Ep 397: How AI Is Democratizing Innovation for Non-Tech Experts

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Making AI Accessible for Non-Tech Users

Getting started with AI need not be a nerve-wracking experience, even for non-tech savvy people. A practical approach is to focus on personal applications first rather than heading straight for business solutions. This helps to minimize concerns related to data privacy. A good starting point could be using AI to assist with simplifying daily personal tasks such as travel planning or managing diet plans.

Testing Different LLMs for Best Matrix

With multiple LLM models like Claude, OpenAI's ChatGPT, Mistral, Meta’s Llama model, and x.ai now available, it's wise to test them out to understand their strengths and weaknesses. To do this, input the same prompt into these models and then compare the results. This way, businesses can better determine which model is most suitable for which task.

Effective Interface Considerations

While combo interface tools can offer efficiency for certain users, there's undeniable value in interacting with individual models. This not only provides a more customized experience but also offers unique insights which might not be possible when using combined tools.

Newer Models to Consider

Google Gemini and Microsoft Copilot are additional models worth considering. Each has its strengths and preferences, making them suitable for different use cases and requirements. Conclusively, the decision all boils down to specific needs and desires.

Democratization of Innovation

An observable impact of LLMs is in how they have sparked personal and business innovation through improved accessibility and enhanced functionality. By breaking down technical barriers, AI has democratized innovation, underscoring the fact that one doesn't need a formal background to be innovative, particularly in the current AI-infused world.

Challenges and Steps Towards an AI-First Workplace

While the benefits of integrating AI in business models are undeniable, the transition is not always smooth sailing. Many established businesses struggle with bureaucracy and bold decision-making is required to fully harness AI's potential. Startups, however, hold a golden ticket to an AI-first work environment, creating competitive edge by substituting traditional employee roles with AI agents.

The Synergy of AI and Business Innovation

The advent of autonomous AI agents by tech powerhouses has sparked rapid advancements in innovation. By leveraging AI's capabilities, businesses can expedite the innovation process, creating new revenue models and improving current ones.

AI in Idea Generation and Execution

The transformative role of AI in creativity is hard to overlook. It augments idea generation, making brainstorming a breeze. However, despite AI's prowess, the role of human involvement in discerning valuable ideas and executing them effectively remains irreplaceable.

How AI Can Inspire New Businesses

AI can tremendously aid in starting new ventures. With the help of AI solutions like ChatGPT, aspiring entrepreneurs can explore potential business ideas and unearth unmet customer needs which, subsequently, can be addressed in unique ways.

The Bottom Line

Ultimately, the key is to not fear starting small and to never shy away from investing in even seemingly insignificant ideas. More than ever before, it's crucial to experiment and engage with AI in a child-like manner, where failure is viewed as a learning opportunity. Whether you're a tech expert or not, AI stands ready to revolutionize your world - as long as you're willing to let it.

Topics Covered in This Episode

1. Applications and Capabilities of LLMs
2. Approach to AI for Non-Technical Users
3. Future Changes and Challenges with AI
4. Role of AI in Creativity and Business Innovation
5. Adapting to AI and Challenges for Big Companies

Podcast Transcript

Jordan Wilson [00:00:17]:
When you think about innovation, sometimes you think that you may have to have a background in innovation to be innovative. Right? That would make sense. But what if I told you that you don't necessarily? Right? It's I think you can still be more innovative in today's AI everywhere world if you have a background in innovation. But if you know what you're doing and if you know what large language model to use when and if you really listen to today's guests, I think that you can become more innovative than ever before, your company, your departments, because I'm excited today to talk about how AI is democratizing innovation even for non tech experts. And we're gonna be talking to an expert in innovation. But first, I have to welcome you to everyday AI. What's going on y'all? My name is Jordan Wilson, and I'm the host of Everyday AI. And we are a daily podcast newsletter livestream helping everyday people learn and leverage generative AI to grow their companies and to grow their careers.

Jordan Wilson [00:01:24]:
But before we get started, have to first give a shout out to our partners at Microsoft in the WorkLab podcast. So why should you listen to the WorkLab podcast from Microsoft? Because it's made for leaders who know they must adapt to stay ahead. WorkLab is the place to find real world lessons and actionable insights to guide you and your organization through AI transformation. That's w o r k l a b. No spaces available wherever you get your podcasts. Alright. Speaking of podcasts, yeah, make sure to go check out WorkLab. If but every day, if you need 400 plus episodes, we have them all on our website.

Jordan Wilson [00:02:02]:
It is, I say, like a free generative AI university. So if you haven't already, please go to your everydayai.com. Sign up for the free daily newsletter. And while you're there, go learn from literally the world's leading experts on whatever topic you want. Alright. And, normally, we come to you fresh and live, and we bring you the day's, freshest AI news. This is technically prerecorded, but debuting it live. But we're still gonna have, everything that you need in today's newsletter, so make sure to go check that out.

Jordan Wilson [00:02:30]:
Alright. But let's get straight into it. Enough chitchat from me. Let me bring on an expert, who knows a thing or 3 about innovation and how even nontechnical people can really start to innovate like the pros by using AI at the right place at the right time for the right purposes. So, please help me in welcoming on the show. There we go. We got him. Mike Todasco, who is a visiting fellow at San Diego State University.

Jordan Wilson [00:02:57]:
Mike, thank you so much for joining the Everyday AI Show.

