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Speaker 1: These sees. Bloomberg Business Week with Carol Messer and Tim

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Speaker 1: Stentovic on Bloomberg Radio, The Whole World worry. We know,

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Speaker 1: we keep quoting our conversation with Kathy Would, but you know,

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Speaker 1: she's all in when it comes to innovation disruptions. Has

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Speaker 1: got a new research report and it really is touching

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Speaker 1: on um she's calling big ideas, but it's touching on

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Speaker 1: so many things that we touch on a lot and

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Speaker 1: as of late, and that includes something like artificial intelligence. Tim. Yeah,

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Speaker 1: and look, I think what's interesting too is that the

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Speaker 1: news that we got a little earlier today, Carol, uh,

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Speaker 1: that you know, you have a series of companies continuing

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Speaker 1: to invest in AI, with Google coming out and saying

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Speaker 1: that it's making a big investment there. So and we

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Speaker 1: feel like on all the earnings calls, like everybody, oh

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Speaker 1: my god, Google yesterday, the first sentence from Sunder Pacha

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Speaker 1: I was all about AI. So you know, we we

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Speaker 1: we see that there's a buzz around it right now,

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Speaker 1: and we see that there's this euphoria. It's led to

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Speaker 1: some wild swings and stocks like Buzzfeeds C three AI.

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Speaker 1: Buzzfeeds saw triple digit gains in certain days because of

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Speaker 1: its association with AI. But what about when it comes

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Speaker 1: to deploying AI for industrial uses. We've got a great

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Speaker 1: guest with us. Alice Globus is CFO at Nanotronics. It's

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Speaker 1: a company that says it uses AI to make the

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Speaker 1: manufacturing process more efficient. She joins us via zoom from

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Speaker 1: New York City. So, Alice, I think a lot of

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Speaker 1: people are familiar with what chat gpt can do. Um.

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Speaker 1: I had a friend, uh write a review for me

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Speaker 1: in chat gpt and it actually was like almost good

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Speaker 1: enough for me to actually use for my own self review. Yeah,

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Speaker 1: it was pretty amazing. I didn't use it um, but

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Speaker 1: he was tempted to use it for his own reviews

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Speaker 1: that he has to has to write as we get

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Speaker 1: to review season. What about when it comes to manufacturing

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Speaker 1: and making the manufacturing process more efficient? What's the tech

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Speaker 1: that you have at Nanotronics. Yeah, Well, just like to

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Speaker 1: say thank you Carol and Tim and Bloomberg for having

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Speaker 1: me here. With all the excitement about AI, a lot

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Speaker 1: of people don't realize the uses that it has on

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Speaker 1: actual physical things in our life. So one of the

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Speaker 1: major problems with manufacturing right now is it's a very

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Speaker 1: wasteful industry, and there's a lot of problems with manufacturing

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Speaker 1: processes that cause everything from uh a lot of waste

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Speaker 1: being manufactured, to energy usage to all these other things,

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Speaker 1: sometimes human accidents that really drive the price of our

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Speaker 1: goods up significantly more than we actually realize. And then

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Speaker 1: there's um companies that have contamination issues that are dealing

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Speaker 1: with like thailan all or baby formula that you've heard of.

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Speaker 1: And this is where AI really can come in and

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Speaker 1: take advantage by helping manufacturers UM optimize their systems in

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Speaker 1: a way that humans just don't have the ability to

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Speaker 1: do so um more because it's it's overwhelming as looking

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Speaker 1: at a manufacturing facility, there's millions of things that are

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Speaker 1: happening and being able to assess that and optimize the

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Speaker 1: process to have the best product possible. Alice are most

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Speaker 1: of manufacturing, even some of the big you know manufacturers

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Speaker 1: that are at their global manufacturers aren't they doing this

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Speaker 1: already though, using AI to some extent to maximize the

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Speaker 1: productivity at their facilities. Yeah, Like I would say they're

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Speaker 1: using what I would consider early stages of AI. What

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Speaker 1: you're seeing right now is really an AI revolution that's

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Speaker 1: happening what you're seeing with chat GPT. They're using a

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Speaker 1: relatively cutting edge technology that allows computer to learn the

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Speaker 1: way humans learned. And this is what we're doing for manufacturing.

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Speaker 1: When our systems are learning like a human does, you know,

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Speaker 1: they're penalized and rewarded based on what's happening they learned

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Speaker 1: through observation, all based on the end goals. Was for

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Speaker 1: most of earth manufacturers that's increasing their yields, but sometimes

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Speaker 1: it's reducing their power consumption or other things that they're

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Speaker 1: looking to achieve. One thing that we talked about with

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Speaker 1: AI is inputs and outputs. What are the inputs that

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Speaker 1: you use? Yeah, so it's kind of something that we

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Speaker 1: do differently is we actually are not simulating what your

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Speaker 1: your factor, your your facility. We actually use your real

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Speaker 1: time data that's coming everything from uh, your comput your

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Speaker 1: brain of your factory, which is known as a PLC,

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Speaker 1: which is kind of takes all the sensors in your

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Speaker 1: factory and puts it into one place and we're able

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Speaker 1: to take that you know, temperature, humidity, pressure, whatever that

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Speaker 1: is those sensors in most cases it's thousands and look

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Speaker 1: at them to be able to optimize for the end

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Speaker 1: goal of winning the game of manufacturing. So Enter Nanotronics.

