In blue we show the recurrent connections – the output'm' at time (t – 1) is fed back to the memory at time't' via the three gates; the cell value is fed back via the forget gate; the predicted word at time (t – 1) is fed back in addition to the memory output'm' at time't' into the Softmax for tag prediction. In spite of this fact, when we test images with multiple clothing type, our trained model generates tags for these unseen test images quite accurately ( 80% accurate). Prediction accuracy of our model improves quickly with increasing number of training iterations and stabilizes after about 20,000 iterations. Moreover, combining DCNN-RNN model helps us extend the trained model to solve completely different problem like fashion image tag generation.

The tech giants have joined forces to create a new AI partnership to study and formulate best practices on AI technologies, and to serve as an open platform for discussion and engagement about AI and its influences on people and society. Google's involvement in the project is mainly through its research subsidiary DeepMind, which made news recently when its AI machine beat a world-class human player in the Asian board game, 'Go'. The heavyweights lobby says, the goal is to "conduct research, recommend best practices, and publish research under an open license in areas such as ethics, fairness and inclusivity; transparency, privacy, and interoperability; collaboration between people and AI systems; and the trustworthiness, reliability and robustness of the technology".

The industry is falling over itself to make products'intelligent' but what does that really mean to a user? As a Product Manager in this space, I've been thinking about intelligence and what it really means to users. There are many definitions of intelligence but they tend to be technical definitions of AI rather than intelligence seen through the eyes of a user. As we progress through the stages, what users once considered as intelligent, can become ordinary over time. For example, improving search so that it was accurate and fast could be regarded as highly intelligent at the time but now it's the minimum we expect.

Now I suppose it is possible that once an agent reaches a sufficient level of intellectual ability it derives some universal morality from the ether and there really is nothing to worry about, but I hope you agree that this is, at the very least, not a conservative assumption. For the purposes of this article I will take the orthogonality thesis as a given. So a smarter than human artificial intelligence can have any goal.

Everyone is talking about driverless cars ... After reading this book, you will be knowledgeable enough to make your own informed opinion. Driverless vehicles are poised to usher in a massive disruption of our transportation system, our urban landscapes, our economy -- and quite possibly the very fabric of society. Anyone who wants to understand what's coming must read this fascinating book. Driverless is a great read for anybody interested in technological, societal, and ethical implications of self-driving cars. The book reaches across fields and issues thoughtfully, and presents a comprehensive view of the state of the art.

In 2014, Tesla and SpaceX founder Elon Musk said in an interview that he believed that AI posed the biggest threat to human existence. That didn't stop him from co-chairing a billion-dollar AI research nonprofit, but it did make people think about whether artificial intelligence could get out of hand. Now, five tech giants including Google and its DeepMind subsidiary, Facebook, Microsoft, Amazon and IBM have come together to form Partnership on AI, a coalition dedicated to highlighting the best practices and ethical research in the field of artificial intelligence. Momentum by TNW is our New York technology event for anyone interested in helping their company grow. The group notes that it "foresees great societal benefits and opportunities ahead, but we also understand that as with every new technology there will be concerns and confusion associated with new applications and competencies, and we look forward to working together on these important issues. We intend to come together to address these important issues, including ethics, safety, transparency, privacy, biases, and fairness."

Virtual reality is on the cusp of becoming mainstream, but one startup in Japan is betting the technology won't really succeed unless it cracks a critical piece of the puzzle: human eyeballs. Fove Inc. is introducing the world's first commercially available VR goggles equipped with tiny infrared cameras to follow eye movements. By tracking human irises, the gadget aims to reduce motion sickness, improve graphics performance and enhance social experiences by making virtual eye-contact possible, says Yuka Kojima, Fove's founder and chief executive officer. "We want to be the company that figures out VR's unsolved problems," Kojima said. "The immediate goal for now is to get as many headsets into the hands of developers as possible."

As it wraps up its annual user conference here this week, San Francisco-based Splunk has one main message for the market. It's going big -- or, given that this is football season -- long with machine learning. In other words, it has expanded in a significant way the early version of machine learning in its platform to deliver new services and capabilities. It has added machine learning to the core of its platform with a machine learning toolkit that can be installed as a free app on top of the Splunk Enterprise platform, Manish Sainani, principal product manager of Machine Learning at Splunk told CMSWire. This toolkit provides 300 algorithms for machine learning, 27 of which are pre-packaged out of the box, spanning all of the major categories, he said.

Five tech giants announced on Wednesday that they are launching a nonprofit to "advance public understanding" of artificial intelligence and to formulate "best practices on the challenges and opportunities within the field." The Partnership on Artificial Intelligence to Benefit People and Society is being formed byAmazon, Facebook, Google, IBM, and Microsoft, each of which will have a representative on the group's 10-member board. The partnership will conduct research and recommend best practices relating to "ethics, fairness and inclusivity; transparency, privacy, and interoperability; collaboration between people and AI systems; and the trustworthiness, reliability and robustness of the technology," according to the announcement. "It does not intend to lobby government or other policymaking bodies." "We're in a golden age of machine learning and AI," said Ralf Herbrich, the director of machine learning at Amazon, in a prepared statement.

Facebook (FB, Tech30), Amazon (AMZN, Tech30), Google (GOOGL, Tech30), Microsoft (MSFT, Tech30) and IBM (IBM, Tech30) have formed a new nonprofit to establish best practices for the development of AI technology in partnership with academics and ethics experts. The group, unveiled on Wednesday, goes by the heartwarming name Partnership on Artificial Intelligence to Benefit People and Society. "This partnership will ensure we're including the best and the brightest in this space in the conversation to improve customer trust and benefit society," Ralf Herbrich, director of machine learning science and core machine learning at Amazon, said in a statement. Each of the corporate members is expected to make financial and research contributions to the group. The nonprofit is also looking to engage with the scientific community and bring academics onto its board.