Ep 303: What the AI experts are getting wrong (and right) about AI. Chicago AI Week recap

Accelerating Business Innovation With AI

Safety and preparedness underline the unprecedented innovation boom in the realm of AI, particularly in the United States. Businesses are now thinking beyond simple integration to become "AI first", even "AI native" companies, demonstrating generative AI's increasingly integral role in enterprise.

AI Expertise: Attributes and Fallacies

AI specialists undoubtedly shine in their respective fields. However, the emergence of AI generalists—who possess broad understanding across a range of AI facets—highlight a growing need. The gap today lies not in specialized knowledge, but in the lack of professionals possessing broad-based comprehension of AI's intricate landscape.

AI Ethics and Job Reshaping

Shifting dynamics in the job market owing to AI require our immediate attention. Workforce re-skilling and up-skilling are pressing factors to discuss, requiring substantial forethought. A proactive approach is necessary to mitigate the potential implications of AI-driven job displacement and maintain organizational harmony.

Corporate Interest in Generative AI

Following a burgeoning trend, public companies are strategically investing in generative AI to reduce headcounts and bolster stock prices. The alignment of AI use with a company's mission, vision, values, and ethics underpins responsible and sustainable AI adoption.

Beware the Over-Hyped AI Proposals

While many startups build their unique value propositions on generative AI, take heed. Flimsy offerings can lead to sharp wake-up calls when businesses realize their so-called "true value" can be easily undermined. Especially if they're relying on fine-tuned language models and competing with the likes of AI giants—Anthropic and OpenAI.

Back to Basics: Prompt Engineering 101

There's a jarring truth in the industry—many AI experts fare poorly with the basics, like understanding large language models, tokenization, context windows, and transformers. The need for a stronger grasp of prompt engineering is evident.

AI Content Detection—Fact or Fiction?

AI content detection has been in the game for years. However, AI-generated content detection is non-existent, contrary to popular belief. Originality and plagiarism in AI content detection are critical, but they shouldn't overshadow the importance of understanding the mechanisms deployed.

The Need for Greater Audience Engagement

Active participation from the audience can significantly enhance their insights into the world of AI. Routine engagement can place individuals among the most informed strata in AI conferences. Such interaction includes asking probing questions, tuning into daily updates, and subscribing to informative newsletters.

Achieving an understanding of AI, becoming a part of the conversation, and making informed business decisions is now more accessible than ever. Utilize this resource wisely, share the knowledge and place your company on the leading edge of the AI wave.

Topics Covered in This Episode

1. Innovation in Business and AI
2. Role and Importance of AI Experts
3. Ethical Considerations in AI Implementation
4. Trends in AI Startups and Public Companies
5. Chicago AI Week

Podcast Transcript

Jordan Wilson [00:00:15]:
The AI experts are getting a lot of things wrong when it comes to generative AI. I'm lucky enough to get to go to a couple conferences and I get invited to speak on panels, and I watch just a lot of other people talking about generative AI. If I'm being honest, a lot of experts are getting things wrong consistently over and over. So today, I'm going to talk about that and a little bit more on everyday AI. What's going on y'all? My name is Jordan Wilson, and I'm the host of everyday AI. AI. Sorry. We have some, alright.

Jordan Wilson [00:00:58]:
We have some difficulties there. We have some technical difficulties. Yes. So normally, we do a a daily livestream that goes out to LinkedIn among, among other places. So we have some, some LinkedIn issues today, but no worries. You can still join us on, YouTube, Twitter, all those other places. But everyday AI, it's for you. So daily livestream, when it works, podcasts, and our free daily newsletter helping us all learn and leverage generative AI.

Jordan Wilson [00:01:20]:
So, let's let's just before we get into it, let me throw out a reminder. If you haven't already, go to your everyday ai.com. Sign up for the free daily newsletter. Gonna be recapping today's conversation and a lot more. Alright. But before we get into what AI experts are getting wrong and right about AI, let's first go over what's happening in the world of AI news. So the US is the most prepared country for AI according to a new report. So the International Monetary Fund, the IMF, has released a new report ranking countries based on their readiness to adopt artificial intelligence into their economies.

