Predictions for AI in 2024

This transcript was created using AI tools and is not a verbatim, word-for-word transcript of the episode. Please forgive any errors or omissions from the finished product.

Courtney: [00:00:00] What does 2024 have in store when it comes to AI? What would Moore’s Law for AI look like?

And is it really possible that less than 4% of companies are using AI to produce goods and services? Hi, I’m Courtney Baker and this is AI Knowhow Podcast from Knownwell, helping you reimagine your business in the AI era.

As always, I’m joined by Knownwell CEO David DeWolf and Chief Strategy Officer Pete Buer. We’ll also have a discussion with Steve Marcinuk to get his take on what’s coming our way with AI in 2024. But first, the news.

Pete Buer joins us as always to break down some of the latest AI headlines and how they apply to your business. Hey Pete, how are you?

Pete: Hi Courtney. How are you doing?

Courtney: doing good. So the first post this week comes to us from the US [00:01:00] Census Bureau. It provides some great news for anyone who may be feeling like they already miss the boat when it comes to AI.

The headline reads like this, only 3.8% of businesses use AI to produce goods and services. Highest use in information sector. Pete, what’s the through line here for business leaders?

Pete: Well, of course your immediate reaction is, what, 3.8%? It seems sort of ridiculously small, I kind of had to put the researcher hat on. And dig in a little bit into the report that the article’s based on, and, and the underlying research. you, you, start to get a feel for, for why the number is small the way it is.

First there’s the sample, right? This is US Census Bureau. So I, I think we’re talking to kind of every type of company in the country all the way down to your landscaper, right? So, um, that you could imagine why [00:02:00] use of. might, might skew in a particular way when you think about the, uh, inclusion of every company under the sun.

and then secondly, there’s the question itself. It, it’s very specifically worded about production of good goods and services, use of AI and producing goods and services. Um, and we know factually, definitively that AI’s being used all over the business. maybe not in every case, to produce an output in the form of a good or service.

So guess I can find my way to understanding why the number would be so low. And so what, uh, like the important thing I is, when you look at the patterns across the data, rather than worrying about the specific levels of, conclusion, what you see inside of it is that information services and professional services.

Are currently nearly, um, triple the

Courtney: Yeah.

Pete: in the TER in terms of their use of AI in, in, in production. And as you look from their level today [00:03:00] to just six months from now, um, respondents from those types of companies are imagining somewhere between a 50 and 75% increase in the next six months.

Uh, so by June of next year, these numbers are meant to increase in a way where. One in five or one in six, um, of these companies will be using AI to produce, um, services. So that feels kind of in mind with what you’d, uh, uh, expect to see. And it absolutely reinforces our focus, which is to say businesses, at the end of the day are the ones who stand to gain the most or to lose the most based on how well they deploy AI in their business.

Courtney: That’s right. And we actually had an episode specifically about professional services and the disruption. It was episode 10, so if you missed it, go back and check that one out. Next up, Pete, let’s look at some news coming out of Seattle. TechCrunch reports that Amazon unveils an AI powered chatbot for businesses at AWS reinvent [00:04:00] Q is being billed as Amazon’s answer to ChatGPT and Microsoft Co-pilot, and it can be connected to org specific apps and software including Salesforce, Zendesk, and Gmail. Pete, what should executives take away from this one?

Pete: So I got a little excited on the last question and ran long. Let me keep this one short and sweet. Um, what’s worth knowing about Q is that it has a technical bent trained on 17 years of AWS data can make recommendations on app. Workload ties in with Code Whisperer. I. can read more about it in the article.

Think the big question for execs, um, is similar to the one that we’re asking ourselves at home right now. Just how many $20 per user per month AI tools can they actually afford? For us, it’s the streaming services conundrum. You know, can we get away with Netflix or do we need Disney Plus for the kids?

Prime for Mom and Dad Masterpiece and [00:05:00] PBS for the grandparents, you know, you’re gonna have to have a strategy for what you buy and for what purpose. And then ultimately I guess how they hang together. But that seems like the interesting question to me.

Courtney: And it may not be too long until we hear from Q at the end of one of these episodes, but also, I don’t know about you, but until my Amazon Alexa can answer my questions better, I may not be ready to switch over just yet. Pete, thank you as always.

Pete: Thank you, Courtney. Love it.

