Speaker 1: These sees. Bloomberg Business Week with Carol Messer and Tim
Speaker 1: Stentovic on Bloomberg Radio, The Whole World worry. We know,
Speaker 1: we keep quoting our conversation with Kathy Would, but you know,
Speaker 1: she's all in when it comes to innovation disruptions. Has
Speaker 1: got a new research report and it really is touching
Speaker 1: on um she's calling big ideas, but it's touching on
Speaker 1: so many things that we touch on a lot and
Speaker 1: as of late, and that includes something like artificial intelligence. Tim. Yeah,
Speaker 1: and look, I think what's interesting too is that the
Speaker 1: news that we got a little earlier today, Carol, uh,
Speaker 1: that you know, you have a series of companies continuing
Speaker 1: to invest in AI, with Google coming out and saying
Speaker 1: that it's making a big investment there. So and we
Speaker 1: feel like on all the earnings calls, like everybody, oh
Speaker 1: my god, Google yesterday, the first sentence from Sunder Pacha
Speaker 1: I was all about AI. So you know, we we
Speaker 1: we see that there's a buzz around it right now,
Speaker 1: and we see that there's this euphoria. It's led to
Speaker 1: some wild swings and stocks like Buzzfeeds C three AI.
Speaker 1: Buzzfeeds saw triple digit gains in certain days because of
Speaker 1: its association with AI. But what about when it comes
Speaker 1: to deploying AI for industrial uses. We've got a great
Speaker 1: guest with us. Alice Globus is CFO at Nanotronics. It's
Speaker 1: a company that says it uses AI to make the
Speaker 1: manufacturing process more efficient. She joins us via zoom from
Speaker 1: New York City. So, Alice, I think a lot of
Speaker 1: people are familiar with what chat gpt can do. Um.
Speaker 1: I had a friend, uh write a review for me
Speaker 1: in chat gpt and it actually was like almost good
Speaker 1: enough for me to actually use for my own self review. Yeah,
Speaker 1: it was pretty amazing. I didn't use it um, but
Speaker 1: he was tempted to use it for his own reviews
Speaker 1: that he has to has to write as we get
Speaker 1: to review season. What about when it comes to manufacturing
Speaker 1: and making the manufacturing process more efficient? What's the tech
Speaker 1: that you have at Nanotronics. Yeah, Well, just like to
Speaker 1: say thank you Carol and Tim and Bloomberg for having
Speaker 1: me here. With all the excitement about AI, a lot
Speaker 1: of people don't realize the uses that it has on
Speaker 1: actual physical things in our life. So one of the
Speaker 1: major problems with manufacturing right now is it's a very
Speaker 1: wasteful industry, and there's a lot of problems with manufacturing
Speaker 1: processes that cause everything from uh a lot of waste
Speaker 1: being manufactured, to energy usage to all these other things,
Speaker 1: sometimes human accidents that really drive the price of our
Speaker 1: goods up significantly more than we actually realize. And then
Speaker 1: there's um companies that have contamination issues that are dealing
Speaker 1: with like thailan all or baby formula that you've heard of.
Speaker 1: And this is where AI really can come in and
Speaker 1: take advantage by helping manufacturers UM optimize their systems in
Speaker 1: a way that humans just don't have the ability to
Speaker 1: do so um more because it's it's overwhelming as looking
Speaker 1: at a manufacturing facility, there's millions of things that are
Speaker 1: happening and being able to assess that and optimize the
Speaker 1: process to have the best product possible. Alice are most
Speaker 1: of manufacturing, even some of the big you know manufacturers
Speaker 1: that are at their global manufacturers aren't they doing this
Speaker 1: already though, using AI to some extent to maximize the
Speaker 1: productivity at their facilities. Yeah, Like I would say they're
Speaker 1: using what I would consider early stages of AI. What
Speaker 1: you're seeing right now is really an AI revolution that's
Speaker 1: happening what you're seeing with chat GPT. They're using a
Speaker 1: relatively cutting edge technology that allows computer to learn the
Speaker 1: way humans learned. And this is what we're doing for manufacturing.
Speaker 1: When our systems are learning like a human does, you know,
Speaker 1: they're penalized and rewarded based on what's happening they learned
Speaker 1: through observation, all based on the end goals. Was for
Speaker 1: most of earth manufacturers that's increasing their yields, but sometimes
Speaker 1: it's reducing their power consumption or other things that they're
Speaker 1: looking to achieve. One thing that we talked about with
Speaker 1: AI is inputs and outputs. What are the inputs that
Speaker 1: you use? Yeah, so it's kind of something that we
Speaker 1: do differently is we actually are not simulating what your
Speaker 1: your factor, your your facility. We actually use your real
Speaker 1: time data that's coming everything from uh, your comput your
Speaker 1: brain of your factory, which is known as a PLC,
Speaker 1: which is kind of takes all the sensors in your
Speaker 1: factory and puts it into one place and we're able
Speaker 1: to take that you know, temperature, humidity, pressure, whatever that
Speaker 1: is those sensors in most cases it's thousands and look
Speaker 1: at them to be able to optimize for the end
Speaker 1: goal of winning the game of manufacturing. So Enter Nanotronics.
