WEBVTT
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All right, so you're ready to get into some Applied AI.
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We're going deep on some of the most popular conversations from last year on Justin Grammon's Conversations on Applied AI podcast.
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Yeah, he had some amazing guests talking about how AI is changing everything.
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For
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sure.
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It's
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pretty wild.
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Like, we should start with John Stanton from Accord.
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Oh yeah.
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They're a non profit, and they're using AI to help people with disabilities get access to services.
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Makes those services a lot easier to navigate.
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Yeah.
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Way easier to understand.
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Like he had this story about building an app that makes all this complex social service information way easier to understand.
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Like plain language, right?
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Plain language.
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Taking all
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that legal jargon and making it something anybody can get.
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It's a game changer.
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Yeah.
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And then the thing that I thought was really fascinating is he was talking about how they're using AI to quantify.
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Social determinants of health.
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Oh, interesting.
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So like, you know, those are things like housing and food security, those kind of things that are traditionally really hard to measure.
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But they're creating a scoring system within their app using AI.
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Wow.
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And so you can imagine having this score, right, and being able to provide personalized support and intervention based on that.
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Tailored assistance, yeah.
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Yeah.
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Wow.
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Really changes the game.
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Okay, so then there's Kevin Liu.
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Uh, associate professor at Ohio State University.
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He was talking about distributed learning and particularly federated learning and decentralized learning.
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Oh, that's a cool area.
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It's really interesting.
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So federated learning, like think of it as like you've got all these, like thousands of mini AI brains all contributing to a larger model.
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Right.
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And he used the example of Google's Gboard.
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Okay.
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Like if the predictive text, you know, as you're typing, how it learns your habits.
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Yeah.
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That's all happening on your device.
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Oh, that's interesting.
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So
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your phone is getting smarter without sending all of your data to Google.
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Right.
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It's
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like, you're getting, you know, your cake and eating it too.
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Yeah.
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But then decentralized learning takes it even further.
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It's like, you know, Get rid of the need for a central server altogether.
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Oh, okay.
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So
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he was talking about how this is like really important for things like autonomous driving.
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Mm hmm.
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Where you've got all these cars that need to be able to learn from each other in real time.
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Right.
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So they don't have time to be like going back and forth to some like central brain.
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Like
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a hive mind, don't they?
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Yeah,
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like a hive mind for cars.
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Yeah.
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So pretty interesting.
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And then he also talked about the challenge of training AI models on low power devices.
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Oh,
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okay.
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Which like opens up this whole other can of worms.
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Yeah.
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Yeah.
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But, like, the potential is there to, like, really revolutionize AI and make it a lot more efficient and a lot more accessible.
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Yeah, that's where it gets really exciting, I think.
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Yeah.
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Okay.
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So, speaking of making AI accessible, we have Lori Ryan.
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Oh, yeah.
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She created loreignite.
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com, and she is all about demystifying AI.
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Oh, that's awesome.
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So like helping people understand AI, helping people embrace AI and not be scared of it.
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Yeah, it can be a little intimidating.
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Like what is it going to
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do to my job?
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Exactly.
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All of that.
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And she really emphasizes that like AI is here to augment Hume y capabilities.
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It's not about replacing us.
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Right,
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right.
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Like her own story is really inspiring, like she started a business using AI.
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Oh.
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And she
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talks about just like diving in and learning as you go.
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That's cool.
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Which is like really inspiring.
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And what I thought was interesting is she talked about how she uses AI to streamline her work.
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Oh, okay.
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So she talked about like, you know, taking meeting transcripts and turning those into training documentation with the help of AI.
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Oh, that's good.
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Because she's using AI to amplify her own effectiveness.
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Wow.
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Very cool.
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Yeah.
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Okay.
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So now let's talk about the ethical considerations around AI.
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Okay.
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So we talked to Rajeev Mukrelia, professor at Minnesota State Mankato.
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Okay.
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And he's a leading voice in this area.
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And
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he really broke down the concept of explainable AI or XAI.
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Yeah, yeah.
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And
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he talked about the importance of transparency, especially in fields like healthcare and finance.
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It makes sense, yeah.
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Where you've got, like, high stakes decisions being made.
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You want to know how the AI is coming to those conclusions.
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Absolutely.
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And he also highlighted the importance of data quality in AI.
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Okay.
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He had a great analogy.
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He said, you know, if you think of a large language model as, like A Lamborghini?
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Mm hmm.
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It might be a really powerful engine, but if you don't have the right fuel and you don't have the right infrastructure, Right.
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It's not going to perform.
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It's not going to go anywhere.
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Exactly.
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That's a great analogy.
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And he was really making a case for CIOs to really invest in data management.
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Yeah.
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To really be able to, like, unleash the power
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of
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AI.
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Makes sense.
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And then he also talked about custom GPTs, which is kind of a fascinating area.
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Oh,
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yeah.
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So, imagine a chatbot that understands.
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The nuances of your specific business.
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Oh, wow.
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That's the kind of like personalized experience that AI can deliver.
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Interesting.
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Okay.
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So let's talk about someone who's on the front lines of AI strategy.
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Tim Bornhold.
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Okay.
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He's all about practical applications.
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Cool.
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So he had a really interesting perspective on how AI is changing the landscape of work.
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And he believes that.
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Um, jobs that require empathy, creativity, what he calls those uniquely human soft skills.
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Um.
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Those are gonna become even more valuable.
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Right.
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He shared a great quote he said, jobs of the past valued strength, jobs of the present value brains, and jobs of the future
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Oh, wow.
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That's a great quote.
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That's from the president of Columbia University, actually.
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Oh, very interesting.
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But it really resonated with me.
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Because it's like, you know, it's suggesting that AI might be shifting our focus away from purely technical skills.
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Yeah.
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And more towards those human qualities that are really hard to replicate.
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Makes
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sense.
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And
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speaking of technical skills, Tim was also talking about how AI is really democratizing software development.
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Uh huh.
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He actually talked about how he Yeah.
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built an app using chat GPT.
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Oh, cool.
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And
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it's significantly sped up the process.
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So, you know, it's amazing to think that now, like people who don't have extensive coding knowledge.
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Yeah.
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Can
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actually bring their ideas to life.
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That's powerful.
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And
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then he also shared a story about using AI to analyze health insurance plans.
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Okay.