Jordan Wilson [00:01:56]:
So the report assesses countries on 4 key measures, digital infrastructure, human capital and labor market policies, innovation and economic integration and regulation. So the US and Netherlands lead the chart with a point 77 rating, followed closely by Finland, Estonia, New Zealand, Germany, Sweden, Australia, jap, Japan, and Israel. Alright. So make sure to check out our daily newsletter to find out which of the countries did not make the top list. Alright. Next, AI generated content easily fools university professors according to a new study. So universe, researchers at the University of Reading in the UK conducted a study where AI generated exam answers outperformed real students in online assessments. So the project involves submitting unedited answers created by ChatGPT under fake student identities with most AI answers receiving higher grades than human submissions.

Jordan Wilson [00:02:55]:
This study challenges the traditional methods of educational assessment and raises questions about the future role of AI in academia, which we're gonna be talking about tomorrow, by the way. Also, some people are suggesting that, oh, this is the Turing test all over again. I don't think so. Also, we're gonna talk a little bit more about this actually in today's episode when it comes to AI content detection, but make sure to check out the newsletter for more on this story. Speaking of the newsletter, we snuck this one in, yesterday that came in just after the podcast, but NBC is going to be using an AI voice clone of legendary broadcaster, Al Michaels, for Olympic recaps. So according to reports, NBC plans to employ an artificial, clone of renowned sports broadcaster Al Michaels' voice for narrating daily streaming recaps of the upcoming Summer Olympics in Paris. So the AI generated voice based on Michaels' past appearances on NBC aims to replicate his signature expertise and allocation, providing viewers with a familiar experience. So Michael's was initially skeptical, but then praised the AI version of his voice as astonishing and almost perfect, expressing amazement and a hint of apprehension.

Jordan Wilson [00:04:11]:
So the cloned voice is obviously powered by generative AI and voice synthesis technology will greet viewers by name. So I believe that's gonna be happening online, enhancing the personalization on the your daily Olympic recap on Peacock. So, according to reports, nearly 7,000,000 personalized variants of the recap are expected to be streamed during the games, drawing from NBC's extensive live coverage of the event. Alright. So make sure to go check out our newsletter at your everydayai.com for more on those and to figure out why YouTube is trying to make AI music deals and what Sam Altman just said about GPT 5. Alright. Let's get into it y'all. So, yeah.

Jordan Wilson [00:04:50]:
Normally, we have our, livestream audience, but, yeah, sorry. We don't, our our LinkedIn's not working today. Bummer. But let's just talk about what the AI experts are getting wrong and right, about AI. Alright? And, also, while I'm here talking about this, this is kind of, you know, based based on a recent event. So, I was lucky enough to be invited to the Chicago AI recap. Sorry. Chicago AI week.

Jordan Wilson [00:05:17]:
So doing a little recap of that as well. And I just wanna let people know this most of what I'm talking about here is not just from one, event. Right? I'm lucky enough to get to go to a lot of great conferences, online events, seminars, panels that I, you know, sometimes chair or speak at. So I'm I'm really taking a broader look here, but I realized I had a lot of notes, right, when I go to all these conferences, and I wanted to talk about what people are right about and what people are wrong about because I'm seeing some common recurring trends that I think I just have to call out. And and, hey, shout out shout out to all of our normal, our normal LinkedIn audience joining us on on YouTube here. You know, Jason and Cecilia and Colby and Tara, thank you for joining us, on on the YouTubes. So, yeah, if you have questions, please get them in. But and so yeah.

