By Catherine Loftus / Head of Growth Marketing, Nuon AI
Welcome to part two in our series exploring real-world applications of AI and the problems it can solve. In part one, we explored examples of AI that have been developed to solve specific existing problems – from medical diagnostics to insurance retail pricing.
Don’t miss: The problem-solving power of AI – Part One
In this second instalment, we’re delving into examples of AI which have been developed thanks to leaps forward in technological innovation, where the potential to solve problems have become apparent once the AI is out in the world.
Generative AI models
Let’s start with what has become one of the most well-known applications of AI: Generative AI, such as ChatGPT.
The viral chatbot developed by OpenAI that catapulted AI into the mainstream has exploded in daily life. From helping students write essays, to planning travel itineraries, debugging code or translating text, ChatGPT (also known as GPT-3) is solving problems in both professional and personal capacities.
Chatbot models like GPT-3 were initially developed with the primary aim of generating human-like responses based on the input they receive, to complete language-based tasks. However, their application in providing conversational interactions has caught the attention of the mainstream, leading to their use in multiple areas including customer support, virtual assistants, and creative writing.
Read more: An AI engineer’s perspective on ChatGPT
Style Transfer in art and design
According to Phosus, style transfer is a technique that allows the transfer of the style of one image to another image while preserving the content of the target image, typically by using neural networks or deep learning. It results in a new image that combines the content of the input image with the style of the reference image, creating a new and unique image from two different inputs.1
This technique was initially developed as an experimental form of image processing. However, over time, Style Transfer found applications in creating unique artworks, graphic design, and even generating commercial creative content.
Autonomous vehicles and simulations
Advances in AI and machine learning assisted in the development of autonomous vehicle systems by brands including Tesla, Rivian and Lyft. While initially this technology was geared towards the creation of self-driving cars, the resulting tech developed for navigation, perception, and decision-making have also found applications in simulators for training human drivers, testing scenarios, and even entertainment through racing video games.
Whether AI is being applied to solve a specific problem, or its potential for problem solving has been discovered later, it’s clear that AI technologies have become hugely influential in day-to-day life.
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Sources:
1 Phosus: Style Transfer
