Can you tell us more about how you're working with the MIT Open Documentary Lab to use artificial intelligence to'fill in the blanks' so to speak?

Artificial intelligence is a staple of many movie plots – and those thrilling stories often revolve around the potential dangers of AI, rather than the good it can do. Since popular culture plays a part in shaping attitudes about technology, it's not surprising that questions surrounding AI are informed by what we see in the movies. People are asking whether we are creating a future that we'll be able to control, and whether computers will remain accountable to people. This, too, has been the stuff of science fiction in popular films. Here are five times Hollywood has taken on AI.

Artificial intelligence has already permeated our lives as consumers. The transformation was discreet, but it has made things better in every way. The last time you used Netflix, an AI helped you decide what to watch, when you shopped on Amazon, an artificial intelligence influenced what you purchased, and when you ordered that Uber, an AI helped find the best driver for you. In all of these instances, artificial intelligence improved the way in which you interacted with the product or service. Ultimately, the positive interaction that was generated when you found the perfect show to binge-watch, toaster to purchase, or got a ride, was due to an AI that optimized your experience.

Machine learning has been reshaping our lives for quite a while now. Be it the smallest thing such as unlocking your phone through Face Recognition to useful interactions with Siri, Alexa, Cortana, or Google using Speech Recognition, machine learning is everywhere! In this article, I am going to provide a brief overview of machine learning and data science. With a basic understanding of these concepts, you can dive deeper into the details of linear regression and how you can build a machine learning model that will help you to solve many practical problems. The article will focus on building a Linear Regression model for Movie Budget data using various modules in Python.

"Please think forward to the year 2030. Analysts expect that people will become even more dependent on networked artificial intelligence (AI) in complex digital systems. Some say we will continue on the historic arc of augmenting our lives with mostly positive results as we widely implement these networked tools. Some say our increasing dependence on these AI and related systems is likely to lead to widespread difficulties. Our question: By 2030, do you think it is most likely that advancing AI and related technology systems will enhance human capacities and empower them? That is, most of the time, will most people be better off than they are today? Or is it most likely that advancing AI and related technology systems will lessen human autonomy and agency to such an extent that most people will not be better off than the way things are today? Please explain why you chose the answer you did and sketch out a vision of how the human-machine/AI collaboration will function in 2030.

The research also found U.S. employees are split on their perception of their readiness to work with AI. In fact, just over half (52%) of the U.S. employees surveyed believe they have the necessary skills to be successful in an AI-enabled workplace. However, almost as many (48%) doubt they have what it takes, with 20% saying they do not possess the right skills and 28% reporting they simply aren't sure. But confident Millennial employees are the most likely age group to feel their current skillset will meet the challenge of AI. "The most successful AI deployments take more than good data and the best technology – people are an equally important part of the equation. We believe that's why employers should be investing in their people to prepare them for a future workplace that will change as a result of this intelligent technology," said Merijn te Booij, chief marketing officer, Genesys.

AI and machine learning are the driving forces for innovations in the field of precision medicine.