What is AI & Why the Hype?

Are you skeptical about AI? Do you think AI is just ChatGPT? Are you wondering what AI has to do with Customer Success? In this session we will cover what AI is, why you should care about it, and what you should do with it.

Spoiler Alert:

AI is a transformational technology on the scale of automobiles, planes, radio, television, internet, and mobile. The hype is because it has started to "hockey stick". If you haven't thought about it or started to dig in on AI yet, NOW is the time to pay attention and get involved.

Speaker

Jan Young - Founder & Chief Customer Officer at JanYoungCX

LinkedIn

Watch What is AI & Why the Hype?

‍Transcript

This transcript was created by AI. If you see any mistakes, please let us know at marketing@matik.io.

Matik MC: Okay. For those of you just joining you are currently watching what is AI and why the hype will get started in just a moment, letting a few people filter in.

Matik MC: Okay. Let's get started. I'm excited to introduce our speaker. And as I introduce her, I'm also gonna have her answer our ice breaker question. What would you use AI to automate in your life outside of work? So again super excited we have here Jan Young, founder and chief customer officer of Jan young CX.

Jan Young: Hi. How are you doing? Thank you so much for having me. So, you know, I do a lot of, the cooking and we're a vegan and my husband is alerted to so, and he can't eat cilantro, and that really complicates things. So, I'm constantly looking for, you know, new recipes and it's really hard when you're just trying to search online. And I love how AI especially using being makes it much easier. I still have to give Bing feedback because sometimes it'll still give me a curry is another thing he can eat. So like there's still like some feedback I'm having to give it, but it learns and so I'm really thankful for that.

Matik MC: I love that idea. I would definitely sign up if that was available.

Jan Young: It is, it is, use it now.

Matik MC: Before we start the session, just a reminder to everyone if you have any questions for Jan, go ahead and open up the Zoom control bar. You'll see the Q and a functionality. So drop your questions in there for her. Okay? Now, hand it over to Jan.