Mike Todasco [00:03:00]:
Jordan, thanks for having me. And I like your chit chats. I I I wanna hear more of that chit chat in fact. I was I was really enjoying that. So I'm gonna keep going.

Jordan Wilson [00:03:08]:
Don't tempt me, Mike. We might accidentally, you know, turn this into a 3 hour podcast like a Lex Fridman style, but we'll try not to. But, Mike, can you tell everyone just a little bit, you know, about what you're doing right now at San Diego State University? And then we'll we'll tap into your background a little bit more. But what are you working on now?

Mike Todasco [00:03:24]:
Yeah. I I'm at San Diego State, but I live in Silicon Valley, and and I've lived here for about 20 years. I kind of have a dream role. I get to, mentor students. I get to teach. I get to work in our lab when I go down there, and it's beautiful to go down to San Diego whenever you possibly can. And we work on things like using AI and robots, for mental health, and we do, research in those spaces and so forth. And it's just a very exciting place to be.

Mike Todasco [00:03:50]:
And it's a very exciting time for anybody who is at all using, developing, doing whatever in the world of AI right now. This is this is something that you will look back 20, 30, 40 years from now and tell your kids about, yeah, I remember doing that way back when. I mean, this is an amazing time right now.

Jordan Wilson [00:04:08]:
Alright. So sounds sounds like a dream job, FYI. But, you you know, you you've had quite a a background in in history in the tech sector, you know, being there in Silicon Valley. But can you tell everyone a little bit about your, you know, to on the topic of today's, podcast innovation? You have quite a background in it. Can you tell us a little bit about your time at PayPal?

Mike Todasco [00:04:32]:
Sure. And, actually, even before PayPal, I wanna just level set with everybody. Like, my career started off as an accountant. So, like, I am, like, old school accountant, was actually even working at a paper company, like like, Dunder Mifflin style paper company and so forth before I joined PayPal and started my own little tech business. So, like, I I do wanna make clear, like, when if you're listening to this and all that and you're like, oh, but I'm not technical, like, I ain't either. I kinda just learned all this stuff by doing because I was interested and excited and so forth. But 2011, I joined PayPal after my start up was not going where I wanted it to go. I was a PayPal customer for years and got a job at PayPal doing product analytics.

Mike Todasco [00:05:19]:
It's kinda like being data science, but they didn't even call it data science back then, but I had no idea what I was doing. I always like to tell people I was dangerously unqualified for every single job I ever had at PayPal, and it was just an amazing ride. I joined the mobile team back in 2011 when I joined when mobile was its own little weird thing, like, separate from the rest of the business. Like, well, what are those mobile people doing and all that? And, eventually, it kinda overtook everything at the company. And just had an amazing ride there. Was in various product roles for my first half at PayPal. And then when PayPal separated from eBay in 2015 moving into 2016, had the opportunity to kind of run the innovation group for the newly formed company. And, honestly, like, talk about, like, dream jobs, that was pretty amazing.

Mike Todasco [00:06:06]:
It it was so much fun to do. It was all about, inspiring our company to be more innovative, to work on new products, next generation technologies, new tools, all that awesome stuff. I every Sunday evening, I was super excited to go to work that very next day. You know, you can't ask for much better than that.

Jordan Wilson [00:06:25]:
Yeah. And, you know, I'm curious because I I do think, you know, PayPal, unless you grew up in the, you know, surge of of PayPal. Right? I think it was one of the most innovative companies of its time. Right? I I don't know if Yeah. You know, I'm sure we would have gotten there eventually, but so much of what you see today with online shopping, you know, in transacting online, PayPal actually paved the way very early on. So, you know, I'm curious before we jump into the AI side, Mike, because, I kick myself if I didn't ask you. You know? Mhmm. What was it like having to, you know, to to be in charge of innovation at a company like that that at its, you know, in its heyday was one of the most innovative companies in the world, and and how did you approach that challenge?

Mike Todasco [00:07:13]:
Yeah. So so the first thing I would say is I was in charge of the innovation group. I wasn't in charge of innovation because everybody was charged of in charge of innovation. And and that sounds like a very, you know, distinct thing that I like to do say, but, that was true. I mean, that was part of our culture. There's a great book. If you're really interested in the history of PayPal, it's called The Founders. I actually hosted the author, Jimmy Soni, at PayPal, back in the day and kind of walked through it.

Mike Todasco [00:07:39]:
And it talks about the early days of PayPal and just how we, as a company, were forced into innovation because there were all these Russian hackers that were, you know, days, maybe even hours away of just taking down the business. Because if the credit cards got exposed, then the company was no more. And when you're forced into that, it forces you to be innovative. And this, like, really built this culture within the company that was something that we tried to continue as much as possible with my little innovation group. And, you know, it it it introduced, like, little things that don't seem like much, but if anybody has ever, tried to connect a, bank account to something and all of a sudden you get 2 little deposits, you know, of, like, 14¢ 32¢, and you have to confirm what those were. Like, that was a PayPal innovation, and that came from some engineer who basically, they were asking the question, hey. We gotta, like, have people send in checks and do all this stuff to add a bank account. I wish there was just a PIN number for a bank account.