Courtney: You know what time of year it is? It’s prediction season. I always love hearing about what smart folks have to say about what to expect in the year ahead. So I was excited to talk with David DeWolf about what he thinks we’re gonna see next year in the AI space. David. Hey, how’s it going?

David: Good.

Good

to see you.[00:06:00]

Courtney: You know, I, uh, I feel almost like we’re gonna squeeze this in right here at the end of 2023, and I’m, I’m really excited. I haven’t, I haven’t taken a deep dive into what we’re talking about today

David: Uh oh.

Courtney: just wanted to set this up for you, so.

David: I have to do this without Mohan. Uh,

Courtney: have to

David: okay, here we go.

Courtney: uh,

David: it to me.

Courtney: who’s out of the country.

What I wanna talk about today is predicting the future.

David: Okay.

Courtney: And specifically what I’m curious about is your predictions on the

David: Huh?

Courtney: Uh, no pressure.

David: How far out are we talking?

Courtney: We’re just talking about next year, but

David: Okay.

Courtney: we’ve experienced in 2023,

David: Oof.

Courtney: cause you some, uh, is it possible to get this right now in the world of AI?

David: Yeah.

Courtney: what do you see on the forecast if I, you know, I’m just asking for your best guesses here, but I think [00:07:00] our audience would be curious, what do you think might be coming in 2024?

David: Well, so you mentioned 2023. I think I have to start this conversation with a just maybe formalization of what we saw in 2023, and I think it’s gonna continue. Right. So most of our listeners are probably familiar with Moore’s Law. Moore’s Law was all about the. Pace of innovation and saying that transistors on a microchip would double every two years, and talking about just the pace.

I think in 2023, we have experienced that in spades. Even though Moore’s law is dead and we’re no longer experiencing it in physical chips, what we are experiencing with the advancement of AI. I think we’re going to see in 2024, the formalization of the next Moore’s law, right? However, we figure out how to express the advancement of knowledge and [00:08:00] intelligence, artificial intelligence over time.

We’re just seeing it going faster and faster, and it’s beating all of our predictions, and so we will figure out how to express that and we will coin the next Moore’s law in 2024. Prediction number one. There you go.

Courtney: Nice. I like it. Okay, number two.

David: Okay. Um, number two, let’s see if that’s the pace. So, okay, here’s another thing that’s driven me nuts.

In 2023, I feel like a lot of AI has been for AI’s sake.

Um, I’ll give you an example. We all love to talk about ChatGPT I find ChatGPT incredibly frustrating because it is simply this little green screen giving us access to large language models, right? It hasn’t taken AI, we haven’t integrated it with other emerging technologies to the degree we need to in order for it to be truly transformative.

So prediction number two is. [00:09:00] I really believe in 2024, we’re gonna figure out how AI integrates with other technologies in order to drive true lasting change versus just being this other little tool on the side.

Courtney: I love that that almost sets up 2024 to be an even bigger year, uh, for technology than

David: Yeah, I.

Courtney: was.

David: I, so I actually think it will be, um, 2024 and 2025 I think are gonna be much bigger because what you see in 23 is the advancement of the technology itself, right? 23 was all about the conversation of the LLM. We saw billions and billions of dollars going into the fundamental technology. But what’s really interesting to me is you haven’t seen the application layer yet, and so this is, here you go.

Prediction number three. 2023, you are going to see the advent of the application layer. The [00:10:00] enterprise software that’s impacting businesses that leverages AI will really hit the scene in 2024. I’ll make a bold prediction. I think we’re gonna see our first unicorn in that space. I think we’re gonna see a billion dollar valuation of an application layer, not a foundation layer company in the space

Courtney: so David, it, it’s almost like what you’re describing with ChatGPT is, it’s like the command line interface on our computers and you know, that’s obviously just the beginning

David: Very much so.

Courtney: it

David: Yeah. I mean, those of us that remember the advent of the personal computer, go back to DOS, right

before we even had Windows, uh, you know, three or whatever it was, I don’t even remember,

right. We had DOS and we were typing command prompts. Um, I think that, that, here’s another prediction.

There you go. I think we’re going to see the next level of user experience and a user interface. Um. Artificial intelligence has the [00:11:00] ability to fundamentally change the way we interact with technology. And if you look at technology over the course of time, what does it do? It blends into our lives more and more and more, right?

We started off with big mainframe computers, then we had personal computers, then we had laptops, then we had mobile devices, right? Then we had wearable devices. They get smaller and smaller, they blend into our natural lives. I think AI is gonna drive user experience. There’s gonna be huge innovation in the user experience space, this coming year.

