How AI Can Make Manufacturing More Efficient

as of late, and that includes something like artificial intelligence. Tim. Yeah, and look, I think what's interesting too is that the news that we got a little earlier today, Carol, uh, that you know, you have a series of companies continuing to invest in AI, with Google coming out and saying that it's making a big investment there. So and we feel like on all the earnings calls, like everybody, oh my god, Google yesterday, the first sentence from Sunder Pacha

I was all about AI. So you know, we we we see that there's a buzz around it right now, and we see that there's this euphoria. It's led to some wild swings and stocks like Buzzfeeds C three AI. Buzzfeeds saw triple digit gains in certain days because of its association with AI. But what about when it comes to deploying AI for industrial uses. We've got a great guest with us. Alice Globus is CFO at Nanotronics. It's a company that says it uses AI to make the

manufacturing process more efficient. She joins us via zoom from New York City. So, Alice, I think a lot of people are familiar with what chat gpt can do. Um. I had a friend, uh write a review for me in chat gpt and it actually was like almost good enough for me to actually use for my own self review. Yeah, it was pretty amazing. I didn't use it um, but he was tempted to use it for his own reviews that he has to has to write as we get to review season. What about when it comes to manufacturing

and making the manufacturing process more efficient? What's the tech that you have at Nanotronics. Yeah, Well, just like to say thank you Carol and Tim and Bloomberg for having me here. With all the excitement about AI, a lot of people don't realize the uses that it has on

actual physical things in our life. So one of the major problems with manufacturing right now is it's a very wasteful industry, and there's a lot of problems with manufacturing processes that cause everything from uh a lot of waste being manufactured, to energy usage to all these other things, sometimes human accidents that really drive the price of our

goods up significantly more than we actually realize. And then there's um companies that have contamination issues that are dealing with like thailan all or baby formula that you've heard of.

And this is where AI really can come in and take advantage by helping manufacturers UM optimize their systems in a way that humans just don't have the ability to do so um more because it's it's overwhelming as looking at a manufacturing facility, there's millions of things that are happening and being able to assess that and optimize the

process to have the best product possible. Alice are most of manufacturing, even some of the big you know manufacturers that are at their global manufacturers aren't they doing this already though, using AI to some extent to maximize the productivity at their facilities. Yeah, Like I would say they're using what I would consider early stages of AI. What you're seeing right now is really an AI revolution that's

happening what you're seeing with chat GPT. They're using a relatively cutting edge technology that allows computer to learn the way humans learned. And this is what we're doing for manufacturing. When our systems are learning like a human does, you know, they're penalized and rewarded based on what's happening they learned

through observation, all based on the end goals. Was for most of earth manufacturers that's increasing their yields, but sometimes it's reducing their power consumption or other things that they're looking to achieve. One thing that we talked about with AI is inputs and outputs. What are the inputs that you use? Yeah, so it's kind of something that we do differently is we actually are not simulating what your

your factor, your your facility. We actually use your real time data that's coming everything from uh, your comput your brain of your factory, which is known as a PLC, which is kind of takes all the sensors in your factory and puts it into one place and we're able to take that you know, temperature, humidity, pressure, whatever that is those sensors in most cases it's thousands and look at them to be able to optimize for the end goal of winning the game of manufacturing. So Enter Nanotronics.

Tell us a little bit about your company, what you specifically do against the backdrop of this conversation we're having. Yeah, so i'd say we're the first generative AI company for manufacturing. We started with early artificial intelligence for inspection, which of

identifying defects within the manufacturing process. And and that's not exactly the most sexy thing, but the reality is when you have problems in your materials, especially in industries where it's a long time to manufacture something like the semiconductor space, the sooner you can identify problems that are in your product, the quicker you could either address them in your manufacturing process or replace your supplier. Communicate with your supplier that

there's a problem with that coming in. So that allows you to increase your yields and reduce your costs in the overall process. Talk to me about customers. Who do you have out there right now? You know we're working with most fortune manufacturers. We have over two customers ranging everything from biotech to semiconductor to automobile industries. How do you how do you sell it? That's a good question.

You know, we've been in in an inspection for over a decade, so this is one of those things that we started with. I would say the hardest industry to penetrate, which is the UM the semiconductor space. You know that they are really more lenient to going to some of the larger manufacturers, but right now what we're seeing is that they're hitting a wall with what can be physically done by hardware, and the only way to overcome this

is really through artificial intelligence. It allows our customers to able to do predictive maintenance, to actually have real time feeds from supply chain UM distribution like their EARP systems such as SAP or one of those systems, to change their process based on shipment delays or even people that are interfering or you know, fatigue that's coming into the process. So these are things that we're able to take into account and help optimize. You know, Alice, I kind of

keep thinking, we've been talking about AI for years. This isn't new, it's been around since the nineteen fifties. But I do wonder you you know, and you mentioned generative AI, which is this idea of generating novel content right like chat GPT. Was there something that has happened in the last year or so that all of a sudden we're talking about AI and rightfully? So I just want to make sure that our level of um focusing on it.

I mean, we see companies obviously doing big deals like Microsoft, and we see Google doing a much smaller deal, but nonetheless these are big names involved in it. But I mean, are we rightfully focusing on it right now? Because there's some new development that has made it much more useful in our world. So, actually, the big breakthrough in some of this generative AI technology happened in and I think why it's taken so long to actually get into the mainstream is that there's been a lot of R and

D that that's surrounding it. And it's honestly a combination of human acceptance of AI and willing to take the chance of giving over control to a black box system. And that you mean in the corporate world right when you talk about corporate world for yeah, and the corporate world for sure, and then you know, coming with with

AI for chat CHYPT. These techniques have been developing since seen there was a scientific paper that it really stems from this, But you know, there's been advances in speed and internet uh speed connectivity. These things also help increase adoption of AI within just a social setting. Alright, we only have forty seconds left here. What was it like to work with Neil de grasse Tyson? Just quickly? Which you did do you're an astrophysicist, just quickly? What was

it like? You know, the it changed my life. I always say that everyone should encourage everyone to get their PhD in astrophysics because it shows that, you know, problem is too small to fix. Um. You know, we're trying to solve some of the world, the universe's largest problems. And when I look at you know, something like manufacturing and be able to have carbon negative manufacturing facilities across the world being optimized through it actually seems like an

attainable future that we can we can do. And you know, it was definitely an incredible experience. Well. I love the optimism, uh and I like the idea that no problem is insurmountable. So um, really a great way to start to wrap up our Friday. Alice, thank you so much. Alice Globe is Chief financial Officer Antotronics via zoom from New York City,