Speaker 1: Tell us a little bit about your company, what you
Speaker 1: specifically do against the backdrop of this conversation we're having. Yeah,
Speaker 1: so i'd say we're the first generative AI company for manufacturing.
Speaker 1: We started with early artificial intelligence for inspection, which of
Speaker 1: identifying defects within the manufacturing process. And and that's not
Speaker 1: exactly the most sexy thing, but the reality is when
Speaker 1: you have problems in your materials, especially in industries where
Speaker 1: it's a long time to manufacture something like the semiconductor space,
Speaker 1: the sooner you can identify problems that are in your product,
Speaker 1: the quicker you could either address them in your manufacturing
Speaker 1: process or replace your supplier. Communicate with your supplier that
Speaker 1: there's a problem with that coming in. So that allows
Speaker 1: you to increase your yields and reduce your costs in
Speaker 1: the overall process. Talk to me about customers. Who do
Speaker 1: you have out there right now? You know we're working
Speaker 1: with most fortune manufacturers. We have over two customers ranging
Speaker 1: everything from biotech to semiconductor to automobile industries. How do
Speaker 1: you how do you sell it? That's a good question.
Speaker 1: You know, we've been in in an inspection for over
Speaker 1: a decade, so this is one of those things that
Speaker 1: we started with. I would say the hardest industry to penetrate,
Speaker 1: which is the UM the semiconductor space. You know that
Speaker 1: they are really more lenient to going to some of
Speaker 1: the larger manufacturers, but right now what we're seeing is
Speaker 1: that they're hitting a wall with what can be physically
Speaker 1: done by hardware, and the only way to overcome this
Speaker 1: is really through artificial intelligence. It allows our customers to
Speaker 1: able to do predictive maintenance, to actually have real time
Speaker 1: feeds from supply chain UM distribution like their EARP systems
Speaker 1: such as SAP or one of those systems, to change
Speaker 1: their process based on shipment delays or even people that
Speaker 1: are interfering or you know, fatigue that's coming into the process.
Speaker 1: So these are things that we're able to take into
Speaker 1: account and help optimize. You know, Alice, I kind of
Speaker 1: keep thinking, we've been talking about AI for years. This
Speaker 1: isn't new, it's been around since the nineteen fifties. But
Speaker 1: I do wonder you you know, and you mentioned generative AI,
Speaker 1: which is this idea of generating novel content right like
Speaker 1: chat GPT. Was there something that has happened in the
Speaker 1: last year or so that all of a sudden we're
Speaker 1: talking about AI and rightfully? So I just want to
Speaker 1: make sure that our level of um focusing on it.
Speaker 1: I mean, we see companies obviously doing big deals like Microsoft,
Speaker 1: and we see Google doing a much smaller deal, but
Speaker 1: nonetheless these are big names involved in it. But I mean,
Speaker 1: are we rightfully focusing on it right now? Because there's
Speaker 1: some new development that has made it much more useful
Speaker 1: in our world. So, actually, the big breakthrough in some
Speaker 1: of this generative AI technology happened in and I think
Speaker 1: why it's taken so long to actually get into the
Speaker 1: mainstream is that there's been a lot of R and
Speaker 1: D that that's surrounding it. And it's honestly a combination
Speaker 1: of human acceptance of AI and willing to take the
Speaker 1: chance of giving over control to a black box system.
Speaker 1: And that you mean in the corporate world right when
Speaker 1: you talk about corporate world for yeah, and the corporate
Speaker 1: world for sure, and then you know, coming with with
Speaker 1: AI for chat CHYPT. These techniques have been developing since
Speaker 1: seen there was a scientific paper that it really stems
Speaker 1: from this, But you know, there's been advances in speed
Speaker 1: and internet uh speed connectivity. These things also help increase
Speaker 1: adoption of AI within just a social setting. Alright, we
Speaker 1: only have forty seconds left here. What was it like
Speaker 1: to work with Neil de grasse Tyson? Just quickly? Which
Speaker 1: you did do you're an astrophysicist, just quickly? What was
Speaker 1: it like? You know, the it changed my life. I
Speaker 1: always say that everyone should encourage everyone to get their
Speaker 1: PhD in astrophysics because it shows that, you know, problem
Speaker 1: is too small to fix. Um. You know, we're trying
Speaker 1: to solve some of the world, the universe's largest problems.
Speaker 1: And when I look at you know, something like manufacturing
Speaker 1: and be able to have carbon negative manufacturing facilities across
Speaker 1: the world being optimized through it actually seems like an
Speaker 1: attainable future that we can we can do. And you know,
Speaker 1: it was definitely an incredible experience. Well. I love the optimism,
Speaker 1: uh and I like the idea that no problem is insurmountable.
Speaker 1: So um, really a great way to start to wrap
Speaker 1: up our Friday. Alice, thank you so much. Alice Globe
Speaker 1: is Chief financial Officer Antotronics via zoom from New York City,