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Which is something I think we can all relate to.
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Sure,
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sure.
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Like who really understands their health insurance plan.
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Right.
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But he was able to get a much clearer understanding by just feeding all that information into ChatGPT.
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That's amazing.
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Yeah, so it's like, you know, AI can really help us make more informed decisions.
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It can cut through the noise.
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Exactly.
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Wow.
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He also talked about the importance of prompt engineering.
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Oh, okay.
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Which
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is basically like learning how to talk to AI effectively to get the best results.
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Yeah.
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So he was saying like, you know, don't just tell the AI what to do.
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Okay.
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Ask it questions.
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Uh huh.
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Frame it as a conversation.
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Interesting.
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Instead
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of a, like, search query.
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Right.
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Right.
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Yeah, like a collaboration.
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Exactly.
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And, just like Lori, you know, he's a big advocate for just experimenting and playing around with these tools.
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Makes sense.
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He said, continually be curious, continually be learning, get your hands dirty and play with these things.
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Words to live by.
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Yeah, for sure.
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We've covered a lot of ground here, but we've got a lot more to explore.
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We'll be back shortly to continue our deep dive into the world of AI.
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Looking forward to it.
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It's really interesting how all these different guests are approaching AI from all these different angles.
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Yeah.
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But they all seem excited about the possibilities.
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Yeah, and like Tim in particular had some, um, like some really thought provoking ideas about, like, the evolution of technology.
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Okay.
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He was comparing the rise of AI to, like, the advent of the internet.
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Yeah.
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And mobile phones.
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Yeah.
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You know how those, like, those paradigm shifts, like, really changed the way we live and work?
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Absolutely.
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And
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he was saying, like, you know, those all came with their own challenges, and AI is no different.
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Right.
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Like, we need to be aware of the potential downsides, but also be embracing those opportunities.
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Yeah, for sure.
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It's like, how do we balance those two?
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Right.
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You
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know, he actually told this funny story about how he used DIL E, which is the AI image generator to create this picture of a mermaid doing dishes for her son.
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Oh, that's great.
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That's awesome.
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Yeah.
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It's like, you know, it sounds like something straight out of like a children's book.
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Yeah.
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But it does raise some interesting questions about like, you know, what is creativity in the age of AI?
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Right.
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We were talking about like, is AI going to replace artists?
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Yeah.
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You know, and Tim's view is that true artistry goes beyond what a computer can currently do.
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Okay.
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You know,
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there's something about human emotion and experience and perspective.
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Right.
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That AI just hasn't quite captured.
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Yeah.
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Yeah.
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So.
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He sees AI as like more of a tool for artists.
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Yeah.
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Not a replacement.
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Right.
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You know, it can handle those technical aspects.
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Mm hmm.
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And then like, you know, that frees up human creativity to focus on more of the conceptual and emotional aspects.
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It's like a collaboration,
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right?
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Yeah,
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not a competition.
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I like that.
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And I think like one of the key takeaways from all these conversations is just like AI is evolving so fast.
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Yeah, it really is.
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It's like mind boggling.
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You know, what seems like science fiction today It could be reality tomorrow.
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Absolutely.
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It's crazy.
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Yeah.
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And that's why it's so important to stay curious and keep learning.
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Absolutely.
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You
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know, Tim was encouraging listeners to like, find those little niches that help you explain how to fit these tools into whatever profession or hobby you're trying to improve on.
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Right.
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So it's all about finding those practical applications, like what resonates with you?
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Exactly.
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So if you're feeling overwhelmed by all this AI talk, just like start small, ask questions.
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Yeah.
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Let your curiosity guide you.
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And if you are looking for resources or you want to find a community, I think the Applied AI Nonprofit at, um, AppliedAI.
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M is a great place to start.
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It's a great resource.
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They have a lot of events, workshops.
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They do, yeah.
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A
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whole community of people that are really passionate about AI.
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It's a good place to connect and learn.
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For sure.
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Absolutely.
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And a huge shout out to our sponsors, Lab 651 and Recursive Awesome.
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Yes, thank you.
00:10:14.779 --> 00:10:16.659
You know, they're making this deep dive possible.
00:10:16.669 --> 00:10:17.379
They are, yeah.
00:10:19.629 --> 00:10:26.059
You know, before we move on, like, let's take a moment and just like, think about what we've learned so far we've heard from.
00:10:26.830 --> 00:10:37.460
Experts in social services, education, entrepreneurship, ethics, strategy, like, they've all shed light on different aspects of AI.
00:10:37.509 --> 00:10:38.289
That's true.
00:10:38.309 --> 00:10:46.389
You know, we've explored the potential of AI to empower individuals, make systems more efficient, even enhance our own creativity.
00:10:46.808 --> 00:10:49.539
But we've also, like, you know, we've acknowledged those challenges.
00:10:49.549 --> 00:10:49.730
Right.
00:10:50.075 --> 00:10:53.693
The importance of responsible development and, you know, those ethical considerations.
00:10:53.693 --> 00:10:54.384
Yeah, for sure.
00:10:54.414 --> 00:10:54.563
It's
00:10:54.563 --> 00:10:55.544
a lot to take in.
00:10:55.563 --> 00:10:55.715
Yeah.
00:10:55.715 --> 00:10:59.485
I think the main takeaway for me is, like, AI is not just a technology.
00:10:59.495 --> 00:10:59.845
Yeah.
00:11:00.063 --> 00:11:03.464
It's like this force that's shaping the world in really profound ways.
00:11:03.514 --> 00:11:03.894
Right.
00:11:04.085 --> 00:11:06.153
What stands out to you from all these conversations?
00:11:06.450 --> 00:11:06.940
What?
00:11:07.080 --> 00:11:08.500
What are you curious about?
00:11:10.070 --> 00:11:14.409
We'll be back in a moment to wrap up our deep dive into AI at The Edge and beyond.
00:11:15.379 --> 00:11:20.849
It really is amazing to think about all the different ways that AI is already impacting our lives.
00:11:20.899 --> 00:11:21.789
Oh yeah, totally.
00:11:21.809 --> 00:11:26.100
Even in ways that, like, We probably don't even realize.
00:11:26.500 --> 00:11:26.960
Like,
00:11:26.960 --> 00:11:30.169
it's kind of the, it's the undercurrent of so much these days.