Jordan Wilson [00:06:07]:
I I was, invited to chair a panel, for Chicago AI Week. So thanks, to Zao Chen, who kind of ran and put this together for inviting me out there. Shout out, Quintin, for this little photo there on Twitter, that I just saw this morning. So let me first just give you a quick recap of Chicago AI Week. Yeah. Like sometimes I don't wanna push Chicago too much. I'm from Chicago. That's where we come to you live every single day.

Jordan Wilson [00:06:34]:
But I think it's worth shouting out. Right? A great event, that that Zhou Chen Zhang put on. I've had Zhou Chen on, the show a couple of times here, on Everyday AI. So Think put together just a great program. So, and also his group, AI 2030, 1871 here in Chicago, a great host. So I wanted to get those things out of the way, and I probably listened to more than 30 startups. You know, AI startups kind of pitch their companies, to kind of a a panel of judges, and I also listen to, dozens dozens of speakers. Great panels.

Jordan Wilson [00:07:15]:
Right? So, panels anywhere from, you know, 3 to I think some of the bigger ones were 6 people. So listen to, experts from companies like, NVIDIA, Microsoft, the IRS, Salesforce, Amazon, IBM, big banks, big consult, consulting firms, etcetera. So basically, all industries were represented there. Also a fantastic, women in AI panel, last night. So shout out to the group for putting that on and and really elevating and highlighting, some of the women doing great work in AI. So with that, quick recap of of Chicago AI Week. Now I wanna zoom out a little bit and talk about what experts are getting wrong about AI. Alright? And, again, I'm not singling out the Chicago AI Week.

Jordan Wilson [00:08:04]:
That's not what I'm talking about. Like I said, lucky enough to get invited to speak on a lot of panels, online events, you know, host things for companies, etcetera. But I've seen so many just recurring things that people are getting wrong. I know it's Thursday. I almost have some hot take Tuesday vibes here. So hopefully, our our live audience and podcast audience is okay with that. But let's just go ahead. I'm just gonna go into what people are getting consistently right first, and then get into what experts are getting, I'd say, consistently wrong.

Jordan Wilson [00:08:42]:
Alright. So what most people, experts are right about when it comes to generative AI. Right? And that's just what I'm talking about. I'm not talking about traditional AI. I'm not talking about, you know, deep learning, machine learning. That's not what I'm talking about. I'm just talking about generative AI. Kind of this recent, you know, boom over the last, 3 years as companies everywhere are scrambling to change how they work.

Jordan Wilson [00:09:08]:
Right? And I think that this is unprecedented, and I don't think anyone could make an argument otherwise. Right? This level of business innovation, especially here in the US. Right? Like, we talked about, that story there at the top of the show, about the US kind of leading in, you know, preparedness, safety, and other things, you know, from this new, IMF study. So I am talking through the lens of the US here. I know we have an international audience. Thank you for tuning in from all over the world, but I think what people are getting right here, the experts are getting right, is the importance of safety. Right? Talks I've listened to, you know, ones I've attended over the last, you know, 3, 6 months. Safety is being rightly spotlighted, and it should.

Jordan Wilson [00:10:00]:
And I love what one of the panelists said, yesterday. I I wish I could shout them out by name. But talking about this concept of not everyone can play offense. Right? And I think it's a great concept to talk about because generally when we talk about generative AI, we talk about things that we can create. We talk about ways that we can, create new business value, ways that we can do things faster, better, cheaper. And that seems to be where most of the conversation around generative AI seems to be focused on because it's easy playing offense. Right? If you're talking about a a sports, everyone wants to be the skill position. Right? If you're football, you wanna be the quarterback, the wide receiver, the running back.

Jordan Wilson [00:10:44]:
You know, if you're basketball, you wanna be the the shooting guard. You wanna be the point guard. You wanna be the oop to the alley. Right? People aren't talking about, you know, oh, the defensive line. Right? People aren't talking about, you know, if if if you turn on, you know, the NBA draft was last night. They're not talking about people's ability to, you know, play play defense and they're, you know, plus minus when they're on the courts, when it comes to, you know, the NBA draft. They're talking about, you know, can you score from all three levels. Right? And I think AI is the same.

