Artificial intelligence and machine learning are two phrases that are thrown around a lot in the tech world these days. It has gotten the point where every company has to say they're an AI company, even if they really don't have AI capabilities, just to be taken seriously. The problem is that the best data scientists all want to work for the same few companies: Google, Facebook or Apple. So what are the smaller companies to do? That's the problem that H2O.ai is solving.

Imagine the Internet without Google? Trying to find anything would be unbelieva-bly painful – not to mention time-consuming. Well, by 2020, Cisco forecasts that there will be 65 trillion im-ages and 6 trillion videos uploaded to the web. This will result in over 80% of all in-ternet traffic being image or video-based in two years. Search engines like Google rely on human-tagged meta-data to carry out their searches. These tags are written and added when text-based content is created.

Computers might soon translate between many more languages. Automatic language translation has come a long way, thanks to neural networks--computer algorithms that take inspiration from the human brain. But training such networks requires an enormous amount of data: millions of sentence-by-sentence translations to demonstrate how a human would do it. Now, two new papers show that neural networks can learn to translate with no parallel texts--a surprising advance that could make documents in many languages more accessible. "Imagine that you give one person lots of Chinese books and lots of Arabic books--none of them overlapping--and the person has to learn to translate Chinese to Arabic. That seems impossible, right?" says the first author of one study, Mikel Artetxe, a computer scientist at the University of the Basque Country (UPV) in San Sebastiàn, Spain.

Speaking at the launch of the IT security company's threats predictions report, launched at its MPower conference held in Amsterdam, McAfee chief scientist Raj Samani said in an interview that criminals will increasingly use machine learning to create attacks, experiment with combinations of machine learning and artificial intelligence (AI), and expand their efforts to discover and disrupt the machine learning models used by defender.

A Scottish university reached the final three of a prestigious international competition dedicated to advancing conversational artificial intelligence (AI). A team of Phd students from Heriot-Watt saw more than 100 entries from 22 countries including the likes of Harvard and Princeton to become the only UK institution to be placed in the Alexa Prize. A nine-strong team, named What's Up Bot, won plaudists from judges for their artificial intelligence software named Alana, which can understand and respond to human conversation. The annual competition is organised by online retail giant Amazon and is named after the Alexa voice command system that powers Amazon Echo. The team of PhD students from Heriot-Watt's school of mathematical and computer sciences finished behind fellow finalists, the Czech Technical University and eventual winners, the University of Washington, at a ceremony held in Las Vegas on Tuesday, 28 November.

Just as humanity is starting to deal with business processes that should never have been digitized we might also consider the huge waste in making Smart Cities when we no longer need cities. Watching humanity evolve in retrospect it is easy to spot the errors and poor judgement, but humanity is on the cusp of a revolution so profound it calls into question the structure of our societies. Think for a moment, why do we need cities? They create centralization of people and resources however they also drive costs as often space is insufficient for demand. There is a huge dependency on the need for workspace, shops and local living accommodation. In a Smart Economy with people engaged in Smart Living people rely on digital communications not face to face engagements.

A woman who lost her leg in a speedboat accident that killed her husband and daughter has had prosthetic limbs worth about £30,000 stolen. Victoria Milligan, 45, lost her left leg below the knee in the accident in 2013. Thieves on mopeds stole a suitcase containing three specially-cast limbs from Ms Milligan's car. "I was left on the floor devastated and crying my eyes out when I found out," she told the BBC. "After what I've been through nothing surprises me anymore, but I couldn't believe it happened," she told BBC Radio London's Vanessa Feltz.

Last month, Google-owned DeepMind introduced AlphaGo Zero, the latest evolution of AlphaGo, the first computer programme to defeat a world champion at the ancient Chinese game of Go. Speaking at Web Summit earlier this month, Kevin Bandy, chief digital officer at Cisco, told the audience that "there are more moves in this one game than there are atoms in the universe". A piece of software mastered it in 72 hours, with no human help. This is a narrow application of artificial intelligence (AI), whereby it's focused on perfecting a specific task. It's extraordinary, but things get interesting when we take the debate further.

Advances in cloud computing, hardware, open-source software and algorithms have made it possible to analyse data in ways that simply would not have been practical a few years ago. Much of this success comes from machine learning - a set of techniques that allow us to make sense of large quantities of data and make predictions about what will happen next. Breakthroughs in machine learning are powering advances in almost every domain, from personalised product recommendations and autonomous vehicles through to drug discovery in healthcare and fraud detection in financial services. Traditional approaches to solving problems use hardcoded rules, which describe the solution step-by-step. In contrast, machine learning systems are set a task, and given a large amount of data to use as examples of how the task can be achieved.

This report sets out a series of strategic recommendations to the government, based on core pillars including data supply and exchange, skills and education and developing an artificial intelligence infrastructure in the UK, with a view to growing the country's AI sector, something which was also augmented by the recent Budget and government's Industrial Strategy White Paper this week. The professional panel included speakers such as Westminster Senior Lecturer and journalist Dr Mercedes Bunz, Westminster Business School Senior Lecturer Dr Steven Cranfield, and well known journalist and technology author Joanna Goodman, a Visiting Fellow at Westminster Law School's Centre on the Legal Profession. Speakers dissected the report and its implications for the future and were then questioned by the audience on the matter for nearly one and a half hours. Convener and Westminster Senior Lecturer in Law, as well as artificial intelligence, robotics and the law researcher, Dr Paresh Kathrani, who chaired the event, said: "2017 was undoubtedly an important year for artificial intelligence in the United Kingdom, not least with the House of Lords Select Committee on Artificial Intelligence's work on AI, this report and the recent Industrial Strategy White Paper. The University of Westminster and Westminster Law School will continue putting on LawTech and AI events in 2018 looking at these vital developments."