Jan Young: Thank you. All right. And while I get started, I have my LinkedIn ready to go. So I want everyone to put your LinkedIn and go and find it, go get it, put your LinkedIn. I'm gonna go ahead and start sharing my screen and getting started. But this is something that we do at CS office hours regularly and make certain that people are connected. And I wanna be sure that we're connecting here as well. So in terms of the session today, and the title, you know, what is AI, why the hype? And I wanted to be sure that we took some time to actually look under the hood and really understand what AI is. Because if you understand what it's good at a and what kinds of problems it's good at solving, then you can really use the tool to your maximum benefit. And so that's what I thought would be helpful because we have so many great ideas to day about how to use it, but why, and what, and, you know, how are you using it? And, and I do believe that we've hit this place where we are now at just the hockey stick, right? Like this is where it's really taking off. This is the time to pay attention to and to be sure that you're you know, getting engaged, and using AI and all of its forms because it is a transformational technology. So just briefly about myself as you heard, I'm the founder and chief customer officer of Janine, CX. I lead weekly CS office hours and a slack community which I can share more information with you about that. At the end, I'm also working on building some courses. My expertise is on the business side, but I'm really like a moth to flame. I love emerging and tech. IMOG I've been around since dot com days and I just believe that it's always important to be on the cutting edge, of tech. So I really wanna be sure that by the end of this session that you'll agree with me, and jump in as well. One last disclaimer is if I don't know something I'm gonna tell you that I'm not hallucinating like ChatGPT. So I think that's really important to also recognize and to do as leaders but also, to recognize when tools can help us, and, when maybe they're not helping us in the way that we expect or need. So setting those expectations, okay? So I wanna be sure that by the end of this, you not only have a better idea of how to help your, you know, how to use AI, what it is and reconsider kind of what you might want to do with AI once you under stand it as a technology better so that you can use help your customers help your company. And, and also actually, there are tools being built that can actually really help your career, right? So we'll talk about all of those things. And first though I wanna start actually with providing some context. And I know we're kinda going back when we're looking as far back as the late eighteenth and early nineteenth century, but we really, we were in the fourth industrial revolution right now. We're in it to a T. And I think it's helpful to have some context especially to sort of dispel some of the fear around it. So first in the chat, I wanna ask… I wanna ask you what, you know, in terms of steam power, what impact did steam power have on the way people lived and worked, and what types of businesses there were, you know, what sort of thought huh? Do you have about steam power? I'm not seeing anything in the chat, just give it your best guess. You don't need to use ChatGPT for this. You can just give me your best idea. Steam power, chat, come on, transportation advancements. Thank you. Sheldon trains. All of a sudden could go across continents. They couldn't do that before they were using, you know, horses, and walking literally walking across the continent right? Before that. Also factories didn't have factories before steam power enabled factories. There was a lot of fear around that, right? But all of this stuff changed how we worked, and how we traveled, even how we could connect, and where we could live. When you think about the second industrial revolution, motor engine in electricity, telecommunication, thinking about that, you know, when we're moving from, you know, horses and walking to cars, what sort of infrastructure, was created to support that? Any thoughts on that? Put it in the chat highways absolutely. What about motels and hotels, vacations, even right? When you think about it, before people could fly or drive, there weren't there wasn't a need for motels and hotels. So like really expand out. Like when you think about industrial revolutions, the impact of it is beyond what you initially would think of when you think about infrastructure that supports all of that, right? When do you think the first computer was introduced? In which of these four industrial revolutions… thoughts? Steam? Okay. All right. What other, what other thoughts? So we did have analog ways to compute, right? We did have, but steam didn't necessarily impact it. But that was a great guess. Electricity. However, yes, early twentieth century electricity had an impact because that's when you had transitions and transitions were big. So the first computers took up rooms, right? So IBM owned it. The government owned it, right? So when you think about that, when you take a look at the late twentieth century, when then we had chips, right? I chips that enable to have laptops on a desk, where now I'm looking at you right now, right? And all of a sudden you have improvements in the interfaces, in the PC'S, and you could have actually smaller chips made it. So you could have a laptop, you could take your laptop on the go. You can use an iPad or, you know, other devices like that. Internet allowed for e-mail instead of snail mail, right? Which is what we call it now, right? So you think about these changes now, mobile, when we have our phones, right? We have a computer in our hands, that makes the big difference, right? So when you think about, the way that it has transformed things, did we lose jobs? Do we have fewer black smiths now? Because we are using cars instead of courses? Absolutely? But think about all of the jobs that are different, that have been created, right? In the same way jobs change, you can be fear about it or you can embrace it and be on that cutting edge with it, right? So when you think about then the fourth industrial revolution, some of the stuff you're like robotics, well, you know, they've had, you know, robots, in factories and that sort of thing already. So, you know, internet of things fit bit right here, right? This is something that we already use. I refer to Siri, because I'm in a G household. And if I say G out loud, my lights might shut down. But when you think about all these things that we're already in, when you think about blockchain, it's not being used very much yet. It's just crypto. A, but when you think about, we have been using digital money forever. It's not like you get paid with a bunch of money, in a suit case and go and put it under your bed, right? We've had digital money for some time. So, all of these ways in which we're going to have more efficient and safe means of using all of this digital content that we create every day, right? We'll be digging into artificial intelligence, something that you probably haven't thought about much yet. But quantum computing, when everything goes, instead of being from digital to atomic computing, and it goes from the ones in zeros of digital, when we get. To quantum computing where you can have many states at once using and the, that's also in cubes, is what you'll be hearing about. Then all of a sudden, when you're trying to analyze mounds and mounds of data, right? You can analyze it all at once in, you know, simultaneously traffic will be much easier to work out a because you will, you'll have