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Speaker 1: Tell us a little bit about your company, what you

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Speaker 1: specifically do against the backdrop of this conversation we're having. Yeah,

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Speaker 1: so i'd say we're the first generative AI company for manufacturing.

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Speaker 1: We started with early artificial intelligence for inspection, which of

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Speaker 1: identifying defects within the manufacturing process. And and that's not

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Speaker 1: exactly the most sexy thing, but the reality is when

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Speaker 1: you have problems in your materials, especially in industries where

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Speaker 1: it's a long time to manufacture something like the semiconductor space,

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Speaker 1: the sooner you can identify problems that are in your product,

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Speaker 1: the quicker you could either address them in your manufacturing

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Speaker 1: process or replace your supplier. Communicate with your supplier that

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Speaker 1: there's a problem with that coming in. So that allows

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Speaker 1: you to increase your yields and reduce your costs in

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Speaker 1: the overall process. Talk to me about customers. Who do

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Speaker 1: you have out there right now? You know we're working

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Speaker 1: with most fortune manufacturers. We have over two customers ranging

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Speaker 1: everything from biotech to semiconductor to automobile industries. How do

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Speaker 1: you how do you sell it? That's a good question.

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Speaker 1: You know, we've been in in an inspection for over

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Speaker 1: a decade, so this is one of those things that

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Speaker 1: we started with. I would say the hardest industry to penetrate,

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Speaker 1: which is the UM the semiconductor space. You know that

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Speaker 1: they are really more lenient to going to some of

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Speaker 1: the larger manufacturers, but right now what we're seeing is

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Speaker 1: that they're hitting a wall with what can be physically

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Speaker 1: done by hardware, and the only way to overcome this

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Speaker 1: is really through artificial intelligence. It allows our customers to

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Speaker 1: able to do predictive maintenance, to actually have real time

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Speaker 1: feeds from supply chain UM distribution like their EARP systems

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Speaker 1: such as SAP or one of those systems, to change

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Speaker 1: their process based on shipment delays or even people that

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Speaker 1: are interfering or you know, fatigue that's coming into the process.

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Speaker 1: So these are things that we're able to take into

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Speaker 1: account and help optimize. You know, Alice, I kind of

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Speaker 1: keep thinking, we've been talking about AI for years. This

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Speaker 1: isn't new, it's been around since the nineteen fifties. But

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Speaker 1: I do wonder you you know, and you mentioned generative AI,

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Speaker 1: which is this idea of generating novel content right like

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Speaker 1: chat GPT. Was there something that has happened in the

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Speaker 1: last year or so that all of a sudden we're

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Speaker 1: talking about AI and rightfully? So I just want to

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Speaker 1: make sure that our level of um focusing on it.

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Speaker 1: I mean, we see companies obviously doing big deals like Microsoft,

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Speaker 1: and we see Google doing a much smaller deal, but

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Speaker 1: nonetheless these are big names involved in it. But I mean,

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Speaker 1: are we rightfully focusing on it right now? Because there's

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Speaker 1: some new development that has made it much more useful

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Speaker 1: in our world. So, actually, the big breakthrough in some

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Speaker 1: of this generative AI technology happened in and I think

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Speaker 1: why it's taken so long to actually get into the

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Speaker 1: mainstream is that there's been a lot of R and

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Speaker 1: D that that's surrounding it. And it's honestly a combination

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Speaker 1: of human acceptance of AI and willing to take the

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Speaker 1: chance of giving over control to a black box system.

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Speaker 1: And that you mean in the corporate world right when

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Speaker 1: you talk about corporate world for yeah, and the corporate

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Speaker 1: world for sure, and then you know, coming with with

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Speaker 1: AI for chat CHYPT. These techniques have been developing since

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Speaker 1: seen there was a scientific paper that it really stems

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Speaker 1: from this, But you know, there's been advances in speed

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Speaker 1: and internet uh speed connectivity. These things also help increase

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Speaker 1: adoption of AI within just a social setting. Alright, we

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Speaker 1: only have forty seconds left here. What was it like

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Speaker 1: to work with Neil de grasse Tyson? Just quickly? Which

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Speaker 1: you did do you're an astrophysicist, just quickly? What was

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Speaker 1: it like? You know, the it changed my life. I

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Speaker 1: always say that everyone should encourage everyone to get their

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Speaker 1: PhD in astrophysics because it shows that, you know, problem

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Speaker 1: is too small to fix. Um. You know, we're trying

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Speaker 1: to solve some of the world, the universe's largest problems.

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Speaker 1: And when I look at you know, something like manufacturing

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Speaker 1: and be able to have carbon negative manufacturing facilities across

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Speaker 1: the world being optimized through it actually seems like an

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Speaker 1: attainable future that we can we can do. And you know,

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Speaker 1: it was definitely an incredible experience. Well. I love the optimism,

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Speaker 1: uh and I like the idea that no problem is insurmountable.

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Speaker 1: So um, really a great way to start to wrap

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Speaker 1: up our Friday. Alice, thank you so much. Alice Globe

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Speaker 1: is Chief financial Officer Antotronics via zoom from New York City,