Walk This Way, produced by Rick Rubin, is another great example. By 1986, hip hop originators Run DMC boasted serious local hero status. Jam Master Jay, the group's DJ, had used the iconic breakbeat from Aerosmith's track, but the aging rock band had no idea who Run DMC were. When Rubin suggested Run DMC cover Walk This Way in collaboration with Aerosmith, the rap group needed some serious persuading to re-interpret the, by words of MC Run, "hillbilly gibberish" lyrics. The unlikely collaboration took the world by storm, giving Run DMC the first multi-platinum hip hop record and slingshotting the underground genre into the mainstream culture it is today.

What does AI creativity mean for Human creativity? As the sophistication of Aritifical Technology in the field of creativity continues to grow, there is no doubt that an increasing worry in the eventual obsoletion of human creative tasks has begun to arise. Instead of concering ourselves with this now overused dystopian sci-fi trope however, we should instead be shifting the discussion onto how Artificial Intelligence technology can be used to benefit our own creativity. There is no need in pitting ourselves and AI against each other, especially not this early into its development, and a mutual collaboration would much greatly benefit our creative capabilities in the long run. Defining creativity is an incredibly difficult task as the concept of creativity can vary depending on the individual and its cultural and situational implications. Even so, a clear distinction between human creativity and artificial creativity has been certainly demonstrated.

Machine learning has been trotted out as a trend to watch for many years now. But there's good reason to talk about it in the context of 2020. And that's thanks to developments like TensorFlow.js: an end-to-end open source machine learning library that is capable of, among other features, running pre-trained AI directly in a web browser. It means that AI is becoming a more fully integrated part of the web; a seemingly small and geeky detail that could have far reaching consequences. Sure, we've already got examples a plenty of web tools that use AI: speech recognition, sentiment analysis, image recognition, and natural language processing are no longer earth-shatteringly new.

With all these tantalizing possibilities on the brink of becoming a reality, it's a pity we've had to wait so long for a proper web-side machine learning solution. Then again, it was this insufficient AI performance on mobile devices that encouraged TensorFlow's (as in server-side TensorFlow – the .js And now that we finally have the gift of true web machine learning, 2020 could well be the year that developers unleash their AI creativity.

You may be feeling uncertainty about the future of creativity in what feels like a pretty complex environment. It's the classic right brain/left brain, the blending of art and science to drive innovation, which has become more important than ever before. At a time of advancing automation, creativity remains the essential differentiator. Discover how market leaders are increasing engagement and performance by anticipating customer behavior, and learn how you can create more valuable experiences with artificial intelligence (AI)-powered targeting solutions, such as In-market Audiences, Custom Audiences and LinkedIn Profile Targeting. There will be a live Q&A following the presentation, so bring your questions and take advantage of engaging directly with the experts.

AI's role in Morgan, and numerous other creative endeavors, shows how far AI has come. Using techniques such as deep learning has enabled tremendous progress, but AI remains relegated to an assistant role--for now. "What's interesting is that, compared to a lot of other machine learning techniques, deep learning technology is what's called a'generative model,' meaning that it learns how to mimic the data it's been trained on," explains Jason Toy, CEO of Somatic, a start-up focused on developing deep learning applications. "If you feed it thousands of paintings and pictures, all of a sudden you have this mathematical system where you can tweak the parameters or the vectors and get brand new creative things similar to what it was trained on." But even highly touted AI techniques have their limitations.

AI's role in Morgan, and numerous other creative endeavors, shows how far AI has come. Using techniques such as deep learning has enabled tremendous progress, but AI remains relegated to an assistant role--for now. "What's interesting is that, compared to a lot of other machine learning techniques, deep learning technology is what's called a'generative model,' meaning that it learns how to mimic the data it's been trained on," explains Jason Toy, CEO of Somatic, a start-up focused on developing deep learning applications. "If you feed it thousands of paintings and pictures, all of a sudden you have this mathematical system where you can tweak the parameters or the vectors and get brand new creative things similar to what it was trained on." But even highly touted AI techniques have their limitations.