Right now. It hasn’t happened in 2024. User experiences are gonna get smarter. They’re gonna blend into our lives. Um, and so yes, I think all of these come together a little bit with these predictions. Of, yeah, you will have this command line interface is going away. It’s not about going to ChatGPT and asking it something.

It’s in our natural flows, natural conversations, [00:12:00] natural work that we do, AI is going to begin to engage. And, and it will do that by blending in with other technologies, um, whether that is in the physical world, whether it is in other systems that we have. And it’s going to do that in a way that makes user experience smarter and easier to use.

And then I think once it reaches that point, then it’s gonna start impacting businesses. And this is where you’re gonna see the application layer step up. So all of these start to come together, to your point. And, um, I, I think it’s just the maturation, right? We’re, we’re in phase one and we’ve got 2, 3, 4, and five yet to go.

And I think you’re gonna start seeing it happen in 2024.

Courtney: Okay, so what I heard on the prediction front AI establishes its own Moore’s Law

David: Absolutely. Yep.

Courtney: Number two, you said the interaction of AI and other technologies,

David: No doubt it’s gonna [00:13:00] happen.

Courtney: and then prediction three, you foresee the first $1 billion valuation of an application layer company in

David: That’s right. Absolutely.

Courtney: And then I think the last one was you said the of AI becomes much more accessible.

David: Yeah, and I, I think more than UX of AI, what I would say is the user experiences that we have that allow us to interface with compute power, right? Right. Now, think about this. Um, we are all familiar with tools that are online, these SaaS platforms, and we go and we have to log into them in order to.

Leverage them, right? And so if, if I’m an operator of a business, um, and I want my dashboards and I want my data to be surfaced and make sense to me, I log into some business intelligence tool. Well, that’s not my natural workflow. That’s not what I naturally am doing. I’m going out there to get data because it’s powerful enough.

It. I will allow [00:14:00] it to disrupt my day. What happens in the future as AI is smart enough to now know what we need to know? Can it proactively do that? Can our user experience come meet me where I’m at, versus me having to go to where that user experience is and what does that look like? Right? Does that mean that I’m getting text messages all day long?

’cause that’s what I’m, how I’m normally interacting with people. So now I’m interacting with my computer that way. Maybe, um, maybe it’s something else. And I think the innovation in the user experience space, um, is really gonna come a long way.

Courtney: You know, I feel like I felt a whole lot of executives just kind of sigh a sigh of relief with not having to log into another platform, uh, to

David: another system.

Courtney: Yes. another system.

David: Well if you think about it, these organizations, yeah, these organizations, are spending years of time and millions of dollars moving all of their data from all these different systems into a modern data [00:15:00] stack and putting um, information and insight reporting on top of it. I actually think that’s going.

To the side. I don’t think organizations are gonna be doing that. Not because data’s gonna be less important because the technology can do the data. Re-engineering. For us,

it can be the platform and this is the type of thing that’s gonna happen. As AI infiltrates the enterprise, it’s gonna solve real problems.

And right now, organizations, they hit a point of scale and they’re investing in these types of systems and spending so much time implementing technology. Let’s flip that around. Let’s have the technology do the work for us. Let’s have it figure out how to re-engineer our data, restructure and clean our data and do it for us.

And then tell us what we need to know versus what we’re doing now. Spending so much time that candidly, I don’t know, in a lot of situations is, is getting all the way done and playing out the way we imagine.

Courtney: Okay. David, I’m gonna throw you a little bit of a curve [00:16:00] ball here.

David: Okay.

Courtney: wondering is there something you think won’t happen in

David: wow. The reverse prediction,

or I guess it’s a prediction.

of won’t happen, the prediction. Um, gosh, let’s talk about that a little bit.

So one of the things out there, I think people assume regulation is gonna hit. Um, I, I think you’re gonna start seeing some regulation in this space, though. I think it’s gonna be really, really hard.

So.

Regulation may not be as strong and, um, as crystal clear by the end of 2024 that we, than we would like to see. That doesn’t feel like a prediction, but maybe just a pace of change, uh, prediction that’ll go a little bit slower.

Um, you know, the, the, oh, here we go. I know. Um, everybody’s clamoring for human alignment, right?

