Guest post by Nell Watson, Researcher in AI Ethics and Curator of AI Con 2022
Formative AI technologies are those which can be directly applied to optimise processes based upon rapidly changing variables. Such situations can be found almost anywhere, from healthcare and business to autonomous vehicles.
These technologies have the capability to transform practically every sector or domain of the economy because they can make existing processes more efficient. Those who embrace these technologies and master their deployment can enjoy very strong advantages over competitors.
The transformative nature of such AI technologies can be compared to how electricity and motive power changed every sector a century ago, with the creation of power drills and tractors instead of mule-driven plows. All businesses must now learn to recognise the advantages that AI is bringing and will continue to bring to their sector.
One of the most exciting and immediately applicable areas of machine learning is generative AI. Generative AI techniques involve multiple neural networks competing against each other. Some try to make plausible yet fake pieces of content, and others try to detect content as being fake. If we set up a loop between them, we can breed more accurate representations of something – human faces for example.
Generative techniques can be used to turn a simple sketch into a painting in the style of a great artist at the touch of a button. They can restore damaged, lost, or obscured content. Simply by providing a few examples, they can massively upscale images or video and can even transform a video taken in winter into a summer scene, or vice versa.
In many ways, this generative form of artificial intelligence can be described as the closest thing to magic in the world today. Such technologies are being widely deployed to restore and upscale older pre-HD content in movies, TV, and games, as well as for video filters in Zoom or Snapchat. The earliest applications have focussed on visual content, but recent developments upon these generative techniques are about to unleash a great step forward.
ML is one of the hottest careers, and that is likely to increase even further. Deep Learning has emerged in the past ten years or so, enabling amazing new predictive processes that can find patterns with patterns, and make order out of chaos.
This has transformed industry but has had less immediate uptake in the office. That’s about to change, thanks to revolutionary new models such as Large Language, Transformers and Diffusions which can be dynamically reconfigured to solve thousands of problems.
With this new technology, ML is finally accessible to the masses, as we no longer require much skill beyond asking a simple question to obtain quick and reasonable assistance with almost any digital office task we could imagine.
The latest models are even generating computer code, video, 3D models, virtual personalities, and music on demand from nothing more than a description of the desired output. One might think that ML skills will be less needed as a result. However, by making the power of state-of-the-art ML clear to the public, the desire for improved machine learning capabilities to optimise almost any problem will be greatly increased.
ML is here to stay, and we will explore where it goes next with leading researchers in the field when AI Con, a conference Hosted by Kainos, returns next month. View the schedule and find out more about the conference here: https://ai-con.ai/2022/schedule.
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