Facebook, Twitter and Google have been given a month to make changes to their user agreements in the European Union or face;enforcement action.;

Scientists from the Oxford University along with Google's DeepMind have developed an artificial intelligence system that can lip-read better than humans. The system was trained by thousands of hours of BBC news programs, the media outlet said Friday. The system, called "Watch, Attend and Spell," can correctly lip-read 50 percent of silent speech correctly, while professional…

If you are looking for a monitor for your MacBook, here are some of the best non-Apple Monitors you can get in the market.

An update to Keras provides a long-term stable API, native TensorFlow version, SkyMind Deep Learning 4 J implementation, and several important updates. I found this great deep dive analysis of text analysis and understanding. The article Multilingual Parsing From Raw Text to Universal Dependencies has a lot of projects. I will be keeping an eye on this one to see some practical business uses. This is a great place to stop learning how to do image classification without a lot of data using Keras.

Bill Gates, Stephen Hawking and Elon Musk first warned us about Artificial Intelligence (AI). Elon Musk then turned around and with other technologists put $1B into starting a nonprofit research effort - OpenAI just to "keep an eye on it"! Facebook, Google, Amazon, Nvidia, Shopify and others are charging full steam at AI and even open sourcing it! So what is all the AI ruckus about? AI has been subject matter for science fiction for a long time now. Every SciFi show you can think of has a intelligent computer or robot as a sidekick or with some prominent role.

In my last retail review, I explored how my learnings at NRF 2017 changed my view ofthe so-called omni-channel (Omni-channel may be science fiction, but a single source of truth matters). That leaves open the impact of predictive, "AI", and personalization tech on retail. CEO and Founder Alan O'Herlihy gave me a fast-paced rundown of how his company has become entrenched in five of the ten largest global retailers. How did they pull it off? Get ready for this one: instead of pursing the singularity, they focused their deep learning tech on a real world pain point: lost sales at the point of sale.

Through extensive systematic experiments, we show how these traditional approaches fail to explain why large neural networks generalize well in practice. Specifically, our experiments establish that state-of-the-art convolutional networks for image classification trained with stochastic gradient methods easily fit a random labeling of the training data. This phenomenon is qualitatively unaffected by explicit regularization, and occurs even if we replace the true images by completely unstructured random noise. We corroborate these experimental findings with a theoretical construction showing that simple depth two neural networks already have perfect finite sample expressivity as soon as the number of parameters exceeds the number of data points as it usually does in practice.

Scientists from the Oxford University along with Google's DeepMind have developed an artificial intelligence system that can lip-read better than humans. The system was trained by thousands of hours of BBC news programs, the media outlet said Friday. The system, called "Watch, Attend and Spell," can correctly lip-read 50 percent of silent speech correctly, while professional lip-readers only got 12 percent right, researchers found. Read: Google AI Firm DeepMind Develops'Streams' App to Help UK Doctors With Patients Some words that rhyme, such as like mat, bat and mat, have similar mouth shapes. However, it's context is what helps lip-reading, Joon Son Chung from the university's Department of Engineering said. The system learns "things that come together, in this case the mouth shapes and the characters and what the likely upcoming characters are," explained Joon.

A deal between Google's artificial intelligence firm DeepMind and the UK's NHS had serious "inadequacies", an academic paper has suggested. More than a million patient records were shared with DeepMind to build an app to alert doctors about patients at risk of acute kidney injury (AKI). The authors said that it was "inexcusable" patients were not told how their data would be used. Google's DeepMind said that the report contained "major errors". It told the BBC that it was commissioning its own analysis and rebuttal, which the authors said they welcomed. When the deal between London's Royal Free Hospital and DeepMind became public in February 2016, some three months after the data started to be collected, it caused controversy over the amount of patient information being shared and the lack of public consultation.

A page from the notebook of British mathematician and pioneer in computer science Alan Turing, the World War II code-breaking genius, is displayed in front of his portrait during an auction preview in Hong Kong Thursday, March 19, 2015. This week's milestones in the history of technology include Alan Turing anticipating today's deep learning by intelligent machines and concerns about the impact of AI on jobs, Clifford Stoll anticipating Mark Zuckerberg, and establishing the FCC and NPR. Alan Turing gives a talk at the London Mathematical Society in which he declares that "what we want is a machine that can learn from experience." Anticipating today's enthusiasm about machine learning and deep learning, Alan Turing described how intelligent machines will work: Let us suppose we have set up a machine with certain initial instruction tables, so constructed that these tables might on occasion, if good reason arose, modify those tables. One can imagine that after the machine had been operating for some time, the instructions would have altered out of all recognition, but nevertheless still be such that one would have to admit that the machine was still doing very worthwhile calculations.