Will we get intelligence to fully align, uh, with human being and human intent? I don’t think that’s gonna happen in 2024, and I will tell you why. I don’t think we’re spending [00:17:00] enough time figuring out what we mean by human intent, right? There’s all sorts of science and technology investigation into the advance of the technology to align it to something.

But what do we actually mean by human intent? Who? Who gets to decide that? Who gets to declare that? I don’t think we’re doing the work on the philosophical, uh, the humanitarian side of that to be able to come to that. And so there’s no way we reach human alignment in 2024.

Courtney: Okay. Those are two good end predictions. Thank you for that. All right, David, before we go, anything else you wanna throw in here for 2024?

David: Yeah. 2024. I think we nailed it on a meta level. I think everybody should keep their eyes open for what known well does,

I think Knownwell might be releasing, um, a pretty powerful platform to help solve a lot of these problems in 2024.

Courtney: Okay. Well, uh, I know what you’re talking about and I’m excited about it. So everybody [00:18:00] stay tuned. uh, thank you. I think this is really good fodder for 2024.

David: Awesome. Thanks for having me.

Courtney: What do you get for an executive who has everything for Christmas? I’m asking myself that all the time right now. Uh, no more cashmere sweaters, by the way, who is getting a cashmere sweater from their employees? Uh, it sounds like a pretty nice gift, uh, but you probably don’t need another one.

Oh, you know what? I bet they would love to have in their proverbial stocking a link to a free AI assessment they can take to show how their company is doing with their AI preparation. So go ahead, send the URL to your favorite executive. It’s knownwell.com/assessment. Steve Marek is an AI entrepreneur and three-time startup founder with one successful exit under his belt. [00:19:00] We were excited to get his take on what he sees coming for AI in 2024.

Pete: Steve, welcome. So great to have you on the show.

Steve: Thank you for having me. Pleasure to be

Pete: Just so we can orient our listeners, can you give us the 32nd version of your role and where AI fits into it?

Steve: Absolutely. Uh, in 30 seconds. Uh, I’m the co-founder of Intelligent Relations. We are a company that uses AI to accelerate, enhance, uh, PR processes. And we started the company about four years ago, hearing these whispers of generative AI and, uh, the tech that was coming down the pike. And, uh, we set out to build a technology that allows us to streamline these processes and PR.

So I’m day-to-day, deep in the weeds on product and every aspect of, uh, operations.

Pete: that makes you perfect episode. Not that you wouldn’t have been perfect otherwise.

Steve: Thank you.

Pete: is our prognostication episode, uh, elsewhere. There’s a segment where our CEO David [00:20:00] DeWolf talks about his. Um, musings on what we can expect to see that’s momentous from AI in 2024. Uh, could we get a glimpse into your crystal ball on the same topic?

Steve: Yeah. So, uh, I would say there’s two main things that were. We’re seeing and building our product around. Uh, the first is connectivity integration on generative AI, and then the other is recursive learning. So on the first point, connectivity, uh. Up until now, we’ve seen mostly generative AI existing in a bit of a vacuum where you can give a prompt, it will reply to you, et cetera.

We saw early indications of movement towards connectivity to. External information, um, in, you know, searching on Bing It does a query to the internet returns, and then, forms an answer based on that. And then the, [00:21:00] uh, with the development of these GPTs from OpenAI and some work we’re seeing on lang chains and things, other initiatives that allow the connectivity of generative AI models into.

Other data sources. I see that’s a trend that’s going to definitely accelerate. And so having generative AI be deeply connected to other sources of information, be that documents, be that analyzing images more, being that connected to databases, you name it. I think that is an area that we’re gonna see a tremendous amount of progress.

And that’s also gonna bring generative AI to a much more usable point for, day-to-day practitioners. We’re building a lot of functionality around that. Uh, so that’s. Chunk one. And the other area, uh. I will put broadly under the category of recursive learning. Basically systems that get smarter over time and can, uh, improve and become customized. So I think that on a super simple way, I will say a, [00:22:00] a chat bot.

Or a, a chat, uh, interaction that learns what you like and becomes customized towards your use case. So for us, that’s about, imagine we’re writing a pitch, an email style, say a sales email as an example. As you do a few examples, your system learns this is what. You like, and it starts to learn from past feedback to get smarter in that very specific use case.

That could be for social media posts, it could be for document preparation, anything like that. So rather than having to customize models that are built from scratch to be. Permanently good for your use case. You’re building models that get smarter over time and kind of, it’s one model, but the, the system itself adapts itself to your use case.