Mike Todasco [00:08:42]:
They're like, well, why don't we make a PIN number? And that, effectively, that micro deposit thing that permeated for 20 plus years for all companies was like a little PayPal innovation. But, like, those are the innovations that really matter. It's the things where there is a problem and, like, you might think that, like, well, wasn't that obvious? It wasn't obvious at the time. But it was a really simple, very elegant solution to be able to solve a big expensive problem that we were having. And so you do hundreds and thousands of those over the years years as a company, and eventually build up this really innovative culture.

Jordan Wilson [00:09:16]:
So I wanna kind of fast forward to to current day and and get your get your viewpoint on it because I'm sure that, you know, PayPal was using artificial intelligence, obviously. But now we have generative AI, right, where you don't necessarily need a a PhD in machine learning to take advantage of AI. You know, what was your kind of first takeaway when you saw the surge of, you know, large language models that were made for everyone? And, you know, as being someone with a background in innovation, what was kind of what did that unlock for you, kind of, you know, in the early days of generative AI, which is funny to talk about now that it's been, like, you know, 2 or 4 years since we've had access to, you know, GPT technology.

Mike Todasco [00:09:58]:
Yeah. Jordan, my I I love talking about this because I remember I I like literally, my heart is probably palpitating right now because I remember how giddy I was the first time I've got to experience GPT 3 firsthand. And because you're right, I in the innovation lab, I would have all these machine learning engineers and they would come in and they would do demos and they would do all this really impressive stuff. And I was always like, that's so cool. I can't do any of that. So I'm not a not an engineer, let alone a machine learning engineer. I don't have the tools to do that. And when GPT 3 when GPT 3 came out, it was a while before I got access.

Mike Todasco [00:10:36]:
But I remember 2021, got access. I was just working on this fun little side project where I was working on a, a short story that was actually an inaugural address for an AI slash robot that becomes president. And I'm like, okay. What's the inaugural address gonna look like? So I actually wrote some pieces. I actually stole some from Obama's second inaugural address. I put that in there. And then I just kinda put that into GPT 3, and I just, like, said, okay. I, like, hit go, whatever it was in the playground or whatever I was using at the time, and it just started generating.

Mike Todasco [00:11:12]:
And, honestly, Jordan, I was like, oh my. I was so excited because I'm I'm seeing this, and it's creating, like, cohesive thought. It's continuing the story from where I was, and it would screw up. Like, one time it just kept up. It was like, and, and, and, and like, it it was hallucinating, which actually made for a better story when I was kinda choosing this because we were actually seeing the AI screw up. But I remember it being in my kitchen seeing that, running upstairs, screaming. My wife didn't know what was wrong, and all that, but I was just so excite I'm like like I'm like, the computer, it is it's making words. It's making words that it makes sense.

Mike Todasco [00:11:51]:
And this was revolutionary. So for me in 2021 to see that, I I immediately I I got it. Like and and I think part of it was because I wasn't an engineer. Like so this was me saying for the 99% of people on Earth who are not engineers, this was the great unlock. And you just see those tools get better and better, and then, you know, move to image generation with DALL E and tools like that and so forth. And that's why by the time I left PayPal summer 2022, that summer, I actually wrote my first article about AI, which was, effectively this is it was called the one technology that everyone should be freaking out about, just because I was like, this is the future, people. Like, it is here. Like, look at what we can do today.

Mike Todasco [00:12:41]:
This is the great unlock, and it's not gonna stop. And and it's just kinda been up into the right since then.

Jordan Wilson [00:12:46]:
Yeah. It's it's it's funny, Mike, because I had a very similar reaction. Right? My background, you know, I had a couple careers, but I was a journalist for a while. And, you know, our team, I I had a digital strategy agency at the time and, you know, we're we're writing Google Ads and, you know, SEO copy for clients. And, I think it was late 2020, early 2021 when this GPT 3 technology, you know, started to roll out to these other, you know, 3rd party providers. And I think it was writing, you know, headline options for a current client, something small. But to be able to write, you know, hey. Here's the client.

Jordan Wilson [00:13:22]:
Here's here's the problem, and it would spit out 10 headlines. I was straight up flabbergasted. Right?

Mike Todasco [00:13:28]:
And

Jordan Wilson [00:13:28]:
as a former journalist, I I know, you you know, what goes into, you know, sometimes writing a newspaper headline and spending 3 people around the newspaper and spending 10, 15, 30 minutes. And for it to be able to spit out something so fast, I could see how revolutionary, that that was. Right? And, like, I love hearing that you had this exact same kind of, feeling.

Mike Todasco [00:13:51]:
Yeah. Absolutely. And and specifically on the writing side, you know, let's fast forward to today and what the technology on on, opens up today for us. When you're using this technology, it it is it is the greatest not the greatest. It is an amazing writing partner that is always accessible. Like, yes, I'd rather have Ernest Hemingway sitting next to me, like, drinking than just, like, being able to shout out ideas and so forth. But like that aside, to pay $20 a month to use one of these tools to be able to say, hey, here's an article I just wrote. Give me 10 potential headlines for this or do you know what? I'm I'm struggling with this piece here.

Mike Todasco [00:14:29]:
Give me 5 different ways that you can, you can shorten it, make it snappier, or, like, I I just got nothing here. Give me, like, 2 different options. Like, that's how I use tools like Claude and ChatCBT all the time in my writing today. It is not going to be able to write something from beginning to start as well as a a good writer could. It could do things like it could take sports and it's been doing this for almost a decade now, taking, like, sports scores and just making an article out of that. There's a there's a formula to that. If you're trying to get a little bit more advanced in writing, it doesn't quite do that, but to have it as a writing partner to help you out with that, it just helps you iterate so much faster as part of that process.

