Several years ago, when I was at university, I was involved in the theater. One day, in an exercise linked to the interpretation of a character, I asked my teacher if what I was doing was "perfect". He suggested that in the theater, the concept of'accuracy' was better than'perfection'. No actor is'perfectly' Romeo or Caligula. Instead, the image of the character emerges from the actor's interpretation of a text written perhaps a century or more ago.
Back in 2016, at the London International Festival of Science Fiction and Fantastic Film, in the 48hr Film Challenge, filmmaker Oscar Sharp and artificial intelligence (AI) researcher Ross Goodwin entered a film called Sunspring (https://www.youtube.com/watch?v LY7x2Ihqjmc). The unique thing about the film was that it had been entirely scripted by an AI. The AI was originally called Jetson, but later named itself Benjamin. The AI not only wrote the script, it even did the background score and put the acting together using face-swapping and voice-generating technologies. Benjamin was given thousands of hours of old films and green screen footage of professional actors, and allowed to put the film together.
Jurassic World, Avengers: Infinity War, the latest in the Star Wars franchise, Solo: Movie theatres, as usual, are jam-packed with sequels this summer. Hollywood is addicted to sequels for one reason: A proven concept can reduce the risk of failure in a business where hundreds of millions of dollars are at stake. But some Canadian tech entrepreneurs believe the the odds of making an original hit movie could be greatly improved -- and so could sequels -- with the help of artificial intelligence. "Hollywood is using very primitive data analytics," said Jack Zhang, of Greenlight Essentials in Kitchener, Ont. His company's software analyzes movie plots, audience profiles and box office ticket sales to predict a film's future success and help identify who will watch.
In today's world, every customer is faced with multiple choices. For example, If I'm looking for a book to read without any specific idea of what I want, there's a wide range of possibilities how my search might pan out. I might waste a lot of time browsing around on the internet and trawling through various sites hoping to strike gold. I might look for recommendations from other people. But if there was a site or app which could recommend me books based on what I have read previously, that would be a massive help. Instead of wasting time on various sites, I could just log in and voila! 10 recommended books tailored to my taste. This is what recommendation engines do and their power is being harnessed by most businesses these days. From Amazon to Netflix, Google to Goodreads, recommendation engines are one of the most widely used applications of machine learning techniques. In this article, we will cover various types of recommendation engine algorithms and fundamentals of creating them in Python. We will also see the mathematics behind the workings of these algorithms. Finally, we will create our own recommendation engine using matrix factorization.
The safety driver in a self-driving Uber was not being very safe -- aka, not paying attention -- when the vehicle in autonomous mode struck and killed a woman in an Arizona city earlier this year, police records show. Included in a massive Tempe Police Department report this week were details about the March 18 fatal crash. The 318-page report found that Rafaela Vasquez, the 44-year-old driver, was frequently looking down and even smiling and laughing at what appears to be a cellphone streaming an episode of the talent search show, The Voice. In the moments before the test vehicle hit 49-year-old Elaine Herzberg, who was walking her bicycle across a Tempe, Arizona, road, the test driver, Vasquez, was apparently streaming the TV show through Hulu. A video of the moments before the crash shows Vasquez looking toward her right knee while occasionally looking up and around.
C-3PO and R2-D2 are an odd couple in the Star Wars universe. C-3PO is a cowardly droid who obeys pre-defined protocols and routine tasks, while R2-D2 is a curious and adventurous robot who learns from previous problems, uses logical thinking and larger concepts to solve new problems. But together they do things they could not do alone. Similarly, RPA (Robotic Process Automation) and Advanced Analytics are an odd but very complementary combination of new business technologies. Like the diligent but unimaginative C-3PO, RPA follows precise rules to execute repetitive business processes; and like the curious and adaptable R2-D2, Advanced Analytics learns to make complex judgments when faced with new situations.
Is the newest droid in the "Star Wars" universe the future of modern robotics? In the recently released film "Solo: A Star Wars Story," the droid L3-37, also known as L3 or Elthree, showcased a unique set of traits among "Star Wars" robots. The intelligent pilot droid is always changing, improving and repairing itself with found scraps from other bots. L3 is also one of the first bots in the "Star Wars" franchise to bring feminine programming to a major role. L3 is a hodgepodge of various droids and astromechs, which are robots typically used for repairs aboard starships in "Star Wars."
This is my latest short film sharing some thoughts on my #1 speaking topic: humans versus/with machines, artificial intelligence and the future of humanity in a world where machines can hear, see, speak, learn and'think'. On the one hand, artificial intelligence (AI) clearly has the capacity to improve our lives in pretty much every aspect, from energy to medical to smart cities; on the other end it could fundamentally change who we are as humans, and what we think of as'human'. It could be a great destroyer of jobs but it could also free as from unsatisfying routines. But if machines become truly'intelligent' what will be left for us to do... you may ask. I think it will all come down to what I call DIGITAL ETHICS i.e. how will we use technology to our collective human benefit (i.e.
When you consider the popularity of Amazon's virtual assistant Alexa and the company's Fire TV streamers, it was really just a matter of time before the folks at the Everything Store decided to mash them up. In fact, Amazon already has, sort of: The company started down that path last year by giving Echo devices the ability to pass commands along to a Fire TV or Fire TV Stick. With the new Fire TV Cube, though, Amazon is trying to break down the wall between Alexa and the content you want to see altogether. Now, we've only had our Fire TV Cube for about two days, and that's just not enough time to really put the streaming box through its paces -- instead, read on for our first impressions about Amazon's new hardware and the virtual assistant that will ultimately make or break it. The Fire TV Cube itself is a glossy black box that, aside from the blue ring that lights up when Alexa is listening to you, looks about as nondescript as a bit of home theater kit can be.
All of us have heard about driverless cars, automated machines, bots and virtual assistants, even if we don't fully understand what these terms mean. All of these are manifestations of self-learning algorithms, smart technologies such as Artificial Intelligence (AI) and Machine Learning (ML). The application of these technologies is no longer just limited to sci-fi movies and erudite research papers. Directed by data-driven insights from these powerful technologies, traditional decision-making by experienced professionals is slowly being transformed. Let's take a look, then, at this metamorphosis that AI is ushering in across business functions such as marketing.