Facebook has begun allowing businesses to send users adverts on Messenger, but only if those users have previously made contact with the brand. Part of Facebook's iteration of its Messenger chat service as a platform, announced at Web Summit in Lisbon, the change will mean that if a user ever contacts a brand that will open the door to that brand then sending them adverts through the instant messaging app. "Sponsored messages" as Facebook calls them provides another revenue opportunity for Facebook, targeting users in a place where they are less likely to automatically screen out adverts. David Marcus, Facebook's vice president of messaging, said: "Of course, people using Messenger shouldn't worry about getting spammed, because the starting principles still remain: businesses can't send a sponsored message to threads that weren't previously opened by their customers or prospects, and users have full control to block messages or people/businesses they no longer want to hear from." However, users wanting to avoid ads will have to be careful which brands, chatbots and other interfaces within Messenger they use. If a user messages a chatbot it gives that brand carte blanche to then send the user adverts.

The meetup will be hosted by AAA-data / Comité des Constructeurs Français d'Automobiles and the networking event is sponsored by Zen.ly . A big thank you to them. The program for this third regular meetup of the season (and the fifth total for season 4) is a little extraordinary this time and will feature the following: Dominique Gillot, Sénatrice, ancienne ministre et Rapporteure avec le député Claude de Ganay d'un rapport sur l'Intelligence Artificielle pour le Parlement. Julien Simon (Amazon), Machine Learning & Deep Learning with Amazon Web Services Gautier Marti (Hellebore Capital), A closer look at correlations You may have already read many times that the job of a Data Scientist is to skim through a huge amount of data searching for correlations between some variables of interest. And also, that one of his worst enemies (besides correlation doesn't imply causation) is spurious correlation.

Chainer is an open source framework designed for efficient research into and development of deep learning algorithms. In this post, we briefly introduce Chainer with a few examples and compare with other frameworks such as Caffe, Theano, Torch, and Tensorflow. Most existing frameworks construct a computational graph in advance of training. This approach is fairly straightforward, especially for implementing fixed and layer-wise neural networks like convolutional neural networks. However, state-of-the-art performance and new applications are now coming from more complex networks, such as recurrent or stochastic neural networks. Though existing frameworks can be used for these kinds of complex networks, it sometimes requires (dirty) hacks that can reduce development efficiency and maintainability of the code.

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You might expect the operating theatre to be one of the last places you'd find robotics in action but, increasingly, you'd be wrong. The OT is typically the most labour-intensive and expensive part of a hospital -- which, in this age of spiraling health costs, makes it a priority for any cost-savings that can be achieved through systemisation and standardisation. Robotic surgery, or robot-assisted surgery, has the advantage that it allows doctors to perform many types of complex procedures with more precision, flexibility and control than they could with conventional techniques. Given the speed at which robotics is advancing, how long will it be before robots start making all the decisions on surgery without the need for human control or intervention? OK, you say, that's fine where standard and predictable procedures are required.

Lancaster University is developing artificial intelligence (AI) software for servers that could potentially drive down the amount of energy consumed by datacentres. A collection of our most popular articles on datacentre management, including: Cloud vs. Colocation: Why both make sense for the enterprise right now; AWS at 10: How the cloud giant shook up enterprise IT and Life on the edge: The benefits of using micro datacenters This email address is already registered. By submitting my Email address I confirm that I have read and accepted the Terms of Use and Declaration of Consent. By submitting your personal information, you agree that TechTarget and its partners may contact you regarding relevant content, products and special offers. You also agree that your personal information may be transferred and processed in the United States, and that you have read and agree to the Terms of Use and the Privacy Policy.

Lip reading, an essential tool that helps the hearing-impaired to better understand the world, is now conducted by artificial intelligence with a better accuracy than done by humans, University of Oxford reveals. In an article currently published by Quartz we learn that a new paper issued by the University of Oxford with funding from Alphabet's Deepmind, reveals that they have developed an artificial intelligence system called LipNet that can read lips with an accuracy of 93.4%. University of Oxford has previously released a system that operated word-by-word with an accuracy of 79.9%, but their new system has now developed a new and different way of approaching the problem. "Instead of teaching the AI each mouth movement using a system of visual phonemes, they built it to process whole at a time. That allowed the AI to teach itself what letter corresponds to each slight mouth movement", Quartz writes. The new system was exposed to 29 000 3-second-videos videos labelled with the correct text to train the system, and in comparison with human lip-readers that had an average error rate of 47.7%, the AI's error rate was only 6.6%.

Why do Digital marketers need Artificial Intelligence? What does Artificial Intelligence in Digital Marketing look like today? When it comes to humans and machines understanding each other, humans are in luck because they already know how machines talk. Machines however, have a lot of learning to do. This is where semantic analysis comes into play.

We recently published a news strory about an artificial intelligence system that predicted that Donald Trump will win the US presidential elections. We also went ahead to inform you that the A.I christened MoglA had predicted the past three American elections correctly. Well, it looks like MoglA has added another feather to it's cap as Donald Trump has been declared the president elect of the United states of America. To read about Trump's win, click HERE The AI system christened MoglA was developed by an Indian startup founded by Sanjiv Rai. The prediction was a bold one, putting into consideration the fact that most polls before the elections have put Hillary ahead of Trump by a good margin.

Baidu has launched Melody, an AI-powered conversational bot designed to provide relevant information to doctors to assist with recommendations and treatment options. Melody incorporates advanced deep learning and natural language processing (NLP) technologies developed by Baidu. Melody integrates with Baidu Doctor, an app that Baidu launched in China in 2015. Andrew Ng, chief scientist, Baidu, said: "Melody is designed to help both doctors and patients. By focusing on the medical-assistant vertical, we've built a conversational bot that can give highly-customized and situation-appropriate responses to a patient's query."