So general purpose models and systems that adapt and learn from you. That’s kind of on a, on a microcosm and zooming out a little bit more, I think we’ve started to hear this [00:23:00] conversation about artificial general intelligence and that. On, on, on steroids on the accelerated version is you have the entire system is learning and retraining its model.

So that’s one of the things that just got Sam Altman and in a bit of hot water, is

Pete: Yep.

Steve: were some rumors and maybe evidence that they were accelerating towards models that self-trained and improved over time without necessarily the right guardrails. The, this time of recording, it’s still not totally clear, uh, on that ride.

But yeah, it’s, that will probably happen. It’ll take us towards models that improve naturally over time, either for a fixed use case or much more general use cases. And that is a tremendous amount of power that’s coming down, uh, down the pike.

Pete: It’s, it’s so fascinating, um, and it’s so important for business leaders to understand. You, you circulate among companies and executive teams on a regular basis. What’s your [00:24:00] sense for how well leadership teams are staying on top of the possibilities like the ones we’re talking about right now, of of ai?

Steve: So I think there’s a lot of enthusiasm and a lot of skepticism. Um, I think on the enthusiasm side there is similar to what we saw with things like blockchain and virtual reality. There’s a lot of enthusiasm for people saying, this is the next big thing. And I think some understandable skepticism of, yeah, that’s nice, but how is this actually gonna impact bottom line operations, productivity, anything like that.

From my perspective, having worked with this for the last four years in our. In building our applications, I do see that this has immediate, practical implications that are worth paying attention to, and I think that any business leader should be increasingly familiar with what this technology is capable of doing and thinking of very specific ways to apply that to their, their [00:25:00] current operations.

I’m happy to dive in there a little bit more if, if

that’s, uh, useful.

I, yeah, I’d, I’d like to, because I could imagine, um, being a leader, listening to the podcast and thinking, you know, I, I either I. Aren’t as far along as I ought to be, or I’ve got some skepticism or, or maybe I get it, but my, my team isn’t there yet. what, what’s the way that, leaders can, for themselves or for their teams get smarter and steps in what order?

Steve: Yeah, so I think that the best way to familiarize yourself is to dive in and try using some of these tools. The good thing about this technology is that there’s a lot of companies that are deeply invested in making this AI generative AI accessible.

So that’s going to, going to open AI, playing with chatbots, going to, there’s a, a one I like called a Claude that is rather, rather fun and more personable.

Uh, there’s a number of different tools and so [00:26:00] interacting with them and pushing the boundaries of what you can and cannot get out of them is a really great way to get immediate feedback on what these models are capable of and not capable of. Entry level, you start to understand what’s the next step beyond that would be, I think the best user interface is open AI’s playground.

So you can sign up on OpenAI. I think it’s free, where you can add a credit card and pay pennies for setup. But. E, I’m talking specifically to non-technical folks here. When I say these playground environments are set up for business leaders to experiment and play, and that’s how we have built some of our best technology, I, as a non-technical co-founder, have been able to, but, but subject area expert in.

Our use case in public relations,

I have been able to dive in, set up initial models, [00:27:00] worked with our engineering team to, to take them to a level that’s production ready. So just by exploring and saying, I wanna see if it can do this, and then integrating the, the technical team, that’s actually a really cost effective way and.

My perspective is a lot of the, the business leader folks have a certain kind of creativity in terms of operations and workflows. You can really start to see the potential just by diving in, but reading about, it’s not gonna really do it. You know, I, I like the newsletters, uh, prompt Warrior and some others, but diving in, that’s, that’s what this technology’s about.

Pete: Awesome. Steve, it has been such a pleasure. Thank you so much for, for joining us.

Steve: Thank you so much for having me.

Courtney: That’s it for today’s show. As always, thanks for joining us and don’t forget to like and review our show wherever you [00:28:00] listen, We always like to ask one of our AI friends what they think about this week’s topic to round things out.

And I don’t know if you’ve been noticing, but we’ve had some new AI friends here with some really unique voices. So you can thank our producer Nick for that. But this week we’re gonna go back to ChatGPT. Since you just celebrated your first birthday, can you tell us what you think is in store for AI in 2024?

And now you’re in the know. Thanks as always for listening. We’ll see you next week with more headlines, roundtable discussions, and interviews with AI experts[00:29:00]