Jordan Wilson [00:15:12]:
Yeah. And I think that was probably one of the the earlier and, lowest hanging, fruit use cases. Right? Helping maybe people who weren't great writers be good or okay or better, right, or above average pretty quickly. But now large language models are so much more than that. Right? We have multimodality, the ability to input audio, output right? It's it's it's getting wild now. And I think this, you know, especially some of the developments over the last 6 to 9 months have really opened up the eyes to the everyday business person on, hey. I should probably be using large language models a lot more than I should, but where do I start? Right? Especially people who are nontechnical. So, Mike, what would be your best advice on how do people start? Where do they go? How do they know which model is maybe best for them or their use case?

Mike Todasco [00:16:00]:
So let's start with, like, where to start, and and then we'll get into which model next is part of that. So the where to start, I would actually say is not in the business context. It's probably in the personal context. Think about a problem that you're having in your life. Think about something that is mundane that maybe you don't enjoy doing. Maybe it's travel planning. Maybe it's cooking. Whatever it might be, just start to apply the models because then, especially, you're not worried about data leaking out or any of these other kind of things that you may be worried about in the business context.

Mike Todasco [00:16:31]:
So what I always say is, like, for people, start with those personal use cases. To give one very specific example, my dad is you know, he just saw a doctor, and doctor's like, yeah, you gotta do some tweaks to your diet here. And so one of the things that I am working with him on is actually building a custom GPT for him, and this is something that I think anybody who'd pays the $20 a month for ChatGPT can get. And we're going to, like, put all the information into that custom GPT. And within there and it's gonna say, like, hey. These are the things, like, you know, here's actually his blood test. Here's a few other things. Here's some statistics, and here's what we want.

Mike Todasco [00:17:10]:
Here's the goal. Here's what we want to achieve. Now give him and there's so many different ways to do this. Give him a 10 point scale. And so whenever he holds up his phone and takes a picture of what he's about to eat or a menu or whatever, grade those things for him, as far as, you know, meeting his health goals. And sitting at a restaurant, that's pretty darn awesome to be able to just take a picture of the menu and to see, like, oh, if I eat the, the chicken carbonara, that's a 4 out of 10. But if I eat the salad, it's an 8 out of 10. I'm gonna go with this one today.

Mike Todasco [00:17:44]:
And, again, you customize that however you want, however resonates with you. By doing that kind of stuff personally, for starters, that begin that starts to open up so many things of, like, oh, wow. If I did it for this, could I do it for that? And, you know, it just becomes natural that you start to realize that. Now bringing it to the other part of your question, bringing it into actual workplace or even just finding out, okay, what model is best? What I would recommend is start with all the models. So I'm just gonna, like, mention, like, 5 here that I like, our well, my most frequent go tos. There's Claude by Anthropic. There's OpenAI's ChatGPT. There is Mistral.

Mike Todasco [00:18:29]:
They have their own free model that's out there. There is Meta. So Meta has a llama model. If you just go to meta.ai, as long as you have any Instagram or Facebook account, you can use it. And there's also x.ai, which I think you actually have to pay for it to use all things, but I don't so that's kind of the 5. And how to find out which one's the best? Put the exact same prompt into all 5 months. And that's how I would start the process. So say you are a product manager and you're working on a, PRD.

Mike Todasco [00:19:04]:
So, you know, some sort of product description. It's gonna be a very formal format and so forth. And, yeah, here's a paragraph of it. Like, you know, give me the high level points or whatever for a PRD. Drop that into each one of the 5 models, and just and then within 10 seconds, all of them will have responded with the results and just, like, see, like, okay. Well, it looks like Claude did the best here. It looks like Meta did the best here or whatever it might be. And then you kinda go down that path.

Mike Todasco [00:19:31]:
Now, of course, this is there's always the business concerns of data leakage and all this other kind of stuff. Like, I'm just putting that aside for the time being. You know, we can get to that later if you if you want to, Jordan, on how to think through that. But, like, that's how I would think about these problems and that because you will find, like, for me, when I'm writing, Claude is definitely the best one, the one that I gravitate to and so forth. If I'm doing something a little bit more mathematical, the chat ChatGPT zero one preview, I think is the name. The the the naming is awful at these companies. It is, like, beyond ridiculous how bad it is. But, but, like, that's where I go to, and I've just kinda learned that over time.

Jordan Wilson [00:20:13]:
Yeah. Yeah. I I I love that. And FYI, I I I'm gonna put a video in our, in in our newsletter, today. I there's there's quite a few tools that even allow you to do this all at once. Right? Put in one prompt, and you can get a, you know, a window of 4 or a window of 6 to to make it even easier. But I do think there are some instances where I even like to go in individually because, you know, the user interface matters as well. But but, Mike, one thing actually, I gotta ask you this because you didn't mention Google Gemini and and you know, Microsoft Copilot, which I know is based off of GPT.

Jordan Wilson [00:20:48]:
Like, is this is this a personal, vendetta here or just Oh

Mike Todasco [00:20:52]:
my god. No. No. I I literally I even have an Android phone and everything. I mean, so no. It's actually so funny. I I I don't pay for the advanced version of Google Gemini. I use the free one just because I'm paying for so many of these darn things right now.

