ChatGPT and other large-scale language models touted a new age of AI, or even the Fifth Industrial Revolution, pushing AI into mainstream consciousness. With his Nvidia joining the high-profile “AI wars” and the participation of trillions of dollars in hyperscalars, this hype is unlikely to stop anytime soon.
With clients flooding ARC with questions, I recently embarked on a new adventure into the complex world of industrial AI breakthroughs. I have years of expertise in IT, OT, and ET, but I’m not an artificial intelligence expert. 
Intelligence. In the first installment of this blog series, I plan to ask more questions than provide answers and be an avid guide on my journey of discovery. Together, we navigate the twists and turns of the latest advances in AI, stopping at the point of discovering repeatable business value. Buckle up and join us on this thrilling expedition. The ever-evolving realm of AI proves that even industrial engineers can learn new tricks.
As I plunged headlong into this fascinating underworld, I found myself tumbling down the rabbit hole of machine learning history. There, he rediscovered neural networks (which I had used in his advanced process control solutions over 20 years ago), a fascinating technique for annotating and labeling data. , and myriad types of learning: unsupervised, semi-supervised, supervised, and even reinforcement learning from human feedback (RLHF). All this exploration led me to the gateway to the much touted Large Language Models (LLM) and Foundation Models (FM) that have taken the AI world by storm. OpenAI’s ChatGPT, Google’s PaLM, and Amazon’s Titan FM, to name a few. . These giants in the artificial intelligence space have piqued my curiosity, and I am eager to unravel their mysteries as I share my findings with you. So let’s continue our journey through this enchanting landscape, distinguishing between fact and fiction in the ever-expanding world of AI.
Fear not, industrial engineers. This expedition is tailored specifically for us, hardcore problem solvers striving to make a difference in a resource-poor world. Our mission is to focus on high-value business outcomes while navigating the complex process of designing, sourcing, manufacturing, selling, delivering and servicing sustainable products and services. We are not just wading into the vast ocean of AI’s far-reaching impact on society. Instead, we focus on specific applications and innovations that revolutionize the industry. While staying true to your roots and core values as a dedicated industrial engineer, why not roll up your sleeves, think more, and dive deeper into the fascinating world of AI-powered solutions.
The next chapter in this AI journey will tackle the myriad of thought-provoking questions swirling in my head. Let’s consider the following together.
- What data governance and “data fabric” do you need as the foundation for industrial AI use cases?
- With the new level of digitization of industrial data, how should the use of AI in industrial organizations be managed to manage the potential loss of intellectual property (IP) and increased cybersecurity risks? Is not it?
- Is Generative AI the most efficient tool for any industrial AI use case?
- What are the high-value industrial AI use cases that will benefit most from generative AI?
- Will generative AI change the balance of people, process and technology in industry organizations?
- Can industrial AI systems fill the skills gap in real-world manufacturing?
- How do you decide where you need Human Involvement (HIL) and which industrial use cases have the potential to become autonomous?
- Are the carbon costs of generative AI ecosystems receding in the pursuit of more sustainable products and services?
- How should the convergence of IT, OT, and ET evolve to better capture the business value of industrial AI?
- In the quest for true industrial intelligence, who will be the leader in industrial software, harnessing their expertise to power generative AI and surpass it?
- In the race to harness the full potential of AI, are investments in industrial cloud and industrial metaverse sidelined by hyperscalar?
- How is AI reshaping the industrial ecosystem? Who should we partner with?
- With the limits of generative AI exposed and demands for traceability, explainability and ethical practices already surfacing in the EU and US, what will happen next for AI? Causal AI? Explainable AI?
With the limits of generative AI exposed and demands for traceability, explainability and ethical practices already surfacing in the EU and US, what will happen next for AI? Causal AI? Explainable AI?
I and the rest of the ARC team look forward to your valuable contributions as we embark on this fascinating journey together. Share your questions, experiences, learnings and solutions with us as we believe collaboration is the key to unlocking the true potential of AI in industry. Your insights not only enrich our collective knowledge, but also help us navigate the ever-evolving world of industrial AI more effectively. As a cohesive community of passionate engineers eager to learn, grow and innovate together, let’s join forces to explore this fascinating landscape.