00:11:30.519 --> 00:11:33.989
But like, the thing that really gets me is like, the bigger picture.
00:11:34.078 --> 00:11:34.629
Yeah.
00:11:34.629 --> 00:11:35.519
You know, like, what
00:11:35.528 --> 00:11:37.750
happens as AI continues to evolve?
00:11:37.769 --> 00:11:38.318
Right.
00:11:38.328 --> 00:11:38.489
How
00:11:38.489 --> 00:11:42.360
is it going to shape the future of, like, society?
00:11:42.370 --> 00:11:44.409
Yeah, it's the million dollar question.
00:11:44.409 --> 00:11:45.073
It really is.
00:11:45.304 --> 00:11:49.953
And all of the guests that we've heard from have grappled with that in some way.
00:11:49.964 --> 00:11:50.504
For sure.
00:11:50.544 --> 00:11:56.104
You know, we heard about the potential of AI to solve, like, these global challenges like climate change and disease.
00:11:56.114 --> 00:11:56.354
Yeah,
00:11:56.354 --> 00:12:02.663
it's like we could automate the mundane tasks, make systems more efficient, you know, maybe help us make better decisions.
00:12:02.683 --> 00:12:02.974
Right.
00:12:03.274 --> 00:12:06.404
But at the same time, like, there's that flip side, right?
00:12:06.404 --> 00:12:07.894
Right, there's always a flip side.
00:12:07.894 --> 00:12:09.235
Like, what about job displacement?
00:12:09.495 --> 00:12:13.345
Potential biases, you know, AI being used for harmful purposes.
00:12:13.345 --> 00:12:14.284
For sure, for sure.
00:12:14.335 --> 00:12:15.514
It's that double edged sword.
00:12:15.585 --> 00:12:18.904
Which is why I think it's so important to talk about responsible AI.
00:12:18.904 --> 00:12:21.784
You know, this isn't just about developing cool technology.
00:12:21.793 --> 00:12:27.163
It's about making sure that AI is used ethically and that it benefits everyone.
00:12:27.163 --> 00:12:29.594
Yeah, building systems that are fair and transparent.
00:12:29.684 --> 00:12:30.514
Right, exactly.
00:12:30.514 --> 00:12:31.024
Accountable.
00:12:31.065 --> 00:12:31.914
Accountable.
00:12:31.945 --> 00:12:35.414
And like, that's going to take a conscious effort from all of us, right?
00:12:35.644 --> 00:12:36.105
It will.
00:12:36.115 --> 00:12:40.254
Developers, policy makers, like even everyday users like us.
00:12:40.304 --> 00:12:41.164
Absolutely.
00:12:41.203 --> 00:12:48.534
We all need to be having these conversations about AI and working together to create a future where AI is a force for good.
00:12:48.803 --> 00:12:49.104
Yeah.
00:12:49.404 --> 00:12:51.583
And that's where you come in, you know?
00:12:51.604 --> 00:12:55.644
You've heard these amazing insights and now it's time to take all that knowledge and do something with it.
00:12:55.703 --> 00:12:59.044
Like, ask yourself, what problem are you going to solve?
00:12:59.438 --> 00:12:59.970
Using AI.
00:13:00.269 --> 00:13:01.000
Exactly.
00:13:01.000 --> 00:13:06.240
Like maybe you'll be inspired by John Stanton, you'll find ways to make those essential services more accessible.
00:13:06.250 --> 00:13:06.679
Right.
00:13:06.688 --> 00:13:09.809
Or maybe you'll dive into the world of distributed learning like Kevin Liu.
00:13:09.929 --> 00:13:15.058
Or maybe you're going to be the next Lori Ryan using AI to launch your business.
00:13:15.080 --> 00:13:15.289
Yeah,
00:13:15.289 --> 00:13:16.589
there's so many possibilities.
00:13:16.599 --> 00:13:16.938
Yeah.
00:13:16.938 --> 00:13:20.110
And remember, like, you don't have to be a tech whiz to get started.
00:13:20.370 --> 00:13:22.529
There's so many resources available.
00:13:22.580 --> 00:13:23.169
Yeah, for sure.
00:13:23.318 --> 00:13:26.090
Like, the Applied AI Nonprofit.
00:13:26.134 --> 00:13:28.774
AppliedAI.
00:13:28.774 --> 00:13:28.784
mm.
00:13:28.825 --> 00:13:29.784
Great resource.
00:13:29.794 --> 00:13:30.024
Yeah,
00:13:30.063 --> 00:13:30.654
go check them out.
00:13:30.654 --> 00:13:33.825
They've got events, workshops, a whole community of people.
00:13:33.835 --> 00:13:34.504
Yeah, they do.
00:13:34.514 --> 00:13:34.734
That are
00:13:34.734 --> 00:13:36.014
passionate about AI.
00:13:36.014 --> 00:13:39.024
It's a great place to get connected and learn.
00:13:39.104 --> 00:13:39.684
It is.
00:13:39.703 --> 00:13:44.163
And of course, huge thanks to our sponsors, Lab 651 and Recursive Awesome.
00:13:44.163 --> 00:13:46.044
Yes, thank you so much to our sponsors.
00:13:46.083 --> 00:13:47.073
We couldn't do it without them.
00:13:47.124 --> 00:13:47.293
We
00:13:47.293 --> 00:13:47.913
could not.
00:13:48.323 --> 00:13:51.274
All right, so as we wrap up, let's leave you with this.
00:13:51.904 --> 00:13:54.085
Stay curious, stay engaged,
00:13:54.335 --> 00:13:55.134
keep learning,
00:13:55.245 --> 00:13:56.365
and never stop learning.
00:13:57.034 --> 00:14:02.375
The world of AI is constantly evolving, and it's really up to all of us to shape its trajectory.
00:14:02.384 --> 00:14:03.235
It is, yeah.
00:14:03.264 --> 00:14:09.254
So until next time, keep exploring, keep asking questions, and keep that spark of wonder alive.
00:00:00.040 --> 00:00:02.250
All right, so you're ready to get into some Applied AI.
00:00:02.649 --> 00:00:10.259
We're going deep on some of the most popular conversations from last year on Justin Grammon's Conversations on Applied AI podcast.
00:00:10.599 --> 00:00:14.558
Yeah, he had some amazing guests talking about how AI is changing everything.