Mike Todasco [00:21:07]:
So I will occasionally use Gemini more for doing, like, complex searches, but you can try Google Gemini. I have and and, actually, if anybody and I have a free newsletter. I'm not trying to sell anything. If anybody ever checks it out, a little while ago, I actually did something comparing them all, and I did have Google Gemini in there. So I it was 6. Alright. And just

Jordan Wilson [00:21:27]:
to have the thing with Gemini

Mike Todasco [00:21:28]:
is so Gemini is, at least the version that I used. One of the things I did was I actually had each of the models write copy, and then I put it into an AI detection editor. And it would tell and Grammarly has a decent AI detection editor. And I will say, like, Gemini was the only one that was consistently getting, like, 100%. Meaning, it was like, the detection editors, like, this is a 100% AI written. Now they all were a 108 100% AI written, but Gemini, for whatever reason, like, it feels a little bit more AI y for certain things. That's why it's not usually the first one I turn to.

Jordan Wilson [00:22:06]:
Yeah. Yeah. Something feeling AI y. That's that's, it's a very common feeling, especially if you scroll on social media, you know, nowadays. Mike, one one thing I wanna get into, so this is great. You kind of gave us some some great tips on on where you can start, how you can, you know, kind of try on the different models, find the right one for, for your needs. But when it comes to innovation, right, that's where I really wanna tap into it. So maybe I I wanna even start with with you personally, you know, with with your background.

Jordan Wilson [00:22:35]:
How has, kind of the the innovative process or the process of, you you know, whatever innovation actually entails. Right? Creativity, brainstorming, iteration. Right? But this innovation process, how has this changed for you personally using large language models?

Mike Todasco [00:22:54]:
It's the 2nd place I go. I mean, and that's the honest answer. And when when I what I mean by that is, like, the first place is still always kinda my brain, my pad of paper, whatever else. But, like, once I have that, then it just becomes my my brainstorming partner on all these things. So let's take, you you know, let let's just say we're trying to build a new product or or whatever it might be, and we have a a customer who's has a very specific need where they, you know, they they they have a hard time they their dog, they have a hard time finding out what to do with their dog during the day while they're gone. There we go. So I don't have any pets or anything, so I don't even know what to do in these situations. So I would just start with myself.

Mike Todasco [00:23:37]:
They're like, okay. The problem statement is this. There's a customer who has this problem. During the day, they're gone for 10 hours a day. What do they do with their dog? Well, yeah, you could get somebody to walk it. You could keep the TV on. You could do all this other kind of stuff. I'm just gonna, like, kind of lay out my exhausted list of that.

Mike Todasco [00:23:55]:
When and whenever you're brainstorming yourself, and I've run literally hundreds of brainstorm sessions throughout my my career and and seen this well, your first ideas are basic and suck. Like, just that's just how the brain works. Once you get up to, like, 7, 8, 9, that's when it starts to become interesting. And you kinda almost wanna extend that to the point where it's almost slightly painful. Like, I don't know if I got anything, and things are getting stupid. And it's kinda like this waveform almost. You see it, like, quality of idea over time as you're moving forward. But then I would take that, and then I would frankly snap a picture using ChatGPT or whatever tool.

Mike Todasco [00:24:34]:
And I would then say, hey. I'm trying to find a solution for my dog or a business to help, people who leave their dog at home all day and want to do something to keep their dog occupied. Here's a starter. I want you to take all these and and go beyond. Take them to the next level. And that's where the ChatGPT it's gonna see the patterns that you have. So it's gonna be able to kind of take that, see, like, the type of things you're thinking about and so forth. But it's going to, you know, 2, 3 x those ideas.

Mike Todasco [00:25:07]:
Most of the ideas are gonna be crap. And when you're brainstorming, when you're ideating, that's part of the process. It's no different for ChatGPT than it is for people. But then when it gives you, you know, and you could say, hey, give me 15 ideas. Then what you should say is like, okay, Ideas 7 actually, I wouldn't you could say, like, ideas 7, 2, and 6 are actually really bad. Don't go in that direction. But ideas 11, 13, and 15, I let's go down on those. And, in fact, can you combine, can you instead of saying this in 13, say this instead and whatever, and then give me 10 more.

Mike Todasco [00:25:45]:
And then you kinda keep doing this again and again and again, and then all of a sudden, you've gone from you know, and this happens in minutes. This is not hours or anything like that as it would be for those humans doing this. This is, you know, 20 minutes of you brainstorming something and then 5 minutes of just running stuff through ChatGPT and you evaluating it. You know, the one thing ultimately in, like, our AI future that I see, no matter what role you have in business, whether you're in finance, whether you're a product person or an engineer or an entrepreneur or whatever it might be, you're going to be much more the director of things, kind of pulling the string strings, saying what's good, what's not good. Taste is going to matter even more in this future because, you know, the value of I of coming up with an idea is effectively going to be 0 in this future.

Jordan Wilson [00:26:36]:
Oh, wow. That's deep. The the the value of coming up with an idea could effectively be 0 in the future. Sounds like a hot take, Mike. I I, a 100%, agree, by the way. But explain that a little bit more. Right? Because I think so like, so much like, so many times, people, right, all successful people in business have gotten to where they are today partially because they had good ideas. Right? And then they had knowledge, to to back that up.

