8CIOReview | | SEPTEMBER 2023IN MY OPINIONJarrod Anderson heads the AI Team at a major nutrition company, where his team of AI engineers and data scientists create innovative technology solutions for global supply chains, manufacturing, transportation, commodity trading, the human microbiome, and food ingredients.The introduction of Generative AI into the world of the Industrial Internet of Things (IIOT) promises to revolutionize the way we design and manufacture products. Generative AI is a powerful tool that can create entirely new designs based on deep learning algorithms. With the advent of Augmented Reality (AR), it can also help easily visualize these designs prior to production. In terms of IIOT specifically, Generative AI has the potential to drastically reduce costs associated with product development while simultaneously streamlining workflow.This game-changing technology has already made its way into IIOT applications such as robotic automation and machine-learning-based predictive maintenance systems, allowing for unprecedented levels of efficiency across industrial sectors. But what sets Generative AI apart from previous technologies used in IIOT systems is its ability to generate entirely new products from existing data -- something no other set of tools has achieved at this level before.By leveraging deep learning algorithms, generative AI can take existing products or prototypes and create infinite variations for further evaluation or market testing. As a result, companies can rapidly develop innovative solutions tailored specifically to their niche market without sacrificing time or resources.In this article, we will briefly explore how Generative AI will impact IIOT in the areas of Augmented Reality and generating new designs and products, as well as what this means for businesses operating within this space.What is Generative AI?Generative AI is a type of artificial intelligence capable of creating new data, such as images, videos, text, or audio that is similar to existing data but not identical. It can be used for various tasks, such as image generation, text generation, music generation, and video generation, among others.There are two main types of Generative AI:Generative Adversarial Networks (GANs): GANs consist of two neural networks: a generator and a discriminator. The generator creates new data, and the discriminator evaluates the authenticity of the generated data. The two networks are trained together, and the generator improves over time to create data that is indistinguishable from real data.Variational Autoencoders (VAEs): VAEs consists of an encoder and a decoder network. The encoder network compresses the input data into a lower-dimensional representation, and the decoder network generates new data similar to the input data.By Jarrod Anderson, Senior Director, Artificial Intelligence, ADMGENERATIVE AI IN IIOT
< Page 7 | Page 9 >