software smart enough to spot and seal vulnerabilities in other programs before malicious hackers even know they exist. "Currently, the process of creating a fix for a vulnerability is all people, and it's a process that's reactive and slow," said Mike Walker, head of the Cyber Grand Challenge at Darpa. This counted as a grand challenge, he said, because of the sheer complexity of modern software and the fundamental difficulty one computer had in understanding what another was doing - a problem first explored by computer pioneer Alan Turing.

This meetup is a gathering place for professionals who use or (or want to learn about using) machine learning to solve messy optimization problems where "hard coded" solutions like deterministic grammars and rules-based systems just don't cut it. If you have a working expertise in machine learning, suspect that you may have a problem where you need to develop a program that "learns" from the data to provide an adequate solution, or you just want to learn more about machine learning and how it might benefit you, this is the place to be! Regular meetup topics will run the gauntlet of supervised, unsupervised, and reinforcement learning approaches and range from natural language processing to computer vision and everything in between.

Last month, the bot's makers announced plans to turn it into a fully fledged personal finance bot that can answer questions in natural language, like: "How much did I spend dining out last month?" Over time, the bot claims it can automate savings and help people accumulate wealth. Made by 19-year-old college student Joshua Browder, DoNotPay helps people challenge parking tickets in New York, London, and soon Seattle. Browder said in June that DoNotPay has successfully challenged 160,000 tickets, saving New Yorkers and Londoners millions of pounds and dollars.

We've all got bills to pay, fiscal responsibilities to meet, retirements to save for -- and we need help. As tens of thousands of chatbots proliferate across Slack, Facebook, and other platforms, you hear naysayers claim that bots might be useful someday but that today they're little more than a gimmick. It's hard to feel that way after you learn about a handful of chatbots that have saved people more than 10 million. Next time you hear someone make that argument, point them to this list, because perhaps nothing is more useful than putting (or keeping) money in your pocket. After its first month, about 100,000 people have interacted with PennyCat, according to maker Leo Kangin.

This year, chatbots and virtual assistants have made their entrance into our lives. And many experts are convinced that they're here to stay. These technologies take ecommerce to a new, much more conversational level that is "conversational commerce". It's a term coined by Uber's Chris Messina (by the way, he's the inventor of the Twitter hashtag) and describes the step towards more personalized interactions between people and brands utilizing chat, messaging, or other natural language interfaces (i.e. Chatbots and Virtual Assistants are artificial intelligence systems that can communicate with users on a more personal level.

But efforts to use artificial intelligence, machine learning and big data in healthcare contexts have not been uncontroversial. On the one hand there is wild enthusiasm – lives saved by data, new medical breakthroughs, and a world of personalised medicine tailored to meet our needs by deep learning algorithms fed by smartphones and FitBit wearables. Too often the debate dissolves into anecdote rather than science, or focuses on the breakthrough rather than the hard slog that led to it. Of course the reality will be somewhere in the middle.

Watch Sunspring, the Sci-Fi Film Written with Artificial Intelligence, Starring Thomas Middleditch...

Intel has set its targets on the world of artificial intelligence, as it continues to bolster its armoury to capitalize on the potentially lucrative IoT segment. Speaking at Intel Developer Forum, Diane Bryant GM of Intel's Data Center Group outlined the ambitions of the business, with the finish line pointed towards artificial intelligence. There are still hurdles to be overcome over the next few years, as technology needs to catch up with the potential, though Bryant highlighted the 400 million acquisition of AI start-up Nervana shows the ambitions of the business. Only last week Intel announced it was acquiring deep learning specialists Nervana, though the move towards IoT, of which AI could be seen as a crucial aspect, has not been a secret. Back in April, CEO Brian Krzanich made it very apparent IoT was one of the more prominent pillars of the company's strategy, and this was echoed in Bryant's talk.