00:00:14.589 --> 00:00:14.730
For
00:00:14.730 --> 00:00:15.099
sure.
00:00:15.109 --> 00:00:15.199
It's
00:00:15.199 --> 00:00:15.890
pretty wild.
00:00:15.898 --> 00:00:18.329
Like, we should start with John Stanton from Accord.
00:00:18.379 --> 00:00:18.960
Oh yeah.
00:00:19.140 --> 00:00:24.919
They're a non profit, and they're using AI to help people with disabilities get access to services.
00:00:24.939 --> 00:00:27.489
Makes those services a lot easier to navigate.
00:00:27.554 --> 00:00:28.074
Yeah.
00:00:28.085 --> 00:00:29.484
Way easier to understand.
00:00:29.524 --> 00:00:35.715
Like he had this story about building an app that makes all this complex social service information way easier to understand.
00:00:35.734 --> 00:00:37.014
Like plain language, right?
00:00:37.024 --> 00:00:37.634
Plain language.
00:00:37.634 --> 00:00:37.965
Taking all
00:00:37.965 --> 00:00:40.624
that legal jargon and making it something anybody can get.
00:00:40.765 --> 00:00:41.673
It's a game changer.
00:00:41.715 --> 00:00:42.024
Yeah.
00:00:42.454 --> 00:00:48.395
And then the thing that I thought was really fascinating is he was talking about how they're using AI to quantify.
00:00:48.814 --> 00:00:50.534
Social determinants of health.
00:00:51.164 --> 00:00:52.024
Oh, interesting.
00:00:52.314 --> 00:00:57.984
So like, you know, those are things like housing and food security, those kind of things that are traditionally really hard to measure.
00:00:58.173 --> 00:01:02.215
But they're creating a scoring system within their app using AI.
00:01:02.284 --> 00:01:02.575
Wow.
00:01:03.545 --> 00:01:10.185
And so you can imagine having this score, right, and being able to provide personalized support and intervention based on that.
00:01:10.194 --> 00:01:11.594
Tailored assistance, yeah.
00:01:11.594 --> 00:01:11.905
Yeah.
00:01:12.045 --> 00:01:12.224
Wow.
00:01:12.614 --> 00:01:13.454
Really changes the game.
00:01:13.734 --> 00:01:15.275
Okay, so then there's Kevin Liu.
00:01:15.584 --> 00:01:17.814
Uh, associate professor at Ohio State University.
00:01:17.875 --> 00:01:24.555
He was talking about distributed learning and particularly federated learning and decentralized learning.
00:01:24.665 --> 00:01:26.045
Oh, that's a cool area.
00:01:26.054 --> 00:01:26.715
It's really interesting.
00:01:27.093 --> 00:01:35.155
So federated learning, like think of it as like you've got all these, like thousands of mini AI brains all contributing to a larger model.
00:01:35.204 --> 00:01:35.555
Right.
00:01:35.704 --> 00:01:37.769
And he used the example of Google's Gboard.
00:01:37.969 --> 00:01:38.319
Okay.
00:01:38.329 --> 00:01:41.659
Like if the predictive text, you know, as you're typing, how it learns your habits.
00:01:41.659 --> 00:01:42.019
Yeah.
00:01:42.099 --> 00:01:43.728
That's all happening on your device.
00:01:43.789 --> 00:01:44.618
Oh, that's interesting.
00:01:44.859 --> 00:01:44.969
So
00:01:44.969 --> 00:01:49.099
your phone is getting smarter without sending all of your data to Google.
00:01:49.140 --> 00:01:49.549
Right.
00:01:49.558 --> 00:01:49.659
It's
00:01:49.659 --> 00:01:51.799
like, you're getting, you know, your cake and eating it too.
00:01:51.828 --> 00:01:52.168
Yeah.
00:01:52.289 --> 00:01:54.938
But then decentralized learning takes it even further.
00:01:55.159 --> 00:01:58.609
It's like, you know, Get rid of the need for a central server altogether.
00:01:58.659 --> 00:01:59.149
Oh, okay.
00:01:59.340 --> 00:01:59.450
So
00:01:59.450 --> 00:02:03.478
he was talking about how this is like really important for things like autonomous driving.
00:02:03.489 --> 00:02:03.909
Mm hmm.
00:02:03.969 --> 00:02:07.659
Where you've got all these cars that need to be able to learn from each other in real time.
00:02:07.689 --> 00:02:08.189
Right.
00:02:08.338 --> 00:02:12.338
So they don't have time to be like going back and forth to some like central brain.
00:02:12.338 --> 00:02:12.449
Like
00:02:12.449 --> 00:02:13.248
a hive mind, don't they?
00:02:13.248 --> 00:02:13.459
Yeah,
00:02:13.459 --> 00:02:14.628
like a hive mind for cars.
00:02:14.628 --> 00:02:14.908
Yeah.
00:02:15.609 --> 00:02:16.389
So pretty interesting.
00:02:16.460 --> 00:02:21.959
And then he also talked about the challenge of training AI models on low power devices.
00:02:21.989 --> 00:02:22.109
Oh,
00:02:22.599 --> 00:02:23.159
okay.
00:02:23.438 --> 00:02:26.139
Which like opens up this whole other can of worms.
00:02:26.149 --> 00:02:26.519
Yeah.
00:02:26.520 --> 00:02:26.598
Yeah.
00:02:26.829 --> 00:02:33.500
But, like, the potential is there to, like, really revolutionize AI and make it a lot more efficient and a lot more accessible.
00:02:33.599 --> 00:02:35.569
Yeah, that's where it gets really exciting, I think.
00:02:35.569 --> 00:02:35.849
Yeah.
00:02:36.169 --> 00:02:36.538
Okay.
00:02:36.929 --> 00:02:40.658
So, speaking of making AI accessible, we have Lori Ryan.
00:02:40.669 --> 00:02:41.748
Oh, yeah.
00:02:41.748 --> 00:02:43.179
She created loreignite.
00:02:43.209 --> 00:02:46.688
com, and she is all about demystifying AI.
00:02:47.069 --> 00:02:48.250
Oh, that's awesome.
00:02:48.280 --> 00:02:55.069
So like helping people understand AI, helping people embrace AI and not be scared of it.
00:02:55.239 --> 00:02:57.150
Yeah, it can be a little intimidating.
