The Exchanges

Q You can take rings of data and drop it in ChatGPT and then in natural language, you can query it and it will give you answers today. Um, But if you're working on the line in a factory, or if you're managing operations in some industrial settings, it's hard for me to fully picture how Generative AI can then be applicable in that setting. So how do you do it?

A A hundred percent. Well, think about an example that we're working on. Real example, real use case we're working on in development with Boston Dynamics, with Eversource Energy, and with Anthropic, ok? Three parties orchestrated as one to make manhole, Duct inspections operate at a different level, ok? So what happens in practice? We send a Boston Dynamics Spot robotic along a five kilometer manhole duct. The Eversource are required by Boston law, in Boston law, Massachusetts, that by law they have to inspect that manhole duct on a, or a periodic basis, ok? Now that robotic dog is picking up LiDAR, picking up video, image, gas sensors, heat, Temperature, pressure, all the way through that manhole duct, ok? They're spotting issues and fractures and, and problems in that environment that the human often will miss, or they might not get with the same level of accuracy. Something spotted a stress fracture on a transformer, immediately captured. GPS coordinates immediately triggering a work order, looking for the spare part, dispatching a crew. That's all happening pretty much instantaneously. Now you think about the alternative when the human's doing that, often they don't want to do that work, it's difficult to resource it, and they might not spot that, and a catastrophic failure might arise, and therefore you see issues in uptime, you see issues in transmission, all sorts of probl…

AI assessment note: “Real example, real use case we're working on in development with Boston Dynamics”

Q robot like I saw, uh, today walking around a factory floor looking for spills, uh, and probably very efficiently through computer vision, making a notice that, hey, there's a spill and maybe saving, you know, a lot of time or a potential, like, Uh, batch of product. Uh, but previously maybe that was something that a person did. So how do you think that this will impact labor moving forward?

A So I'm an optimist. Uh, and I read with great interest and agreement that all we're going to experience is growth. Uh, economic growth for sure. The predictions are one percent percentage point increase to global GDP growth in the coming years. Uh, and I look at You know, research like the World Economic Forum, who did the Future Work Study at the beginning of this year, and they concluded that a hundred and seventy million new jobs will be created by 2030, ok? Uh, ninety-two million of existing jobs will be displaced. My mathematics tell me that's seven to eight million of net new jobs, incremental jobs, and employment by 2030, ok? And what we're experiencing is, in all senses, Economic growth. So you think about growth, you think about some of that research and you think about some of the previous general purpose technology shifts that we've been through, albeit this one is different. All of them have resulted in growth and more labor and more employment and more business models. And I think the same is absolutely true here. When I put that into the real world, so put that to one side for a second, every customer that we deal with, whether it's in North America, whether it's in Europe, Whether it's in Asia and the industries that we serve to a greater or lesser extent are dealing with labor shortage today. And that's driven by aging workforces. It's also driven by re-industri…

AI assessment note: “they concluded that a hundred and seventy million new jobs will be created by 2030”

Q Is that a preview for what's going to happen with us?

A I haven't studied it in detail, but directionally, from what I understand, I think so. And I think, again, we come back to an environment where I genuinely believe there's going to be employment growth over the long term. The nature of the roles will fundamentally change, no question. And I think You know, that's a responsibility that falls onto, you know, governments, uh, higher education to be thinking about what's the shape Of the labor force to come, and how do, what does one plan for it? The nature of the jobs will be different, and there's no question, World Economic Forum said ninety-two million jobs will be displaced, and those individuals in those roles will need to be thinking about how they enhance their skills and how they develop to take on new roles.

AI assessment note: “directionally, from what I understand, I think so.”

Q So as someone who works very close to industry, Uh, you obviously are keenly aware of the need for power and how much these large language models are planning to take out of the ecosystem. What do you think the future is going to be on that front?

A Well, I think the future is going to be on two fronts. Uh, obviously increased power generation is one way to solve the energy crunch. The other way to solve the energy crunch is by getting more at what already exists. And I don't know if you were listening to Sabine from Siemens, the CEO of Grid Software at Siemens, but the stat that caught my eye was that there's a hundred and fifty billion output a year that's lost in the US as a result of outages, right? So if we deal with those outages, and I don't know what the power consumption issues are there, but we deal with those outages, with those types of numbers, something's telling me that we've got more energy available. So how do we look at existing infrastructure and squeeze more out of existing infrastructure? How do we avoid downtime? How can we get the throughput increased on existing infrastructure and then overlay that with new power generation? And there's all sorts of ways clearly you can do that. Um, you know, introduction of new nuclear technology is obviously one that tends to be more carbon efficient. There's clearly carbon intense hydrocarbons that can be used. Uh, there's a proliferation of different things. Uh, I also feel the renewables needs more attention. Some of the technological developments with solar in particular, predominantly coming out of China, Make the cost of generating wattage for that technolog…

AI assessment note: “Well, I think the future is going to be on two fronts.”

Q I'm going to send it to someone. I'm going to trust them to get that signal accurately to The people I'm working with. The other level of trust is I'm going to trust the large language model to actually make decisions, ah, that would previously be made, made by the company. Where do you stand?

A I mean, we're not relying blindly. I mean, these things don't get into production without rigorous stress testing, uh, in all sorts of ways. Uh, one of the ways in which we think about stress testing the capability that ultimately makes decisions in the field is running millions of scenarios, because the more scenarios run and the more times you run queries, the higher probability you are getting that accurate. So, and the availability of compute allows that to happen. So I think we recognize, Anthropic recognize, you know, the job to be done, the nature of the operations. They are mission critical in nature. So we will find ways together to get the level of trust we jointly need, because our brand's on the line. Anthropic's brand will be on the line, and the nature of what we do is so significant. So it's not blind trust, but the nature of the partnership and, and, and how we are as organizations, I think, creates that environment of trust to develop in that way.

AI assessment note: “we're not relying blindly. I mean, these things don't get into production without rigorous stress testing”

Q I want to take a moment to talk a little bit about IFS, because of course there's a lot of moving parts here, right? There's the robot dog, there's the anthropic large language models, but there has to be some sort of system in the middle to route these signals to the people on the line. So talk a little bit about the role that IFS plays here.

A Yeah, what I talked about this morning at the event that we're hosting today, which we've called Industrial X, Uh, Unleashed. Industrial X Unleashed is all about what I describe as bringing the dimensions of the X, you know, the four dimensions or, or engines, as I call them, of progress and possibility. They all need to come to bear. You've got the models, you have the infrastructure and the data, you have the robotics, and then you've got the reinvention partners. We often work with partners, advisory firms, top tier consultants, because when you're changing fundamentally operations, And teams, and skills, and capabilities, with all that coming together, you have to move an organization from A to B. It doesn't happen by magic overnight. There's resistance to change, et cetera, ok? IFS has been supporting the industries we serve for decades. The entire organization is geared with understanding the intimacy of every industry we serve. And we've been developing workflow for field engineers, for asset maintenance, for ERP in these industries for over 40 years. So we've got know-how built in. We know how to orchestrate value chains. So IFS is sitting in the middle of those four engines of progress and possibility. Our platform, the application stack, it doesn't go away. Because ordinary workers in the field, they still need coherence. They still need to understand how they're expe…

AI assessment note: “IFS is sitting in the middle of those four engines of progress and possibility.”