all of the roots analyzed at once whether will be something that will be much more accurate when you're predicting that because all of that data that goes into that will be analyzed so that you'll be much more accurate, right? And that's what happens, when you have changes like this when we're in the fourth industrial revolution. So now, I want you to think more specifically about why the hockey stick is happening for AI when it hasn't happened for some of these other things quite yet. So, what's changed? You have large data sets that we're talking about, right? All of the stuff that's creating data through the internet. You have cloud. We have jobs in saas tech because we're using the cloud for efficient and economical computing, right? And so when you think about that, the cloud has had an impact, advances in deep learning where you're looking at, a transfer transformer architecture which you don't have to worry about the details of it. But you do need to understand that when their advance is like that and vector databases, you'll also hear about when you hear about those things, what you'll understand is that this is what is enabled, things like pre trained models like ChatGPT being barred cloud, all of these things right now for business is going to be able to use it more easily because either they're going to connect to the API of those commercial models or like you've probably heard of GitHub. If you work in tech hugging face will be sort of, the GitHub of AI, right? That's how it looks like it's shaping out to be. And so when you think about the open source models that you'll be able to use to train your, data is going to be key in everything we do forward, how, what data you're using, what data pool, the way you're training, it will be sort of your advantage, right? So you want to start thinking about all of these things that are leading to the tipping point, and why AI is taking off in a hockey stick. So this is not a time to sort of sit back and say, I'm not sure this is a time to jump in this is a time to realize like it is taking off your career will benefit if you understand AI and you know how to use it. So let's keep going. So what is AI? You know, when you think about how it is simulating human intelligence? We've been using… we've been using why can I think of the word right now all of a sudden? But we've been using not analog. We've been anyway, we've been using the way, you program. We always get upset with the word I'm looking for is the backbone of AI and I can't think of anyway, don't worry about it. So, we've been programming in as human first programming for a while. The difference, is when we get to machine learning, right? When we get to machine learning. Now, the actual model is training itself and improving upon itself. Then when you think of, deep learning is actually using artificial neural networks, right? So it can go way more complex problem solving because it's mimicking how our own brains work. Our brains are amazing what they're able to compute, and computers are starting to use some of those same approaches, right? When you look at gen AI or generative AI, what that's doing now is not only training itself, it's now and it's not just predicting an answer. It's generating, right? That's why when you go to ChatGPT and you're saying improve this e-mail, it can generate something new, right? So that is, does anybody know which one of these initials here in the orange box? Which one is ChatGPT, is it gas or llmanybody? Gas? Or LM? It's actually LLM is large language model. Thank you, Roberta. But I'm glad everyone else is giving it a try because the large language models or what is you're sort of training for, you know, generating the output, right? And so you put in something and it's been trained on a bunch of data and based on your input, now, it's out putting something new. It's generating something new, right? Gas actually gas stands for generative adversarial networks. Still doesn't help. But what it really is this is deep fix because what it's doing is it's well, it can be deep fix but it, but it's generating images, right? So this is how you can go over and say, hey, give me a logo. I want the following things or, you know, and here's some colors I want to use. You can also use it in any of these things that we're doing. You can use it for bad or good so that's where you're also seeing some deep banks where all of a sudden audio and visual or video images can be created, and it looks like, wow, I didn't know that Jan knew how to speak in French fluently well, I don't but it was able to mimic it, mimic me and have me speak in French. So that's actually a great business use unless you have me participating in some sort of French conversation that I wouldn't normally participate in, right? So those kinds of things, right? Funny, I just came up with the French example but anyway come up with your own ideas at home. So how is AI being used? We've kind of heard throughout the day. You know, I can already, if you go to being, it is using the current internet and so you can come up with travel itineraries with, you know, all the things that, are your requirements and what dates you're going to be there and all those kinds of things. And it can pull from the internet and come up with travel itineraries, the recipes that I'm pulling, right workouts or what, you know, what you should be making for the next week, you know, things like that. If you only have certain things in your refrigerator and you're not sure what to make with it, you can put that in a and get some various ideas back. Now, when you're using something like ChatGPT, perhaps you've heard, but that's only information going up to 2021. So that can still be pretty good for recipes. But if there's any new recipes that have been coming out in the last couple of years, you're gonna miss out. So think about what all of these tools are out there and what their limitations are, and what their, what opportunities they give you, right? When you think about eCommerce, so personalized shopping, anybody use stitch fix back in the day when you have to go to the office, maybe use stitch fix. So that is using AI to personalize your shop shopping, right? When you think about, yeah, I love it too when you think about to like search. So home depot, I don't know if you ever have tried to find something on home depot, but like many types of search in the past, if you do a search and as I, yeah, I said fan, but now you're giving me all these other fans that I don't need because it's just giving you the most popular search. If you need a slope ceiling fan now? Because they are using a vector database using, a, no, it will return first the fans that you need for a slope ceiling that's the improvement they made. Now people are staying on their site longer and more likely to buy. That has then the implications for revenue, right? And, and to, and it gives them an edge over someone other than home depot. That maybe hasn't done that when you look at medicine and science, when you literally think about how AI in the past, the machine learning AI before it got into deep learning at first got trained on pong and chess and go literally. And one of the resources I have, is a podcast about is fantastic. But literally, they use the training they did with go which was more deep learning training. And then they were able to map out product. Excuse me, pro team folding now, pro team folding is literally mapping out the, pro teams are the basis of any organic material to a. And so when you take a look at that, we were, they were able to then map out literally everything people food plans, viruses, right? So when we got to COVID 