Feature AI are often seen as cold, calculating machines, devoid of any warmth or humanity. One way to make AI more relatable and human-like could be encouraging them to take part in human activities like making music. Using AI is one of the geekiest ways to make tunes, and has been around since the 80s. It's a thriving area of research with dedicated academic conferences. And with the recent boom in machine learning, it also means the quality of music created by AI seems to be getting better too.

The brain is often said to be like a computer. Now it turns out that we store memories of famous people in a similar way to Google. Our hippocampi – two small, curved brain structures towards the sides of our head – are crucial for memory. Studies have found that people with damage in these areas can no longer make memories of new events. By studying people who had recording electrodes put into their hippocampi, Rodrigo Quian Quiroga at the University of Leicester, UK, previously found that some neurons in these areas fire only when we see particular celebrities or people we recognise.

Most of the talks will be given by well-known invited speakers. However, we would also like to give students and startups an opportunity to present their work and research. It will be realized in the form of short lightning talks. Each speaker will get a free ticket to the conference. If you are interested in becoming a lightning speaker, please send us a short paper (less than 1000 words) describing your machine learning project.

"Algorithm" might be one of the most popular terms that almost no one understands. Not many people have PhDs in data science, and even those experts don't always know what's happening. "It's not clear even from a technical perspective that every aspect of AI algorithms can be understood by humans," says Guruduth Banavar, IBM's chief science officer for cognitive computing, which is what IBM calls AI. Artificial intelligence is making decisions by reviewing people's medical tests in hospitals, credit histories in banking, job applications in some HR systems, even criminal risk factors in the justice system. Yet it's not always clear how the computers are thinking.

'Siri, catch market cheats': Wall Street watchdogs turn to A.I. NEW YORK (Reuters) - Artificial intelligence programs have beaten chess masters and TV quiz show champions. Two exchange operators have announced plans to launch artificial intelligence tools for market surveillance in the coming months and officials at a Wall Street regulator tell Reuters they are not far behind. Executives are hoping computers with humanoid wit can help mere mortals catch misbehavior more quickly. The software could, for instance, scrub chat-room messages to detect dubious bragging or back slapping around the time of a big trade. It could also more quickly unravel complex issues, like "layering," where orders are rapidly sent to exchanges and then canceled to artificially move a stock price.

Video games where people matter? If you're a video game fan of a certain age, you may remember Edge magazine's controversial review of the bloody sci-fi shooting game, Doom. Perhaps you enjoyed a good laugh, as many first-person shooter fans have, at the writer's much-mocked assertion: "if only you could talk to these creatures, then perhaps you could try and make friends with them, form alliances … Now that would be interesting." Of course, we all know what happened. There would be no room in the Doom series, nor any subsequent first-person blast-'em-up, for such socio-psychological niceties. Instead, we enjoyed 20 years of shooting, bludgeoning and stabbing, the ludicrous idea of diplomacy cast roughly aside. But during this era, something else was happening in game design, and in academic thinking around video games and artificial intelligence.

Can your tweets reveal your gender? When you post a tweet or write a status on Facebook, your choice of words sends and impression to others on all aspects of your life. But often these impressions can be wrong - especially when it comes to gender. For example, if you tweet about technology, people will assume you are a man, but if you use the words'love' or'fashion' people will think you are female. Using a form of artificial intelligence, researchers have identified the line where stereotyping goes from'plausible' to wrong.

Is Spotify damaging your hard drive? Spotify has issued a fix for a bug for that has been bombarding user's hard drives with huge amounts of data for as long as five months Multiple reports on Spotify's user forums and across the internet appear to show that the bug is not isolated to any one region. 'Typically, the app wrote from 5 to 10 GB of data in less than an hour on Ars reporters' machines, even when the app was idle', reported Ars Technica. 'Leaving Spotify running for periods longer than a day resulted in amounts as high as 700 GB'. Millions of devastated Tinder users are forced to spend a... Google's self-driving cars can now perform tricky...

Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively 6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer. The human brain is capable of remarkable acts of perception while consuming very little energy.

What do you get if you cross aspirin with ibuprofen? Harvard chemistry professor Alán Aspuru-Guzik isn't sure, but he's trained software that could give him an answer by suggesting a molecular structure that combines properties of both drugs. The AI program could help the search for new drug compounds. Pharmaceutical research tends to rely on software that exhaustively crawls through giant pools of candidate molecules using rules written by chemists, and simulations that try to identify or predict useful structures. The former relies on humans thinking of everything, while the latter is limited by the accuracy of simulations and the computing power required.