Jordan Wilson [00:11:17]:
Right? But I do think people are getting safety right because not everyone can play offense. All right. When it comes to this thing, we need more people playing defense. We need more people talking about safety, but those talking about safety are getting it right, and it is paramount. Right? Especially as we come up here, in the US on our election season. I've said this before, I think AI, generative AI is going to wreak havoc on our election systems. So it's good. Most people talking about safety are getting it right and they are highlighting it and rightfully so.

Jordan Wilson [00:11:52]:
And we do need more people not just playing defense, we need more people talking about defense and talking about the importance. Right? But it's not gonna fill seats. It's not gonna fill seats. Right? The thing that's gonna fill seats is, you know, here's how to create 50 new pieces of content in in 30 seconds with a large language model. That's what's filling seats, but we need more people focused on safety. We need more people focused on risk mitigation. Because whether you want to admit it or not, think about it or not, there's a duplicity to generative AI. It is both something that can create immense value, but it is also something that is inherently dangerous, especially if we don't take the time to understand it.

Jordan Wilson [00:12:42]:
Alright? Another thing experts are getting right on AI is shifting from this talk of integration to AI first. Right. I think at a lot of these conferences, maybe 9 months ago, a year ago or more, some of these earlier ones that, you know, even I attended, so much of the talk was about integration. And, yes, that's still important. Right? It is still an important conversation to have, but at least I think now experts are rightfully so not focused as much on integration and more about being an AI first company, which is great. I think what we need to move to is an AI native company. And instead of, you know, thinking about first, how can we, you know, do this with AI? Do this with generative AI. Right? It's still kind of like a second step, which is fine.

Jordan Wilson [00:13:37]:
Right? But I think we need to move to AI native, where all of our processes, where all of our operations start with generative AI or most of them. Right? I I I mean, I'm not you can't speak blanket across all industries, all sectors, but I I think we also need to take it a step further and go from AI first as in, like, that's your first step to being AI native, like that step 0. Right? Generative AI at at the core, you you know, so we don't have to integrate it with our first step already there, but I think experts are getting that right. You you know, no longer talking about when and if, to implement, but, you know, we're past that, which I think is good. Another thing, I think specialties are shining. There are so many great experts and that's something I love about attending conferences is there are people with deep expertise. Right? All of a sudden, you have people that have been doing this for 20, you know, 20 years sometimes. Right? And maybe 5, 10 years ago, people were were looking at them strangely.

Jordan Wilson [00:14:43]:
Right? Like, say, like, why are you talking about artificial intelligence? Right? I was lucky enough on on my panel talking about, kind of the a the the intersection between AI and and legal tech. Right? I was lucky enough to be able to talk to very choose very smart people who had decades of experience in artificial intelligence. So now, you have people with these specialties that are now shining. Right? It's it's it's a little different. Right? Where, like, even something Cloud or Mobile or Internet. Right? When the Internet first came out, there's very few people that could come out and say, yeah. We've we've been working on this behind the scenes for decades. Right? So artificial intelligence is not new.

Jordan Wilson [00:15:24]:
It's been around for 60 plus years. It's been being used in various sec sectors for many decades. So now you have these people with their specialties shining, and and they can easily translate their very specific expertise and talk about now how generative AI, can we can all take advantage of that. So, I think experts' specialties are shining. And, also, talking about the ethics, Again, I think ethics and safety experts are getting it right. I think we need to take it a step further on ethics, though. I think the conversation that we should be having, which I talk about here on the show all the time, so we need to be talking about what happens when AI works. Right? Yes, ethics are important.

