How to get people interested in art? How to expose permanent-collection works that sit in storage? These are questions art museums constantly ponder. Recently, Tate Britain asked another one: How can artificial intelligence help? It put the question to anyone who wanted to compete for the 2016 IK Prize, which promotes the use of digital technology in the exploration of art at Tate Britain or on the Tate website.

Machine learning as a service market grow at a CAGR of 43.7% to reach USD 3755.0 million by 2021

Fast pace of today's tech evolution is giving rise to new business models and disrupting existing businesses. Your organization is competing with many others that you know of and several more that might not be on your radar yet. We keep an eye out for the latest opportunities in emerging tech and help you leverage these to leapfrog your competitors. Flarrio is a global leader in the field of emerging technologies. We help businesses become future-ready with product management, new solution building, learning, and transformation programs - powered by insights from 600 global experts and 300 emerging tech products.

A Deutsche Telekom official says artificial intelligence (AI) will be needed to break smart city data out of its silos. As reported by Mobile World Live, thoughts about smart city evolution appeared on the blog of Claudia Nemat, the Deutsche Telekom (DT) board member who oversees Technology & Innovation Europe. In her piece, Nemat described current smart city practices as trapping data from sensors in an isolated "landlocked lake." But as sensors proliferate at blinding speed in global smart cities, the rivers of data being produced will turn into oceans. This will be complicated by the multiple digital platforms running simultaneously in each city.

But Facebook has managed to pack AI into its app, which allows people to add filters to their videos in real-time, meaning that computing tasks that once required large data centers can now be done on the mobile device. "This is one application of AI on the device, it's one of the first. But the real breakthrough here is being able to train and build models on a big server…and deploy them directly to your pocket so you can run them in real time wherever you are. That is the exciting future of AI," Schroepfer said during a keynote speech. This so-called "deep learning" system is called Caffe2Go, and it is what makes stylized videos in the app possible.

Machine learning as a service market grow at a CAGR of 43.7% to reach USD 3755.0 million by 2021 Is Elon Musk Right And Will AI Replace Most Human Jobs? Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.

Imagine one day walking into a gorgeous structure--like LA's famous Walt Disney Concert Hall--only to discover it was designed by a computer system and constructed by automated robotic arms. Ai Build, a London-based startup, aims to pave the way to 3D printing on large scales. The company is equipping industrial-grade Kuka robotic arms with artificial intelligence and "3D printing guns" to 3D print large structures that focus on maximizing efficiency with labor and materials. Founder and CEO Daghan Cam dreamed up the technology while considering traditional commercial construction and wondering what a more efficient and automated process might look like. In October, the company partnered with engineering consulting firm Arup Engineers to debut the 3D printed "Daedalus Pavilion" at the GPU Technology Conference in Amsterdam.

In machine learning, you may often wish to build predictors that allows to classify things into categories based on some set of associated values. For example, it is possible to provide a diagnosis to a patient based on data from previous patients. Many algorithms have been developed for automated classification, and common ones include random forests, support vector machines, Naïve Bayes classifiers, and many types of neural networks. To get a feel for how classification works, we take a simple example of a classification algorithm – k-Nearest Neighbours (kNN) – and build it from scratch in Python 2. You can use a mostly imperative style of coding, rather than a declarative/functional one with lambda functions and list comprehensions to keep things simple if you are starting with Python. Here, we will provide an introduction to the latter approach.

New drugs typically take 12-14 years to make it to market, with a 2014 report finding that the average cost of getting a new drug to market had ballooned to a whopping $2.6 billion. It's a topic I've covered before, with a study published earlier this year highlighting how automation could be used to reduce the cost of drug discovery by approximately 70%. It's an approach that a number of companies are taking to market. For instance, London-based start-up Benevolent.AI utilizes complex AI to look for patterns in the scientific literature. They have already managed to identify two potential drug targets for Alzheimer's that has already attracted the attention of pharmaceutical companies.

In 1997, a computer program codenamed Deep Blue, defeated Russian chess grandmaster, Garry Kasparov. In 2006, Deep Fritz dethroned the then World Champion Chess player, Vladamir Kramnik. In 2016, Google developed an artificially intelligent computing system named AlphaGo. It added another name on the "list of humans" defeated by a machine, the highly ranked South Korean Go player, Lee Sedol. Prior to the dethroning of Kasparov, Kramnik and Sedol, it was thought that artificial intelligence still had ways to go before it could outwit and outmatch gifted human players.