00:02:57.399 --> 00:02:58.199
Like what is it going to
00:02:58.210 --> 00:02:59.020
do to my job?
00:02:59.020 --> 00:02:59.860
Exactly.
00:02:59.989 --> 00:03:00.449
All of that.
00:03:00.460 --> 00:03:05.560
And she really emphasizes that like AI is here to augment Hume y capabilities.
00:03:05.568 --> 00:03:06.810
It's not about replacing us.
00:03:06.830 --> 00:03:07.219
Right,
00:03:07.250 --> 00:03:07.560
right.
00:03:08.905 --> 00:03:12.965
Like her own story is really inspiring, like she started a business using AI.
00:03:13.094 --> 00:03:13.875
Oh.
00:03:13.905 --> 00:03:14.215
And she
00:03:14.215 --> 00:03:16.675
talks about just like diving in and learning as you go.
00:03:16.794 --> 00:03:17.474
That's cool.
00:03:17.495 --> 00:03:18.943
Which is like really inspiring.
00:03:19.294 --> 00:03:23.324
And what I thought was interesting is she talked about how she uses AI to streamline her work.
00:03:23.383 --> 00:03:24.085
Oh, okay.
00:03:24.344 --> 00:03:31.534
So she talked about like, you know, taking meeting transcripts and turning those into training documentation with the help of AI.
00:03:31.584 --> 00:03:32.424
Oh, that's good.
00:03:32.424 --> 00:03:35.114
Because she's using AI to amplify her own effectiveness.
00:03:35.183 --> 00:03:35.653
Wow.
00:03:36.395 --> 00:03:37.014
Very cool.
00:03:37.025 --> 00:03:37.335
Yeah.
00:03:37.424 --> 00:03:37.805
Okay.
00:03:38.253 --> 00:03:41.655
So now let's talk about the ethical considerations around AI.
00:03:41.745 --> 00:03:42.215
Okay.
00:03:42.723 --> 00:03:46.865
So we talked to Rajeev Mukrelia, professor at Minnesota State Mankato.
00:03:46.944 --> 00:03:47.335
Okay.
00:03:47.754 --> 00:03:49.544
And he's a leading voice in this area.
00:03:50.284 --> 00:03:50.854
And
00:03:50.854 --> 00:03:54.343
he really broke down the concept of explainable AI or XAI.
00:03:54.344 --> 00:03:55.245
Yeah, yeah.
00:03:55.245 --> 00:03:55.375
And
00:03:55.375 --> 00:04:00.544
he talked about the importance of transparency, especially in fields like healthcare and finance.
00:04:00.794 --> 00:04:01.493
It makes sense, yeah.
00:04:01.495 --> 00:04:04.364
Where you've got, like, high stakes decisions being made.
00:04:04.735 --> 00:04:07.014
You want to know how the AI is coming to those conclusions.
00:04:07.025 --> 00:04:07.775
Absolutely.
00:04:08.224 --> 00:04:12.114
And he also highlighted the importance of data quality in AI.
00:04:12.174 --> 00:04:12.474
Okay.
00:04:12.554 --> 00:04:13.304
He had a great analogy.
00:04:13.304 --> 00:04:17.685
He said, you know, if you think of a large language model as, like A Lamborghini?
00:04:17.764 --> 00:04:18.175
Mm hmm.
00:04:18.213 --> 00:04:23.855
It might be a really powerful engine, but if you don't have the right fuel and you don't have the right infrastructure, Right.
00:04:24.555 --> 00:04:25.464
It's not going to perform.
00:04:25.464 --> 00:04:26.305
It's not going to go anywhere.
00:04:26.314 --> 00:04:27.004
Exactly.
00:04:27.014 --> 00:04:28.165
That's a great analogy.
00:04:28.194 --> 00:04:33.435
And he was really making a case for CIOs to really invest in data management.
00:04:33.524 --> 00:04:33.925
Yeah.
00:04:33.944 --> 00:04:36.483
To really be able to, like, unleash the power
00:04:36.874 --> 00:04:36.954
of
00:04:37.435 --> 00:04:37.495
AI.
00:04:37.564 --> 00:04:38.144
Makes sense.
00:04:38.283 --> 00:04:42.084
And then he also talked about custom GPTs, which is kind of a fascinating area.
00:04:42.093 --> 00:04:42.343
Oh,
00:04:42.343 --> 00:04:42.904
yeah.
00:04:43.324 --> 00:04:47.894
So, imagine a chatbot that understands.
00:04:48.264 --> 00:04:51.245
The nuances of your specific business.
00:04:51.293 --> 00:04:51.884
Oh, wow.
00:04:52.394 --> 00:04:55.714
That's the kind of like personalized experience that AI can deliver.
00:04:55.894 --> 00:04:56.754
Interesting.
00:04:56.853 --> 00:04:57.185
Okay.
00:04:57.793 --> 00:05:01.074
So let's talk about someone who's on the front lines of AI strategy.
00:05:01.413 --> 00:05:02.144
Tim Bornhold.
00:05:02.233 --> 00:05:02.624
Okay.
00:05:02.644 --> 00:05:04.363
He's all about practical applications.
00:05:04.464 --> 00:05:04.944
Cool.
00:05:05.134 --> 00:05:10.214
So he had a really interesting perspective on how AI is changing the landscape of work.
00:05:10.934 --> 00:05:12.214
And he believes that.
00:05:12.855 --> 00:05:19.004
Um, jobs that require empathy, creativity, what he calls those uniquely human soft skills.
00:05:19.014 --> 00:05:19.035
Um.
00:05:19.795 --> 00:05:22.214
Those are gonna become even more valuable.
00:05:22.245 --> 00:05:22.504
Right.
00:05:22.514 --> 00:05:31.713
He shared a great quote he said, jobs of the past valued strength, jobs of the present value brains, and jobs of the future
00:05:33.805 --> 00:05:34.625
Oh, wow.
00:05:34.704 --> 00:05:35.625
That's a great quote.
00:05:35.774 --> 00:05:37.915
That's from the president of Columbia University, actually.
00:05:37.915 --> 00:05:39.204
Oh, very interesting.
00:05:39.264 --> 00:05:40.555
But it really resonated with me.
00:05:41.014 --> 00:05:46.903
Because it's like, you know, it's suggesting that AI might be shifting our focus away from purely technical skills.
