The problem with sequels is that they're forced to juggle the task of being a stand-alone story while simultaneously building off the success of their predecessors. Capturing the same feeling of another film and trying to expand upon it without alienating audiences is a feat that few filmmakers have ever accomplished - and coming across a sequel that actually eclipses its inspiration is even rarer. The first Terminator movie was, in many ways, an '80s slasher flick. Released during the height of the genre's popularity, the film focuses on a young woman fleeing from a seemingly unstoppable force. In all honesty, it's a bit generic: the sci-fi setting gives the film a slightly different feel, but the film never truly sheds its genre baggage. When Terminator 2: Judgment Day was released nearly 10 years later, many moviegoers were expecting more of the same - but that's not what they got.

I was electrified by Jonathan Berger's music before I knew he wrote about music. His chamber works arise out of a lightning storm of modernist angles, dramatic and startling, though anchored to melodies that sail like a swallow, as one of his string quartets is called. His one-act operas Theotokia and The War Reporter, performed together in concert, match taut musical brocades to the hallucinations of, respectively, a schizophrenic, hearing voices of various mothers, and a photojournalist, based on Paul Watson, who won the 1994 Pulitzer Prize for his image of the corpse of an American soldier being dragged through the streets of Mogadishu. A few years ago, I read some of Jonathan's academic writing about music, which had a sharp focus on neurology and acoustics. He is a professor of music at Stanford, where he teaches composition, music theory, and cognition at the Center for Computer Research in Music and Acoustics. On a hunch that he could connect with a popular audience, I asked him to write an essay for Nautilus about how composers upend expectations to keep listeners off guard and engaged. That article, "Composing Your Thoughts," and his next one for Nautilus, "How Music Hijacks Our Perception of Time," which contain musical clips to illustrate his points, have been among our most popular articles. There's a certain amount of problem solving that happens in the context of a band of noise. For this month's issue I called Jonathan and was delighted to learn he had thought a lot about noise.

Cell phones, in particular the'flip phone' popular in the early 2000's, look a lot like Star Trek communicators. The world seen in Star Trek movies and shows is meant to take place hundreds of years in the future. And while we're still waiting on warp drives and transporters some of the technology portrayed in the shows as wildly futuristic is available now. Here are some examples of technology that've taken the fiction out of science fiction in the 50 years that Star Trek has been around. One of the most remarkable technologies seen in the 1966 original series was the communicator.

You may think you choose to read one story over another, or to watch a particular video rather than all the others clamouring for your attention. But in truth, you are probably manipulated into doing so by publishers using clever machine learning algorithms. Every day the web carries about 500,000 tweets, 300 hours of YouTube video uploads, and more than 80 million new Instagram photos. Just keeping up with our friends' Facebook and Twitter updates can seem like a full-time job. So publishers desperately trying to get us to read and watch their stuff in the face of competition from viral videos and pictures of cats that look like Hitler are enlisting the help of data analytics and artificial intelligence (AI).

In December 1964, over a single evening session in Englewood Cliffs, New Jersey, John Coltrane and his quartet recorded the entirety of A Love Supreme. This jazz album is considered Coltrane's masterpiece – the culmination of his spiritual awakening – and sold a million copies. What it represents is all too human: a climb out of addiction, a devotional quest, a paean to God. Five decades later and 50 miles downstate, over 12 hours this April and fuelled by Monster energy drinks in a spare bedroom in Princeton, New Jersey, Ji-Sung Kim wrote an algorithm to teach a computer to teach itself to play jazz. Kim, a 20-year-old Princeton sophomore, was in a rush – he had a quiz the next morning.

In this image released by Warner Bros. Entertainment, cast members, clockwise from left, Margot Robbie, Adewale Akinnuoye-Agbaje, Joel Kinnaman, Will Smith, Jai Courtney and Karen Fukuhara appear in the film, "Suicide Squad." This week's Comic-Con is expected to draw more than 160,000 fans for high-energy sessions featuring casts and crews from such films and TV shows as "Game of Thrones," "Star Trek," "Suicide Squad," "South Park," "Teen Wolf," "Aliens" and "The Walking Dead."(Clay

In this episode of Reinventing Retail, we find out how predictive analytics are giving retailers the power to make data-driven decisions that will forever change assortment planning. Our guest is Richard Wright, VP of merchandising for Predictix: a leading provider of retail machine learning solutions. Infor announced it had completed its acquisition of Predictix on June 28, 2016. Using the artificial intelligence of machine learning technology, retailers are able to forecast potential market fluctuations and trends--with the agility to quickly adapt when disruptions are imminent. Hear what Richard has to say about this next generation retail tech, and subscribe to Reinventing Retail on iTunes for more episodes.

A similar process is done on the target images to mask out the faces and intelligently put your own in their place -- and voila! It's not limited to hairstyles, either: put yourself in a movie, a location, a painting -- as long as there's a similarly positioned face to swap yours with, the software can do it. Kemelmacher-Shlizerman has also created systems that do automated age progression, something that can be useful in missing persons cases. "This is a first step in trying to imagine how a missing person's appearance might change over time."

The author reflects on new research reports on the impact of artificial intelligence (AI) on the workplace. His prediction: AI will make internal politics nastier within management ranks. Artificial intelligence is a hot topic these days. Not surprisingly, news outlets north of the 49th parallel jumped on the release of a new research report cleverly titled "The Talented Mr. Robot: The Impact of Automation on Canada's Workforce." The study was conducted by the Brookfield Institute for Innovation Entrepreneurship, a newly created independent and nonpartisan institute, housed within the Ryerson University of Toronto, dedicated to advancing Canada's innovation and entrepreneurship.

Expert publishing blog opinions are solely those of the blogger and not necessarily endorsed by DBW. Last month, Mike Shatzkin wrote a blog post titled "Full text examination by computer is very unlikely to predict bestsellers," in which he described how the claims of the creation of an algorithm that predicts bestsellers, as outlined in a new book The Bestseller Code: Anatomy of the Blockbuster Novel, are impossible. While I agree in theory with Shatzkin that an algorithm alone cannot predict whether a book will be a bestseller or not, that isn't precisely what The Bestseller Code claims, nor what our experience working with machine learning at Intellogo defines. What we aim to do is identify similar tones, moods, topics and writing styles to those books that are topping bestseller lists--as we can only do through algorithms--and, in this way, better understand the reading audiences' desires. Machine learning allows us to do just that.