Jordan Wilson [00:27:04]:
But now those are things that large language models are increasingly getting better and better at. Right? You mentioned the o one model from OpenAI. That's a reasoning, model. Right? So if if these large language models, essentially have all of the information and all of the knowledge of humankind essentially. Right? And if they're getting better and better at ideating and, creating, ideas. Right? How should we, as as humans, as people who want to grow our companies and careers, how can we prepare for this large language model infused future?

Mike Todasco [00:27:37]:
It's it's a great question, Jordan. And and what I would say is ideas have always been overvalued as far as the is their capital. I I and and this phone that I showed you before, I have thousands of ideas in piles in here, everything from, you know, the next great blockbuster movie to book ideas to business ideas to whatever it might be. I got all these things in there. What matters is execution on these ideas. Any day, I will take a fair idea with excellent execution versus an excellent idea with fair execution. Like like, execution is what matters, and that is going to be the case even more in this future. So, you know, so I think we always overvalued the value of ideas, in the past.

Mike Todasco [00:28:27]:
And again, this I'm the innovation guy. Like my job for 6 years was just coming up with ideas for stuff. It was not about execution and things like that. So I I lived in this world and saw that, like, execution is what really matters. And look, I'm not saying, you know, would I rather have an excellent idea with excellent execution? Of course. Like give me, give me that any day, but it's going to be much easier to get to that excellent idea than it is in the past because we have these tools. And the thing that is just really going to matter, it's taste. It is taste.

Mike Todasco [00:29:00]:
It is discretion. It is these other human traits and qualities that the AI can't quite do yet. We're still they still got a little ways to go before they're really able to say, like, hey. This is this is a better idea than that one. Like, they could sort of do that in some cases, but I think there's a lot of layers to that, lot of experience that has to go into that to really decide that. So that's why, like, execution is what matters in the future. But by all means, use these tools for ideation because that's what one of the things they do best.

Jordan Wilson [00:29:34]:
Mhmm. So since you kind of shared a a a somewhat hot take, Mike, I'm gonna I'm gonna go ahead and

Mike Todasco [00:29:40]:
Lukewarm take.

Jordan Wilson [00:29:41]:
Yeah. I'm gonna I'm gonna throw one out to you, and I I kinda want your response. Yeah. Yeah. So my thought is that we have to unlearn. Right? I think all these companies are throwing out all these AI buzzwords like upskilling, reskilling, skill sharing, AI skill blank blank blank. Right? I think we need to unlearn. I think that we have to unlearn good habits that we've developed, over the past couple of for a lot of people decades, and we have to reimagine how we work in an AI first, in an AI native world.

Jordan Wilson [00:30:13]:
And I think a lot of that requires innovation. Right? And and maybe the way that we, really need to work is and and where we can apply this innovation and execution is literally reimagining how we do our day to day work and and rewire unwiring first and then rewiring kind of our brain and how it works. What's your take on that and even, like, kind of how innovation plays into this future? Because what you said, it sounds like ideas are nothing, execution is everything. And as the models get bigger and better, I think we have to just unlearn everything. What do you think?

Mike Todasco [00:30:46]:
I think unlearning is important and it's so hard. I do not envy big companies right now. I like it. No. I think it's really tough when you have bureaucracy, when you have all of these things go kinda lined up against you. Like, look. I always love the the thought experiment. If we had fine define AGI however you want to.

Mike Todasco [00:31:09]:
So, basically, it's, you know, smarter than the combined intelligence of all humans on earth. If it just was, like, drop Sam Altman just drops it down on us today, is the world going to change tomorrow? And I think everyone would say, well, probably not. Is it gonna change in 6 months? Is it gonna change in 5 years? It's gonna change at some point. But, like, there is so much bureaucracy, in companies. There are so many incentives that are not it doesn't necessarily push towards an efficiency. I mean, in Silicon Valley, for example, I think this is finally starting to change. But for a long time, your mark of worth in Silicon Valley was how big your team was, was how many people you had working for you, how big your organization was, and and, you know, the title that would ultimately come with that was the mark of status in Silicon Valley. And that just meant, well, you just have more people.

Mike Todasco [00:32:03]:
Well, well, you got bigger budget and all this other kind of stuff. And I think there's finally start to be a move away from that of a, like, you know, some, like, these some mass layoffs that we've seen over the last year and start restructuring around that. But that's hard. And and these are supposed to be the most innovative companies in the world, but even they have been caught up very much in their own bureaucracy. So, George, everything you're saying, like, for a big company, it ain't easy. It can be done. And but, like, a lot of bold, sometimes difficult, and sometimes wrong decisions will have to be made to say, well, how do we act in this future? How do we change the incentives so we can be more nimble, so we can be, you know, an AI first company or whatever you wanna call that? For a start up, though, for a small business, it's totally different. Like, if I'm starting a company today, am I going to hire a data analyst? Am I going to hire an HR person? Am I gonna do that? Like, I'm gonna be thinking about, wow.

Mike Todasco [00:33:00]:
Like, there are AI agents that could do this coding, that could do this. And, again, I'm gonna be hiring people to kinda direct these agents, but probably not to do a lot of the rope work itself. And then that's gonna give these companies a competitive advantage. So, look, I spend a lot of my day talking to people hoping to start or starting companies. I think there is this is an amazing time to be starting something if you are truly AI first. And if you're a company who's not, how do you do that culture shift so that you can be? Because this is coming whether you like it or not. There's no legislation. There's no nothing that is going to be able to stop the AI train.