00:05:46.903 --> 00:05:47.173
Yeah.
00:05:47.264 --> 00:05:50.153
And more towards those human qualities that are really hard to replicate.
00:05:50.153 --> 00:05:50.303
Makes
00:05:50.303 --> 00:05:50.543
sense.
00:05:50.615 --> 00:05:50.774
And
00:05:50.774 --> 00:05:56.384
speaking of technical skills, Tim was also talking about how AI is really democratizing software development.
00:05:56.394 --> 00:05:56.735
Uh huh.
00:05:56.785 --> 00:05:58.319
He actually talked about how he Yeah.
00:05:58.430 --> 00:06:00.439
built an app using chat GPT.
00:06:00.509 --> 00:06:01.040
Oh, cool.
00:06:01.040 --> 00:06:01.170
And
00:06:01.170 --> 00:06:03.348
it's significantly sped up the process.
00:06:03.689 --> 00:06:10.529
So, you know, it's amazing to think that now, like people who don't have extensive coding knowledge.
00:06:10.529 --> 00:06:11.279
Yeah.
00:06:11.298 --> 00:06:11.418
Can
00:06:11.418 --> 00:06:13.298
actually bring their ideas to life.
00:06:13.399 --> 00:06:14.699
That's powerful.
00:06:14.699 --> 00:06:14.778
And
00:06:14.779 --> 00:06:20.185
then he also shared a story about using AI to analyze health insurance plans.
00:06:20.223 --> 00:06:20.735
Okay.
00:06:21.413 --> 00:06:23.043
Which is something I think we can all relate to.
00:06:23.055 --> 00:06:23.293
Sure,
00:06:23.314 --> 00:06:23.735
sure.
00:06:23.754 --> 00:06:25.745
Like who really understands their health insurance plan.
00:06:25.745 --> 00:06:26.194
Right.
00:06:26.283 --> 00:06:32.153
But he was able to get a much clearer understanding by just feeding all that information into ChatGPT.
00:06:32.214 --> 00:06:33.274
That's amazing.
00:06:33.274 --> 00:06:37.653
Yeah, so it's like, you know, AI can really help us make more informed decisions.
00:06:37.673 --> 00:06:38.973
It can cut through the noise.
00:06:39.670 --> 00:06:40.259
Exactly.
00:06:40.269 --> 00:06:40.949
Wow.
00:06:40.959 --> 00:06:43.259
He also talked about the importance of prompt engineering.
00:06:43.269 --> 00:06:44.069
Oh, okay.
00:06:44.069 --> 00:06:44.240
Which
00:06:44.240 --> 00:06:48.908
is basically like learning how to talk to AI effectively to get the best results.
00:06:48.939 --> 00:06:49.579
Yeah.
00:06:49.930 --> 00:06:53.389
So he was saying like, you know, don't just tell the AI what to do.
00:06:53.418 --> 00:06:53.750
Okay.
00:06:53.759 --> 00:06:54.848
Ask it questions.
00:06:55.028 --> 00:06:55.399
Uh huh.
00:06:55.408 --> 00:06:56.870
Frame it as a conversation.
00:06:57.204 --> 00:06:57.564
Interesting.
00:06:57.564 --> 00:06:57.805
Instead
00:06:57.805 --> 00:06:59.725
of a, like, search query.
00:06:59.875 --> 00:07:00.285
Right.
00:07:00.334 --> 00:07:00.584
Right.
00:07:00.584 --> 00:07:01.964
Yeah, like a collaboration.
00:07:02.175 --> 00:07:02.845
Exactly.
00:07:03.274 --> 00:07:08.654
And, just like Lori, you know, he's a big advocate for just experimenting and playing around with these tools.
00:07:08.665 --> 00:07:09.225
Makes sense.
00:07:09.283 --> 00:07:15.064
He said, continually be curious, continually be learning, get your hands dirty and play with these things.
00:07:15.165 --> 00:07:16.423
Words to live by.
00:07:16.454 --> 00:07:17.264
Yeah, for sure.
00:07:17.735 --> 00:07:20.305
We've covered a lot of ground here, but we've got a lot more to explore.
00:07:20.774 --> 00:07:24.204
We'll be back shortly to continue our deep dive into the world of AI.
00:07:24.543 --> 00:07:25.644
Looking forward to it.
00:07:26.115 --> 00:07:31.663
It's really interesting how all these different guests are approaching AI from all these different angles.
00:07:31.723 --> 00:07:32.074
Yeah.
00:07:32.103 --> 00:07:34.603
But they all seem excited about the possibilities.
00:07:34.704 --> 00:07:42.343
Yeah, and like Tim in particular had some, um, like some really thought provoking ideas about, like, the evolution of technology.
00:07:42.425 --> 00:07:42.834
Okay.
00:07:42.915 --> 00:07:47.615
He was comparing the rise of AI to, like, the advent of the internet.
00:07:47.783 --> 00:07:48.194
Yeah.
00:07:48.235 --> 00:07:49.384
And mobile phones.
00:07:49.394 --> 00:07:49.495
Yeah.
00:07:49.495 --> 00:07:53.985
You know how those, like, those paradigm shifts, like, really changed the way we live and work?
00:07:53.995 --> 00:07:54.584
Absolutely.
00:07:54.644 --> 00:07:54.774
And
00:07:54.774 --> 00:07:58.254
he was saying, like, you know, those all came with their own challenges, and AI is no different.
00:07:58.365 --> 00:07:58.584
Right.
00:07:58.584 --> 00:08:03.904
Like, we need to be aware of the potential downsides, but also be embracing those opportunities.
00:08:04.319 --> 00:08:05.149
Yeah, for sure.
00:08:05.180 --> 00:08:06.660
It's like, how do we balance those two?
00:08:06.689 --> 00:08:07.089
Right.
00:08:07.110 --> 00:08:07.220
You
00:08:07.220 --> 00:08:17.120
know, he actually told this funny story about how he used DIL E, which is the AI image generator to create this picture of a mermaid doing dishes for her son.
00:08:17.259 --> 00:08:18.000
Oh, that's great.
00:08:18.444 --> 00:08:19.103
That's awesome.
00:08:19.124 --> 00:08:19.343
Yeah.
00:08:19.343 --> 00:08:22.454
It's like, you know, it sounds like something straight out of like a children's book.