19, they could very quickly map what the pro teams were and that's when you saw those little spiky things on a ball that's that was literally the pro team that you're looking at and that helps them so quickly come up with a vaccine that would just attach to that COVID 19 pro team and then be able to take it out of your system. That's literally, why AI is already having an impact on things that we are impact or every day, right? So when you're looking at that also when you think about it in the past, if you needed to use AI, you would have to go and hire like a python code or something like that. But you're not going to do that to generate a better e-mail. Okay, python coder, please, you know, like why would you do that? But now when you have something like ChatGPT and these other things around now, when you put in improve this e-mail all, you can do it in English. You just now for now you're having to work on how to improve a prompt. And if you're paying for the subscription version, chat out there's, a plugin that will help you improve your prompt or if you're over in CS office hours, we have AI and CS channel where you can ask people like, hey, here's, some prompts, what, you know, here. Do you have any ideas on this, right? Exactly. You, do you have a robot friend in your pocket at all times? And it's available, on your phone, right? So when you think about that, the other thing though that you may not be thinking about is apis and data matching. Not only for the tools that you're using, in your own company because you can now get much more improved data matching and then just focused focus on where the problems are and clean up, you know, those areas of data when you can do that. But also a POS API that can help your customers connect more easily, say look at to tango that's something that they announced a while back, they're using Jasper AI for that. But also when you just think about, I saw a tool, a new CS platform tool on Monday. Literally, you can talk into it. And if you wanna make any changes, you can type those in. And literally, it will connect you in like 20 minutes to all of you to all of your other platforms that you need to feed in. So, you know, that sort of thing, right? So there's all of these things are enabled. Because now generative AI, is helping you speak to these apps, and platforms. And, and it can identify what you're saying, show you what you're saying, allow you to input new information that is gonna in the mix. Already. Now, the way you can think about this is very different, right? So it's not just for an e-mail but it's these practical ways that you will improve your customers, lives, your company, your own life, all of these ways. When you're thinking about though, how you're going to use it in your CS program, I want you to think more specifically about what's going to have the biggest priority, what's the biggest impact go for, the biggest impact that AI can improve upon. So when you think about all the ways it's can analyze data or, you know, make things improved upon. Then you wanna think about what's going to have the biggest impact scaling customer success. You don't really hear a lot about personalization at scale, but you should, and you will because that is something that where AI can actually pull in all of the recordings, all of the emails, all the productivity, pull it in and understand for each person. When was the last time they logged in? What sort of persona is this? Did they just come back from the vacation, all of these kinds of things? Then it can help generate that in an e-mail or reach out in your app, things like that. So maybe it's not quite there yet but it will be, and you should start to imagine it and ask for it or build it. Yourself, yes, we're getting pretty close here. So all of these different kinds of things. I'll let you sort of dig into it but think about how you can already people are improving their customer journeys by putting that into an analyzer and getting feedback even in ChatGPT. You can do that… when you look at next steps. Yes, you wanna learn the tools. Yes, you wanna be curious. You are the human. Your emotional intelligence is something that AI doesn't have that's really critical. But also I wanna call attention that you need to know your craft, right? You need to be the guide to AI. So if you're asking something it's it might hallucinate if it doesn't know the answer you have to understand, is it hallucinating, you need to be able to evaluate? Is this information good or not, right? And so because of that, you need to step up, it's really critical right now. And so that's also affects all of the resources that I've added in the, a lot of books. But it's worth it to a, when you look at the types of tools. The main thing I wanna talk to you about is intelligence CS platforms. Increasingly, you're going to see intelligent platforms, that are using AI, at its core. Things like lantern and data plan. Also really impressive already seeing how catalyst and smart carrot have been incorporating. And of course Matik is part of the customer intelligence category here. But let's go ahead and share the links to the slide. So people have all of these things. I do wanna caution folks that, you know, it's not just garbage in garbage out and the data limitations. You've also heard about the difference between public and private AI systems and hallucinate hallucinations, but also think about ethics. And if you're using it for good or bad. And then also thinking about bias, we have an article that in the resources that talk about bias, you wanna think too about if the bias that is, that has been programmed or trained because of the data pool that it's being trained on. If there's bias inherent in what you're creating with AI. Okay, really quickly, you'll see all the different resources and also feel free. There's more resources in community at CS office hours, and this is how to connect. And now we can answer questions for about three minutes. Sorry about that. I knew I was gonna go over.

Matik MC: No worries. And yeah, if we don't get to your question, don't worry. We'll pass it along to jam so that she can answer after the session. Yeah, let's start with this one. You mentioned being aware of ethics and by season AI, how do I guide my team in terms of how to deal with it and minimize it when using AI tools?

Jan Young: That's a great question. The first thing you want to be sure to do is try and have a diverse team to begin with. It's really important that you have different perspectives and different lived experiences, right? And then if you haven't diversified your team yet, then take the time to read about all these different perspectives, right? So that at least you can be more open to it because you want to think about, what have, what am I missing? Right? As a white woman, what other different perspectives or as someone who's always worked in tech, what other perspectives am I missing? You can also do more customer interviews, and think also about doing interviews with your target customer base as well. That can also help to give you some insights.

Matik MC: Some, thank you so much, Jan. And with that, we are at the end of our session, like I mentioned before, I know there are some questions that have come through. We'll pass it along to Jan, so you will get the answers. Keep an eye out in your e-mail when the recording and the additional Q and a is live in our resource hub. We will let you know again. Thank you so much Jan. This is such an educational session for a lot of us and thank you to everyone else for attending. Great.

Jan Young: Thanks a lot.

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