Unfortunately, the new training platform created by OpenAI, a San Francisco-based nonprofit, is only available to AI -- so if you're human, you're out of luck. The new'college' is, in actuality, a training platform called Universe, whereby AI can interact with games, web browsers, protein folding software, and "transfer learning," which allows them to take what they've learned in one application and apply it to another. The AI engages via Virtual Network Computing, or VNC, which involves them sending simulated mouse and keyboard strokes. The Universe digital suite's home is in the OpenAI artificial intelligence learning center in San Francisco, where developers will begin "measuring and training AI agents." OpenAI is the non-profit brainchild of entrepreneurs Elon Musk and Peter Thiel, who have made no secret of their ambitions to greatly accelerate the research and development of transhumanist technologies.

This blog was originally published on our Text Analysis blog, the blog post set out to analyze and visualize 4 million tweets collected during Superbowl XLIX. Not surprisingly, Superbowl XLIX generated a huge amount of chatter on social networks with Twitter Estimating that over 28.4 million posts made with terms relating to the Superbowl. At AYLIEN, we collected just under 4 million Tweets from Hashtags, Handles and Keywords we were monitoring. To keep our sample clean, we removed any reTweets and spam from the Tweets collected and only worked with those Tweets that were written in English. We were left with about 3.5 million Tweets to play with.

British consumers are expected to spend £280 each on gifts over the weeks leading up to Christmas. More than half of these purchases will take place online. Almost a third of people will rely on online reviews to make their buying decisions, although recommendations from friends and family are still the main source of persuasion. Online shopping is estimated to rise by 24% by the end of this year. However, as consumers are looking for more sensory and immersive shopping experiences, the pressure is on for online retailers to find new ways to excite customers and keep them satisfied – and artificial intelligence (AI) is the new technology they will use.

Whether we like it or not, artificial intelligence is slowly but surely automating the processes we take for granted will be done by humans and making it more efficient, cost and time-wise. Big data, machine learning, natural language processing – all fancy terms used to explain the advent of machines learning to think and act and intuit like humans. Almost all tech industries will be, and are being, impacted by AI – and none more so than the B2C vertical of ecommerce. This infographic explains how ecommerce will be impacted by the growth of AI through chatbots, automation and other processes – all to enrich the customer buying experience.

Hospitals in Paris are trialling Big Data and machine learning systems designed to forecast admission rates – leading to more efficient deployment of resources and better patient outcomes. It's just one more way in which cutting-edge data science is being applied to real-world problems in healthcare, along with creating personalized medicines, fighting cancer and streamlining pharmaceutical trials. At four of the hospitals which make up the Assistance Publique-Hôpitaux de Paris (AP-HP), data from internal and external sources – including 10 years' worth of hospital admissions records has been crunched to come up with day and hour-level predictions of the number of patients expected through the doors. The core of the analytics work involves using time series analysis techniques – looking for ways in which patterns in the data can be used to predict the admission rates at different times. Machine learning is employed to determine which algorithms provide the best indicator of future trends, when they are fed data from the past.

Before assessing R and Python, I will start with Wolfram Mathematica. You can handle lists and matrices easily, you have all the best mathematical functions, backup of Wolfram Alpha and extremely sophisticated graphics visualizations, that allow you, for instance, to make and visualize an animated gradient descent, animate different weights for a given neural network, choose a specific Machine Learning algorithm and automatically classify your dataset in classes, plot stunning 3D visualizations, make animations and manipulate variables values dynamically at the same time you see the output of your calculation. It has 4.65 Gb size and comes with all libraries integrated. It's a great program when you know the formulae for Machine Learning algorithms, so you can build them from scratch, in a completely customized way. You can also do face recognition, geolocation of objects with 3D plots of map surface, handle cellular automata like any other and develop social networks models with artificial intelligence completely customized.

Understand convolutions (and why they are so much easier to grasp than they seem). Study Convolutional Neural Networks (what they are used for, why we use them, etc.). Review the building blocks of Convolutional Neural Networks, including: Discover common network architecture patterns you can use to design architectures of your own with minimal frustration and headaches. Utilize out-of-the-box CNNs for classification that are pre-trained and ready to be applied to your own images/image datasets (VGG16, VGG19, ResNet50, etc.).

Digital transformation reshapes every aspect of a business, and over recent years this has evolved to become a central component of modern business strategy. There are three fundamental effects of digital innovation: experience and engagement, business innovation, and the secondary effects that result from increased digital capabilities. Over the coming months, as digital technology continues to evolve, I believe organisations will be forced to explore the secondary effects of digital disruption and use technology to reimagine their business and embrace new ways of working in a more efficient, innovative and agile way. Existing digital technology platforms will evolve Digital platforms, interoperable sets of services brought together to create applications, provide the basic building blocks for a [digital] business. There will be growth in each of the five major digital technology platform types to enable the new capabilities and models that characterise today's digital business.

After spending a weekend in Tokyo learning about Artificial Intelligence, my entire perspective changed. I'm a bit embarrassed to admit that I was a sceptic when I walked into the plane for the overnight flight. I went determined to ask probing questions in support of my presupposition that machines can only do what man tells them and that they're void of emotion. Simply defined, AI, as it is commonly referred to, is machine intelligence. According to Russel and Novig, computer scientists known for their contributions to AI, "An ideal'intelligent' machine is a flexible rational agent that perceives its environment and takes actions that maximise its chance of success at some goal."

With the majority of consumers spending significant time on various messaging platforms, brands are turning to these messaging platforms to better interact with consumers. The increase in private messaging between customers and brands is driving companies to turn to chatbots for improved social customer care. The Watson Conversation Service offers a simple, scalable and science-driven solution for developers to build powerful chat bots to address the needs of various brands and companies. As developers leverage Watson Conversation to build cognitive solutions for various, one recurring question is: "How much time should I plan to train my solution" or "How do I know when my model is trained sufficiently well"? While the answer depends greatly on the problem being solved and the data powering the solution, in this blog we offer a common methodology for training the machine learning (ML) models powering your chat bot solution.