Mike Todasco [00:33:40]:
Ethan Malek, the professor from Wharton, I I I love one of his thoughts that he has where he talks about even if that model stopped improving today, like, this was the the end. We never get better than this ChatGPT version or cloud version. We would still have years of productivity gains ahead of us because we haven't even figured out fully what these models are gains ahead of us because we haven't even figured out fully what these models are currently capable of.

Jordan Wilson [00:34:02]:
Mhmm.

Mike Todasco [00:34:03]:
And re in reality, they're gonna keep getting better. There there's tens of 1,000,000,000 of dollars being spent on hardware and all of these things that are just going and, you know, scaling laws laws have not stopped. Basically, meaning, the more money, the more, NVIDIA GPUs they're throwing at this, the better results that they are getting, which is how NVIDIA has become, you know, the 2nd most valuable company in the world or whatever it is today. But, like, we still don't see it will probably stop at some point. It's we still got a little ways before that actually happens.

Jordan Wilson [00:34:34]:
Alright, Mike. So I have 1 or 2 quick follow ups on this that I I really wanna get to, but but real quick, I have to shout out one more time our partners from Microsoft and the WorkLab podcast. So why should you listen to the WorkLab podcast from Microsoft? It explores the questions business leaders are asking. How can they guide their organizations on their AI adoption journeys? How can the technology help them create new products and business models and maximize value? How should they help their teams reskill in the new era of work? Why is it important to be completely transparent about when and how you utilize AI? Well, find the answers on the WorkLab podcast. That's worklab, no spaces, available wherever you get your podcasts. Alright. Thanks again to our, friends at Microsoft for sponsoring the Everyday AI Show. But I wanna follow-up on something that you said there real quick, Mike.

Jordan Wilson [00:35:29]:
I know we've already, been been all over the place, but I I love this. So, you know, you kind of talked about scaling laws. Right? And they're actually getting, like, the, like, the rate of technology and the rate of of of compute is is far out, like, exceeding what we thought scaling laws would limit us to. More and more money is is being poured into GPUs, NPUs, quantum, etcetera. Right? And now we have agents. Right? In literally any day now, we're going to have autonomous AI agents that you can build with natural language, right, from, Salesforce and their agent force and then from, Microsoft, that announced their copilot studio autonomous AI agents. Right? So this is all happening very fast. And when you talk about innovation and starting a company, right, I wanna go there now.

Jordan Wilson [00:36:20]:
If you were, starting a new company today or if you were a business leader that needed to start a new line of business, a new line of revenue, Where would you be looking? Because everything's happening so freaking fast.

Mike Todasco [00:36:34]:
Yeah. You know, I think am Bezos, when he was still running Amazon, would kinda talk about what are the things that are not going to change in the next 5 or 10 years. And it was things like, customers are gonna want their products faster. So, like, like, delivery time is, you know, that's not going to change. They're probably gonna want lower prices. That's not going to change. But, like, everything else is kind of up in the air. And and that's where I would kind of start.

Mike Todasco [00:37:03]:
1st principles of, like, okay, who is it that you're serving today, or who is it you wish to serve? And, you know, if you're starting a new business, you never want to fall in love with your product. You want to fall in love with your customer and, specifically, with solving the specific problem that your customer has. This has to be a burning need, burning desire. And when you have that, that becomes an unfair advantage for you. Whenever if there's something that you obsess about all the time, that then becomes an advantage that no big company, no other start up, no nothing else out there can compete with. And so if I'm a small if I'm looking to start a small business, that's the first thing I'm seeing. Like, where do where's the thing that I am obsessed about that I want to solve a problem that exists out there in the world? And if you're listening to me say this right now and you don't know what that is, that's okay. I would ask ChatCPT.

Mike Todasco [00:38:00]:
I would ask Copilot. I would go into one of these tools and say, hey, I'm looking to start a new business. Is this help me I'm I wanna be obsessive about something. Can you walk me through this? Ask me a bunch of questions. Help me find the thing that the problem out there in the world that's not solved that I can uniquely solve in some way. And do you know what? I bet you in a 30 minute discussion with 1 of the AI models, you're gonna actually have, like, those are, like, 3 ideas that I want to explore. So that's the first thing that I would say is, like, so if you are obsessing about whatever that is, that's the starting point. And then, Jordan, I forgot.

Mike Todasco [00:38:38]:
What was the rest of the question? I totally went on a tangent there, didn't I?

Jordan Wilson [00:38:41]:
No. No. I mean, you you crashed the first half. Right? Like, what would you do if you were because we started to talk a little bit about AI agents and scaling laws and all these things that are happening and starting new businesses. But then I said, what about for those listening that are in charge of driving new areas of revenue for their current company? Right? Because I'm sure there's so many businesses. Actually, if you think about it, I don't know what businesses out there can't create new lines of revenue because of the the the innovation and the creativity and the strategy that all these large language models are bringing, especially when we talk about autonomous AI agents. But, yeah, maybe what should leaders, who are working in a certain department, how can they be looking to innovate with AI to create new lines of business?

Mike Todasco [00:39:26]:
So the one thing I would say is never be afraid to start too small. And that is something that I don't think most businesses truly follow. Let let me give an example. I I know and and it's funny. They're in the headlines for other reasons now, but the folks who started character dotai were, I believe, on the Google Brain team. And one of the reasons they left Google Brain is because they wanna do some kind of fun, interesting things with character dotai, and that was like Google's like, that's not gonna move the needle for us. That's not interesting enough. And, frankly, when you get into larger companies, that comes up all the time.

