Artificial intelligence is beginning to disrupt entire industries from finance to medicine. Yet the most revolutionary application has yet to arrive--and it's an existential one. As thinking machines become more integrated into our lives, we must expect a transformation in how we define what it means to be conscious; what it means to live and to die; and ultimately, what it means to love a non-human being. These questions are artfully explored in the plot of the 2013 sci-fi film, Her, which tells the story of a man who falls deeply in love with an intelligent operating system. This OS, Samantha, is designed to evolve and adapt her personality to appeal to Theodore.

"The information all becomes shareable and then the decision will be made by these kind of guardian angels for each of the firefighters," said Edward Chow, manager of the Jet Propulsion Laboratory's Civil Program Office and AUDREY program manager. The AI automatically warns a police officer inside to evacuate, while also telling incoming firefighters or hazardous-material teams to address the threat quickly. Those firefighters, police officers and EMTs of the future will carry body-worn sensors, cameras and augmented glasses with heads-up displays. "The proliferation of miniaturized sensors and internet of things devices can make a tremendous impact on first responder safety, connectivity and situational awareness," said John Merrill, Next Generation First Responder program manager for the DHS' Science and Technology Directorate.

The time has arrived when every marketer, every business owner should buckle up themselves to face the shift from Text Based Search to Voice Search in the digital world.

Below there's the whole Gist page containing the full Python code. It has been developed and tested with Theano/GPU support, but it can easily work with CPU-only support. Any comment or suggestion is welcome!

It has been developed and tested with Theano/GPU support, but it can easily work with CPU-only support. Any comment or suggestion is welcome!

In this post I refer to lyrics of certain bands as being "Metal". I know some people have strong feelings about how genres are defined, and would probably disagree with me about some of the bands I call metal in this post. I call these band "Metal" here for the sake of brevity only, and I apologise in advance. It is all around us, and the rate at which it is produced in written, stored form is only increasing. It is also quite unlike any sort of data I have worked with before. Natural language is made up of sequences of discrete characters arranged into hierarchical groupings: words, sentences and documents, each with both syntactic structure and semantic meaning. Not only is the space of possible strings huge, but the interpretation of a small sections of a document can take on vastly different meanings depending on what context surround it.

Who here remembers taking computer programming in school? Whether you learned programming by punching holes in a never ending series of cards, or by writing simple DOS or other computer language commands, the fact remained that computers needed an incredibly precise set of instructions to accomplish a task. The more complicated the task, the more complicated your instructions had to be. Machine learning is inherently different. Rather than telling a computer exactly how to solve a problem, the programmer instead tells it how to go about learning to solve the problem for itself.

Any aspiring science fiction writer looking for a good protagonist could do worse than ripping off the Wikipedia page for Demis Hassabis: He grew up in England as a chess prodigy and built absurdly sophisticated video games before getting a degree in computer science from Cambridge, started studying neuroscience and publishing respected papers on amnesia and other topics, and then proceeded to co-found one of the hottest artificial-intelligence startups. Now that his company, DeepMind, has been snapped up by Google for a reported 400 million to 500 million (depending on your tech blog of choice), exactly how this latest twist will change his story remains to be seen--but there's a decent chance Hassabis will ultimately become commander of an army of humanoid Googlebots. Google's acquisition of Hassabis and the rest of the DeepMind team points to the surging interest in the field of deep learning, a funky part of computer science seen as key to building truly intelligent machines. It centers on having computers learn to do tasks and find patterns on their own. Google, for example, received attention a couple of years ago, when its network of self-learning computers were able to understand the concept of a cat and find cats in YouTube videos.

Scientists at IBM have claimed a computational breakthrough after imitating large populations of neurons for the first time. Neurons are electrically excitable cells that process and transmit information in our brains through electrical and chemical signals. These signals are passed over synapses, specialised connections with other cells. It's this set-up that inspired scientists at IBM to try and mirror the way the biological brain functions using phase-change materials for memory applications. Using computers to try to mimic the human brain is something that's been theorised for decades due to the challenges of recreating the density and power.

Machine learning and artificial intelligence are some of the hottest fields in tech right now. While the terms have kind of become buzzwords in startup land, Google has had teams doing research and building AI-driven applications for years. For example, the company established its "Brain" group five years ago and the team has since penned dozens of papers, built an open-source AI system called TensorFlow, and influenced a bunch of Google products and services like Photos, SmartReply, and speech recognition. The team held a question and answer session yesterday on Reddit, and one of the most striking parts (to someone not entrenched in that world, at least) was reading about the crazy-diverse backgrounds that Google Brain team members have. You might think that to be working at one of the preeminent machine learning groups, you would have to have a degree in computer science from Stanford.