Interestingly, Nest (now a part of the same company) shied away from the idea of an Echo like device, citing privacy concerns about talking to Google, its search engine, algorithms and other internet magicks. Recode's sources suggest voice search and intelligent responses from your Google devices will be the centerpiece of Google's showcase, alongside virtual reality developments. Show us what you've got.

At the end of last month, Sundar Pichai wrote his first annual shareholder letter as CEO of Google. Eight months prior, Larry Page and Sergey Brin led a restructure of the company they founded, separating its core internet business from subsidiaries focusing on new areas of innovation, such as self-driving cars, drones, augmented reality, biotech and life sciences. Page and Brin now lead umbrella company Alphabet as CEO and president respectively, while Pichai heads up Google. It was the first time the annual shareholder letter had been written by anyone other than Page and Brin. Pichai kept it simple, outlining the key areas Google will focus on across its product lines – but he was bold enough to say they will all be driven by a long-term investment in machine learning and artificial intelligence.

Machine learning is the process of building analytical models to automatically discover previously unknown patterns from data that indicate associations, sequences, anomalies (outliers), classifications, and clusters and segments. These patterns reveal hidden rules as to why an event happened--for example, rules that predict likely customer churn. The widely used Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is used to develop predictive analytical models. CRISP-DM includes six phases: business understanding, data understanding, data preparation, model development using supervised and unsupervised learning, model evaluation and model deployment. The business understanding phase involves defining the business problem or use case, the business objectives and the business questions that need to be answered.

Unless you've been living under a rock for the last few years, you have probably heard of TV shows such as Breaking Bad, Mad Men, How I Met Your Mother or Game of Thrones. While I generally don't spend a whole lot of time watching TV, I have also undergone some pretty intense binge-watching sessions in the past (they generally coincided with exam periods, which was actually not a coincidence…). As I was watching the epic final season of Breaking Bad, it got me thinking on how TV series compare to one another, and how their ratings evolve over time. I therefore decided to look a bit further into user rating trends of popular TV series (and by popular I mean the ones I know). For this, I simply had to define a quick scraping function in R that retrieves the average IMDB user ratings assigned to each episode of a given series.

Artificial intelligence is already powering your Google searches, your Netflix recommendations, and your smartphone's virtual assistant. It is playing humans at complex, intuitive games like Go, and it is beating them. Now, researchers say, they want AI to power your doctor's diagnoses, your drug prescriptions, and your smartphone's virtual psychologist. They want AI to perform tasks that radiologists do, and at least match them. Machine learning has made tremendous strides in the last decade, becoming one of the fastest-growing, most-hyped areas of computer science.

AUTONOMOUS cars are just around the corner. Cities across the world are rolling out pilots of driverless vehicles, and soon motorists in Germany will be able to relax on the autobahn as their cars drive them from Munich to Berlin (see "London is set for driverless car roll-out – so what comes next?"). In other words, we are on the brink of a transport revolution as potentially radical as the one that began in 1908 with the Model T Ford. By 1931 the automobile's transformative power was so clear that Aldous Huxley imagined the people of his Brave New World worshipping Henry Ford as the creator of their dystopian society. Huxley was on to something. The Ford revolution changed Western society.

BigML Spring 2016 release is here! GMT 02:00) for a FREE live webinar to learn about the latest and greatest version of BigML. We'll be focusing exclusively on WhizzML, a new domain-specific language that lets you automate Machine Learning workflows, implement high-level Machine Learning algorithms, and share them with others. WhizzML stands to make a big difference not only in how developers conceive of and implement smart applications, but also how analysts and scientists reduce the burden of repetitive analyses.

Introduction to deep learning based on Google's TensorFlow framework. These tutorials are direct ports of Newmu's Theano Tutorials.

DeepMind, Google's AI lab in London, is well known for creating an algorithm that beat the best human in the world at Chinese board game Go. It's also been in the news this month for the controversial work it's doing with the NHS in healthcare. But DeepMind is understood to have a collection of other projects on the go that no one knows about. The research-intensive organisation, which employs around 250 people in a discreet building in King's Cross, writes on its website that it is building self-learning algorithms that can complete a wide variety of tasks straight out of the box. The company, which was backed by PayPal billionaire Elon Musk in its early days, also writes on its website that it wants to "solve intelligence" to "make the world a better place."

Computers do what we tell them to do. Any talk of computers doing things they weren't programmed to do is only a way of speaking. It's a convenient shorthand when used properly, misleading mysticism when used improperly. But of course the computer was programmed to print the number 168. It just wasn't directly programmed to do so.