Mike Todasco [00:40:03]:
I I couldn't tell you how many times I heard that within PayPal. They're kind of like, unless it's gonna produce a $100,000,000 of revenue, we're not interested. And I think that is the first thing that you need to move away from in your business. That's, you know, let's just say you are a a a business that does $10,000,000 of revenue, and somebody comes up to you with an idea for, hey. I think this could maybe produce $25,000 of revenue in the 1st year. Your initial reaction is like, that's not even worth what we're paying the people that are gonna be building this. The way you gotta look at that is, like, okay. We we do need to place bets in all these different places, and we need to see what our own core competencies are, what our customers' needs are.

Mike Todasco [00:40:49]:
And then in this new future, we don't know where things are going to go. And this is something that, again, I think, this is, like, one of the downfalls of innovation in larger companies whenever they start to push those things away because then all of a sudden, startups create, you know character AI was not thought to be a bit it's and for folks who don't know, it is effectively a way to talk to it's a way a bunch of teenagers talk to online, avatars. And they will it's literally, I think, in the top five trafficked Mhmm. AI websites or something. It's crazy. I tried it once. I don't get it. I'm I'm 47 years old.

Mike Todasco [00:41:26]:
I'm way too damn old for that thing. But the the kids, like, they got their AI friends on there.

Jordan Wilson [00:41:30]:
Yeah. They love it.

Mike Todasco [00:41:32]:
But but yeah. For but for businesses, like, that's the one thing I would say. Like, don't worry about it being too small. Like, remove that constraint you have in your brain for size and just know that you gotta place bets in different places. There are different ways to do this. Maybe you do it through like some outside like almost like a venture fund type investments. There are different ways to do that. Yes.

Mike Todasco [00:41:54]:
It is going to be a bit of a distraction, but it's going to help you learn so much more. And when you start to look at these things, you truly don't know how these things, these little bets are going to bubble up in the next 5 years.

Jordan Wilson [00:42:07]:
Alright. So, Mike, we've covered so much. Right? Yeah. Generally generally, we these podcasts are a little shorter, but we just we like, I was having fun. I wanted to keep going. Right. We go. You know, as as we wrap it up here, maybe what's your one most important takeaway? This is something I always ask our guests.

Jordan Wilson [00:42:22]:
So what's your one most important takeaway on, how nontechnical, people can really use AI to be innovative even if that's not their, you know, big skill set? What's that big takeaway?

Mike Todasco [00:42:37]:
Yeah, Jordan. I I would say I end every presentation that I give to students in the AI on this, and this is me talking to a bunch of, like, 18 to 24 year olds. The thing I tell them is to embrace their inner child, and that's what I'm gonna tell all of your listeners as well. With these tools, you've got to just you gotta be afraid unafraid to look dumb, to ask a dumb question, to get something that's not going to give you the response that you wanted to give. You got to experiment. You gotta just try all of these things out. You gotta know that maybe if you tried to do something today, 3 months from now, when these models improve, it's gonna give you a totally different answer. I think too often people will say, you know, they'll put in a query in the ChatGPT about something where they have a lot of knowledge, where they know a whole bunch about, and they're like, you know, I got 10% of this wrong.

Mike Todasco [00:43:32]:
Like, I don't trust this thing. Well, like, here's the real like, if anybody I I forget that there's a name for this. Like, if you've ever read, like, a newspaper article about yourself or anything you know deeply about by that's written by a generalist, there's always a bunch of things that's wrong. Like like, I mean, it is just how these things go and, like, you know, what the first time you kind of see that in life, you're like, oh, that gives you an entirely new perspective. But this is how things have always been. There's shortcuts taken. There's things that are misunderstood or reinterpreted again and again, and, like, things are always going to be somewhat wrong. If you're dismissive of that and just say, like, well, it got a little bit wrong today.

Mike Todasco [00:44:09]:
I'm not even gonna bother with this. Or maybe even got a whole bunch wrong. I'm not gonna bother with this. Like, that's not what a kid would do. It could be kid would look at him and say, like, okay. I I tried to play with this build these blocks up here this way. That didn't work. I'm gonna try and build it this way, and that's what you gotta do.

Mike Todasco [00:44:24]:
So embrace that inner child, and I I think that is something that could benefit us all, not only with AI, just in life in general. Such

Jordan Wilson [00:44:33]:
such great takeaways from someone who's been there and is helping us all get to a better, more creative, and more innovative, place with AI. So, Mike, thank you very much for taking time out of your day to join the Everyday AI Show. We really appreciate it.

Mike Todasco [00:44:50]:
Thanks, Jordan. It was a lot of fun.

Jordan Wilson [00:44:52]:
And, hey, as a reminder, y'all, we covered a whole lot there. Don't worry if you weren't able to accurately take down every single piece of knowledge that Mike dropped on our heads. That's what I do. I'm a human. I'm gonna go back, relisten to this, and type up a newsletter with my bare hands. It's old school. So, if if you enjoyed this, please make sure to tell someone about it, and also go to your everydayai.com. Sign up for that free daily newsletter where we will be recapping all of the highlights from today's show as well as keeping you up to date with everything else that you need to know.

Jordan Wilson [00:45:24]:
So thank you for tuning in. Please join us tomorrow and every day for more everyday AI. Thanks, y'all.