00:08:22.454 --> 00:08:22.803
Yeah.
00:08:23.514 --> 00:08:28.923
But it does raise some interesting questions about like, you know, what is creativity in the age of AI?
00:08:28.973 --> 00:08:29.125
Right.
00:08:29.125 --> 00:08:32.725
We were talking about like, is AI going to replace artists?
00:08:32.774 --> 00:08:33.254
Yeah.
00:08:33.524 --> 00:08:40.453
You know, and Tim's view is that true artistry goes beyond what a computer can currently do.
00:08:40.604 --> 00:08:40.964
Okay.
00:08:40.974 --> 00:08:41.104
You know,
00:08:41.104 --> 00:08:44.514
there's something about human emotion and experience and perspective.
00:08:44.524 --> 00:08:44.764
Right.
00:08:44.884 --> 00:08:46.884
That AI just hasn't quite captured.
00:08:46.884 --> 00:08:46.994
Yeah.
00:08:46.995 --> 00:08:47.345
Yeah.
00:08:47.355 --> 00:08:47.534
So.
00:08:47.820 --> 00:08:53.000
He sees AI as like more of a tool for artists.
00:08:53.100 --> 00:08:53.559
Yeah.
00:08:53.879 --> 00:08:54.919
Not a replacement.
00:08:54.929 --> 00:08:55.289
Right.
00:08:55.330 --> 00:08:57.168
You know, it can handle those technical aspects.
00:08:57.168 --> 00:08:57.418
Mm hmm.
00:08:57.470 --> 00:09:02.788
And then like, you know, that frees up human creativity to focus on more of the conceptual and emotional aspects.
00:09:04.125 --> 00:09:05.174
It's like a collaboration,
00:09:05.184 --> 00:09:05.455
right?
00:09:05.455 --> 00:09:05.693
Yeah,
00:09:06.105 --> 00:09:07.125
not a competition.
00:09:07.245 --> 00:09:08.134
I like that.
00:09:08.644 --> 00:09:14.933
And I think like one of the key takeaways from all these conversations is just like AI is evolving so fast.
00:09:14.965 --> 00:09:16.154
Yeah, it really is.
00:09:16.215 --> 00:09:18.634
It's like mind boggling.
00:09:18.684 --> 00:09:22.750
You know, what seems like science fiction today It could be reality tomorrow.
00:09:22.759 --> 00:09:23.448
Absolutely.
00:09:23.448 --> 00:09:24.269
It's crazy.
00:09:24.279 --> 00:09:24.710
Yeah.
00:09:24.750 --> 00:09:27.659
And that's why it's so important to stay curious and keep learning.
00:09:27.688 --> 00:09:28.139
Absolutely.
00:09:28.149 --> 00:09:28.240
You
00:09:28.240 --> 00:09:36.278
know, Tim was encouraging listeners to like, find those little niches that help you explain how to fit these tools into whatever profession or hobby you're trying to improve on.
00:09:36.340 --> 00:09:36.779
Right.
00:09:36.818 --> 00:09:40.149
So it's all about finding those practical applications, like what resonates with you?
00:09:40.198 --> 00:09:41.198
Exactly.
00:09:41.669 --> 00:09:46.639
So if you're feeling overwhelmed by all this AI talk, just like start small, ask questions.
00:09:46.649 --> 00:09:47.159
Yeah.
00:09:47.169 --> 00:09:48.879
Let your curiosity guide you.
00:09:49.099 --> 00:09:57.359
And if you are looking for resources or you want to find a community, I think the Applied AI Nonprofit at, um, AppliedAI.
00:09:57.369 --> 00:09:58.589
M is a great place to start.
00:09:58.869 --> 00:09:59.928
It's a great resource.
00:09:59.979 --> 00:10:01.779
They have a lot of events, workshops.
00:10:01.779 --> 00:10:02.519
They do, yeah.
00:10:02.519 --> 00:10:02.578
A
00:10:02.578 --> 00:10:05.538
whole community of people that are really passionate about AI.
00:10:05.719 --> 00:10:07.639
It's a good place to connect and learn.
00:10:07.649 --> 00:10:08.078
For sure.
00:10:08.169 --> 00:10:08.759
Absolutely.
00:10:08.769 --> 00:10:13.419
And a huge shout out to our sponsors, Lab 651 and Recursive Awesome.
00:10:13.438 --> 00:10:14.399
Yes, thank you.
00:10:14.779 --> 00:10:16.659
You know, they're making this deep dive possible.
00:10:16.669 --> 00:10:17.379
They are, yeah.
00:10:19.629 --> 00:10:26.059
You know, before we move on, like, let's take a moment and just like, think about what we've learned so far we've heard from.
00:10:26.830 --> 00:10:37.460
Experts in social services, education, entrepreneurship, ethics, strategy, like, they've all shed light on different aspects of AI.
00:10:37.509 --> 00:10:38.289
That's true.
00:10:38.309 --> 00:10:46.389
You know, we've explored the potential of AI to empower individuals, make systems more efficient, even enhance our own creativity.
00:10:46.808 --> 00:10:49.539
But we've also, like, you know, we've acknowledged those challenges.
00:10:49.549 --> 00:10:49.730
Right.
00:10:50.075 --> 00:10:53.693
The importance of responsible development and, you know, those ethical considerations.
00:10:53.693 --> 00:10:54.384
Yeah, for sure.
00:10:54.414 --> 00:10:54.563
It's
00:10:54.563 --> 00:10:55.544
a lot to take in.
00:10:55.563 --> 00:10:55.715
Yeah.
00:10:55.715 --> 00:10:59.485
I think the main takeaway for me is, like, AI is not just a technology.
00:10:59.495 --> 00:10:59.845
Yeah.
00:11:00.063 --> 00:11:03.464
It's like this force that's shaping the world in really profound ways.
00:11:03.514 --> 00:11:03.894
Right.
00:11:04.085 --> 00:11:06.153
What stands out to you from all these conversations?
00:11:06.450 --> 00:11:06.940
What?
00:11:07.080 --> 00:11:08.500
What are you curious about?
00:11:10.070 --> 00:11:14.409
We'll be back in a moment to wrap up our deep dive into AI at The Edge and beyond.
00:11:15.379 --> 00:11:20.849
It really is amazing to think about all the different ways that AI is already impacting our lives.
