Imagine wanting a cup of coffee and suddenly finding it before you, freshly prepared to your exacting standards. In the not-so-distant future, this will be reality for Muggles, too. In fact, thanks to a surge in consumer data, brands and marketers can already make better inferences about consumer wants and needs, but as AI and machine learning are more deftly integrated, insights will only get better, as will the ability to anticipate consumer needs – and to even make decisions on behalf of consumers without any input from them whatsoever. Like, say, ordering a cup of coffee. As it stands, digital enables brands to customize offers for specific users rather than provide generic solutions.

The best television characters have already been immortalized on screen, given reruns and our ability to stream our favorite episodes on demand. Now early research at University of Leeds is attempting to give these characters new life, by building digital recreations that can appear in new episodes or even take over for Siri on your smartphone. The Leeds team is building a nearly-automated pipeline for capturing the digital essence of a TV character. A series of algorithms mutes the laugh track on a TV show, tracks the faces of each character, and analyzes their voices and body language, as well as the way their mouths move as they speak. The machine learning tool also scours the show's script in order to learn dialogue and understand how each character strings together sentences. TV is a natural fit for this kind of research, because there's so much video from which to learn.

Applied machine learning is a tapestry of breakthroughs and mindset shifts. Understanding the role of randomness in machine learning algorithms is one of those breakthroughs. Once you get it, you will see things differently. You will also start to see the abuses everywhere. In this post, I want to gently open your eyes to the role of random numbers in machine learning.

Government-funded artificial intelligence programs could soon be organized under a new effort by the General Services Administration. GSA earlier this month created the Data Federation, a site that intends to coordinate the disparate existing data-related efforts at various agencies by sharing standards, case studies and reusable tech tools. On Monday, GSA plans to announce a new community of practice, or subsection dedicated to artificial intelligence, according to Technology Transformation Service data portfolio lead Philip Ashlock. Ashlock was speaking at a Digital Government Institute conference on Thursday. The Data Federation is still in the very early stages, he said--long term, it's working with 18F and the Presidential Innovation Fellows program to develop a "maturity model" to understand how data projects tend to evolve.

CAMBRIDGE, UK: Professor Stephen Hawking on Wednesday opened a new artificial intelligence research centre at Britain's Cambridge University. Funded by a  10 million (11.2 million-euro, 12.3-million) grant from the Leverhulme Trust, the centre's express aim is to ensure AI is used to benefit humanity. Opening the new centre, Hawking said it was not possible to predict what might be achieved with AI. "Perhaps with the tools of this new technological revolution, we will be able to undo some of the damage done to the natural world by the last one - industrialisation. "And surely we will aim to finally eradicate disease and poverty. Every aspect of our lives will be transformed.

Artificial intelligence (AI) is in the early stages of the technology adoption life-cycle. Like a toddler learning to walk, there will be stumbles in the growth of AI. With any innovative technology, there exists the potential for both good and harm. For example, Microsoft's AI chatbot, Tay, was taken offline after only hours on Twitter after it produced racist and sexist comments. How could this have been prevented?

From driverless cars to online financial infrastructure payments, Artificial Intelligence obviously will be the heart of the next industrial revolution. The wave of globalisation and democracy cannot be overlooked regarding their contributions steering policy integration. Both concepts will play vital roles towards integrating the African continent under an umbrella perceived to end humanity (Artificial Intelligence). The rise of machines and robotics in high-income economies has been a contested discourse by philosophers, economists, tech geeks and policy makers. There is a rising belief it would steal jobs and render humanity useless and even economists seem not to be certain about the relevance of labour in this period. Immediately Japan was announced as the host of 2020 Olympics, what would strike one's mind is the presence of robotics during the famous sporting event.

Since the final episode of hit sitcom Friends first aired in 2004, many fans have clung to the hope of a reunion. Earlier this year, the show's co-creator Marta Kauffman quashed that idea emphatically: "There will never be a Friends reunion movie," she told E! News. Could she be any clearer? But for those still mourning the gang, there is some sort of hope. A team of researchers at the University of Leeds seeks to immortalize popular characters as digital avatars that you might eventually chat with in the way you talk to Siri, Alexa or a similar virtual assistant. As spotted by Prosthetic Knowledge, the team is building a series of algorithms that can recognize and track individual characters and capture their body language, facial expressions and voice.

The IoT is a 410 billion opportunity just waiting for the healthcare sector and other industries to leverage their big data. It is likely that the Internet of Things, along with blockchain technology and artificial intelligence, will start to come into their own as the decade draws to a close, opening up the potential for drastic improvements in care quality, the patient experience, and providers' ability to make informed, actionable decisions.

The study and application of machine learning and artificial intelligence have been around for decades, yet recent hype in the advertising industry presents this as an entirely new and disruptive trend. Headlines used to be all about big data. Now they are about machine learning. Is there a relationship between these terms? Machine learning and big data are symbiotic.