Sony recently released two songs composed by AI and French composer Benoît Carré arranged, produced the songs, and wrote the lyrics. Sony has also announced a full album made by their AI to be released in 2017. Earlier, AI had written the screenplay for a short film (though it doesnt make too much sense, for now). It is already known that many media sources, including Yahoo, have been using AI to write articles for their websites. AI at Google has attempted its hand at poetry and with good result.

Bailey's ruminations bear rereading now that five years have passed since their first appearance. We have survived the advent of the new Millennium, and we have found once again that, after the divine afflatus, human intellect reigns supreme in the cosmos. This is not to say that Bailey's postulations have no merit. The advances of the computer age, particularly in the still-infant and arcane discipline of artificial intelligence, continue to fascinate us and to challenge us. Yet even with the burgeoning networks and the increasingly powerful integration of humanity and its machines, the surprises offered by the observations of the young and young-in-spirit still outdo those of scientific teams.

If you're a dog lover, you may have heard of Chaser, the border collie who has been called a "genius" and the "smartest dog in the world." Retired psychology professor John Pilley, Chaser's owner and co-author of a recent book about her, says he was able to teach her 1,000 words, the largest "vocabulary" of any non-human animal on record. Dog lovers and handlers alike tend to agree that some canines are quicker to catch-on, learn new tricks, and solve problems than other dogs. But how do we know that one dog is really smarter than another--possessing greater general intelligence--and not just more talented at specific tasks, such as learning words, or more easily trained? Despite growing interest in dog cognition over the past 20 years, it wasn't until very recently that scientists tried to answer this particular question empirically.

Sony recently released two songs composed by AI and French composer Benoît Carré arranged, produced the songs, and wrote the lyrics. Sony has also announced a full album made by their AI to be released in 2017. Earlier, AI had written the screenplay for a short film (though it doesnt make too much sense, for now). It is already known that many media sources, including Yahoo, have been using AI to write articles for their websites. AI at Google has attempted its hand at poetry and with good result.

As our species continue to develop more and more advanced technology it is getting nearly impossible to predict how next centuries will look like. Scientists in the 18th century could not even comprehend quantum physics, today we are developing first models of quantum computers. In the 20th century first models of primitive 3D printers started to appear. They could only print some very basic objects such as geometrical shapes. As for today we print bones, ears, blood vessels, skin and heart tissues.

We introduce a new artificial intelligence (AI) approach called, the 'Digital Synaptic Neural Substrate' (DSNS). It uses selected attributes from objects in various domains (e.g. chess problems, classical music, renowned artworks) and recombines them in such a way as to generate new attributes that can then, in principle, be used to create novel objects of creative value to humans relating to any one of the source domains. This allows some of the burden of creative content generation to be passed from humans to machines. The approach was tested in the domain of chess problem composition. We used it to automatically compose numerous sets of chess problems based on attributes extracted and recombined from chess problems and tournament games by humans, renowned paintings, computer-evolved abstract art, photographs of people, and classical music tracks. The quality of these generated chess problems was then assessed automatically using an existing and experimentally-validated computational chess aesthetics model. They were also assessed by human experts in the domain. The results suggest that attributes collected and recombined from chess and other domains using the DSNS approach can indeed be used to automatically generate chess problems of reasonably high aesthetic quality. In particular, a low quality chess source (i.e. tournament game sequences between weak players) used in combination with actual photographs of people was able to produce three-move chess problems of comparable quality or better to those generated using a high quality chess source (i.e. published compositions by human experts), and more efficiently as well. Why information from a foreign domain can be integrated and functional in this way remains an open question for now. The DSNS approach is, in principle, scalable and applicable to any domain in which objects have attributes that can be represented using real numbers.

AI can help to bridge the gap between brands and their audiences, connecting them in direct and practical ways. This fuels the question, however, about how AI can and should be used, and where its benefits can be applied most effectively. The news of the first film trailer created using AI brought into focus the rapid pace with which new applications are being surfaced. But it should be noted that what the AI actually did was to select scenes from which the trailer would be created, based on its analysis of hundreds of previous horror movie trailers. The task of assembling those scenes, editing them and adding music and effects to tell a coherent story (i.e. the actual creative task) fell to a person.

There's no denying that artificial intelligence is lightyears ahead of what it was just a few years ago. The technology continues to advance at an ever-increasing rate. But the ultimate goal of artificial intelligence researchers is to replicate human intelligence. So how do artificial intelligence and human intelligence measure up? The so-called "deep learning" that artificial intelligence is capable of isn't really the type of profound learning like humans are capable of.

There's no denying that artificial intelligence is lightyears ahead of what it was just a few years ago. The technology continues to advance at an ever-increasing rate. But the ultimate goal of artificial intelligence researchers is to replicate human intelligence. So how do artificial intelligence and human intelligence measure up? If after all these years, human intelligence is still vastly superior to artificial intelligence, why do artificial intelligence researchers even bother?

There's no denying that artificial intelligence is lightyears ahead of what it was just a few years ago. The technology continues to advance at an ever-increasing rate. But the ultimate goal of artificial intelligence researchers is to replicate human intelligence. So how do artificial intelligence and human intelligence measure up? Why even try If after all these years, human intelligence is still vastly superior to artificial intelligence, why do artificial intelligence researchers even bother?