00:11:20.899 --> 00:11:21.789
Oh yeah, totally.
00:11:21.809 --> 00:11:26.100
Even in ways that, like, We probably don't even realize.
00:11:26.500 --> 00:11:26.960
Like,
00:11:26.960 --> 00:11:30.169
it's kind of the, it's the undercurrent of so much these days.
00:11:30.519 --> 00:11:33.989
But like, the thing that really gets me is like, the bigger picture.
00:11:34.078 --> 00:11:34.629
Yeah.
00:11:34.629 --> 00:11:35.519
You know, like, what
00:11:35.528 --> 00:11:37.750
happens as AI continues to evolve?
00:11:37.769 --> 00:11:38.318
Right.
00:11:38.328 --> 00:11:38.489
How
00:11:38.489 --> 00:11:42.360
is it going to shape the future of, like, society?
00:11:42.370 --> 00:11:44.409
Yeah, it's the million dollar question.
00:11:44.409 --> 00:11:45.073
It really is.
00:11:45.304 --> 00:11:49.953
And all of the guests that we've heard from have grappled with that in some way.
00:11:49.964 --> 00:11:50.504
For sure.
00:11:50.544 --> 00:11:56.104
You know, we heard about the potential of AI to solve, like, these global challenges like climate change and disease.
00:11:56.114 --> 00:11:56.354
Yeah,
00:11:56.354 --> 00:12:02.663
it's like we could automate the mundane tasks, make systems more efficient, you know, maybe help us make better decisions.
00:12:02.683 --> 00:12:02.974
Right.
00:12:03.274 --> 00:12:06.404
But at the same time, like, there's that flip side, right?
00:12:06.404 --> 00:12:07.894
Right, there's always a flip side.
00:12:07.894 --> 00:12:09.235
Like, what about job displacement?
00:12:09.495 --> 00:12:13.345
Potential biases, you know, AI being used for harmful purposes.
00:12:13.345 --> 00:12:14.284
For sure, for sure.
00:12:14.335 --> 00:12:15.514
It's that double edged sword.
00:12:15.585 --> 00:12:18.904
Which is why I think it's so important to talk about responsible AI.
00:12:18.904 --> 00:12:21.784
You know, this isn't just about developing cool technology.
00:12:21.793 --> 00:12:27.163
It's about making sure that AI is used ethically and that it benefits everyone.
00:12:27.163 --> 00:12:29.594
Yeah, building systems that are fair and transparent.
00:12:29.684 --> 00:12:30.514
Right, exactly.
00:12:30.514 --> 00:12:31.024
Accountable.
00:12:31.065 --> 00:12:31.914
Accountable.
00:12:31.945 --> 00:12:35.414
And like, that's going to take a conscious effort from all of us, right?
00:12:35.644 --> 00:12:36.105
It will.
00:12:36.115 --> 00:12:40.254
Developers, policy makers, like even everyday users like us.
00:12:40.304 --> 00:12:41.164
Absolutely.
00:12:41.203 --> 00:12:48.534
We all need to be having these conversations about AI and working together to create a future where AI is a force for good.
00:12:48.803 --> 00:12:49.104
Yeah.
00:12:49.404 --> 00:12:51.583
And that's where you come in, you know?
00:12:51.604 --> 00:12:55.644
You've heard these amazing insights and now it's time to take all that knowledge and do something with it.
00:12:55.703 --> 00:12:59.044
Like, ask yourself, what problem are you going to solve?
00:12:59.438 --> 00:12:59.970
Using AI.
00:13:00.269 --> 00:13:01.000
Exactly.
00:13:01.000 --> 00:13:06.240
Like maybe you'll be inspired by John Stanton, you'll find ways to make those essential services more accessible.
00:13:06.250 --> 00:13:06.679
Right.
00:13:06.688 --> 00:13:09.809
Or maybe you'll dive into the world of distributed learning like Kevin Liu.
00:13:09.929 --> 00:13:15.058
Or maybe you're going to be the next Lori Ryan using AI to launch your business.
00:13:15.080 --> 00:13:15.289
Yeah,
00:13:15.289 --> 00:13:16.589
there's so many possibilities.
00:13:16.599 --> 00:13:16.938
Yeah.
00:13:16.938 --> 00:13:20.110
And remember, like, you don't have to be a tech whiz to get started.
00:13:20.370 --> 00:13:22.529
There's so many resources available.
00:13:22.580 --> 00:13:23.169
Yeah, for sure.
00:13:23.318 --> 00:13:26.090
Like, the Applied AI Nonprofit.
00:13:26.134 --> 00:13:28.774
AppliedAI.
00:13:28.774 --> 00:13:28.784
mm.
00:13:28.825 --> 00:13:29.784
Great resource.
00:13:29.794 --> 00:13:30.024
Yeah,
00:13:30.063 --> 00:13:30.654
go check them out.
00:13:30.654 --> 00:13:33.825
They've got events, workshops, a whole community of people.
00:13:33.835 --> 00:13:34.504
Yeah, they do.
00:13:34.514 --> 00:13:34.734
That are
00:13:34.734 --> 00:13:36.014
passionate about AI.
00:13:36.014 --> 00:13:39.024
It's a great place to get connected and learn.
00:13:39.104 --> 00:13:39.684
It is.
00:13:39.703 --> 00:13:44.163
And of course, huge thanks to our sponsors, Lab 651 and Recursive Awesome.
00:13:44.163 --> 00:13:46.044
Yes, thank you so much to our sponsors.
00:13:46.083 --> 00:13:47.073
We couldn't do it without them.
00:13:47.124 --> 00:13:47.293
We
00:13:47.293 --> 00:13:47.913
could not.
00:13:48.323 --> 00:13:51.274
All right, so as we wrap up, let's leave you with this.
00:13:51.904 --> 00:13:54.085
Stay curious, stay engaged,
00:13:54.335 --> 00:13:55.134
keep learning,
00:13:55.245 --> 00:13:56.365
and never stop learning.
00:13:57.034 --> 00:14:02.375
The world of AI is constantly evolving, and it's really up to all of us to shape its trajectory.
00:14:02.384 --> 00:14:03.235
It is, yeah.
00:14:03.264 --> 00:14:09.254
So until next time, keep exploring, keep asking questions, and keep that spark of wonder alive.