Jordan Wilson [00:16:12]:
We need to get bring in all the key stakeholders, but we need to be talking about what happens when AI works. What happens when your organization sees a 30, 40, 50, 60% increase in productivity? What are you gonna do if you're a public company? How are you gonna deal with the stakeholder pressure? Do you have a rescaling, upskilling plan in place? Right? It's another thing when we talk about ethics that, you know, we always talk about, oh, you know, and there's all these studies. Some of them I agree with their methodology. Some of them I don't. But, you know, a lot of large studies, you know, from the IMF, from the World Economic Forum, you know, are saying, oh, you know, yes. AI is going to, you know, take away tens of millions of jobs, but it's going to create tens of millions, and it's gonna be a net positive. I've said this before. I'm not a doom and gloom person, but I don't care what anyone says.

Jordan Wilson [00:17:13]:
AI will, take away more jobs than it will create. But regardless, AI is going to create tens of millions or 100 of millions of jobs that do not exist. But companies right now do not have great plans in place for upskilling and reskilling. So when we talk about ethics, we don't just need to, you know, have a, you know, this this would be nice. No. You need to have a plan in place. If you don't already have an ethics plan in place on what happens when AI at your organization works, you are behind. What are you gonna be doing with those jobs? How are you gonna be upscale, upskilling, rescaling your employees? How are you educating them? How are you going to retain the good employees? How are you going to fight off stakehold, stakeholder pressure, right? As we see big tech companies, the same companies that are investing 1,000,000,000 or tens of 1,000,000,000 of dollars into AI yet laying off tens of 1,000 of employees.

Jordan Wilson [00:18:17]:
Right? Public companies play follow the leader. So when the biggest tech companies in the world are investing their money in generative AI, but their headcount's going down and their stock price is going up, other public companies are gonna feel that same pressure. So when we talk about ethics, does your generative AI use align with your mission, your vision, your values of your company? Those are going to become, you know, more important than ever. Alright? And you have to have that in place. So those are some of the things that, people are getting right. So some of the things people are getting wrong. A lot. A lot.

Jordan Wilson [00:19:05]:
Even the experts, y'all are getting a lot of things wrong. Let's talk about some of those things. 1st and foremost. Alright. I'm not I'm not picking on any of the startups that we're pitching. Like I said, I I listened to, I don't know, 30 some, over the last, couple of days. So many startups, y'all are in for a rude awakening. I don't understand it.

Jordan Wilson [00:19:34]:
I really don't. Building your your your US p, building your unique sales proposition around such a flimsy such a flimsy value prop. Right? There's still so many so many AI companies that are starting in 2024, you know, quote, unquote AI startups, you know. I'm sure a lot of them, you know, maybe are side projects, you know, just seeing what sticks. Right? I think right now that's a lot of what startups are doing. You know, you throw a new startup at the wall, every week. There's people that do that. They have teams of talented developers.

Jordan Wilson [00:20:12]:
They put a new startup up every week, see what sticks. But, you know, a lot of these startups that I listen to, I felt bad. I felt bad. You have to understand, Right? If you are an AI startup, if you're in venture capital, if you're in private equity, you need to be very careful. Right? And here's why. A common thread that I saw not just at this conference, but a lot of conferences in general. AI startups are putting their true value on something that can be wiped away or is probably, if I'm being honest, is already wiped away. And it's essentially creating, you know, a a large language model for this or a fine tuned model for that.

Jordan Wilson [00:20:53]:
Right? And trying to raise 1,000,000 of dollars and and to, you know, put the future of your company on that, stop doing that. Stop. Right? Again, this is my hot take. This you know, I'm sure there's, you know, a minority of of AI startups out there that can still do this and find great success. I'm not always right, but so many of these are so flimsy. And I just I just wonder. Right? Do people not understand. Right? They think that they're gonna get, you know, 100 of enterprise clients.

Jordan Wilson [00:21:26]:
Oh, we're gonna build a, you know, a large language model for, you know, I don't know, retailers. You know, because retailers need a special large language model. They can't work with Claude. They can't work with OpenAI. They, you know, so we need to raise, you know, $3,000,000 to build a a large language model specifically for retailers. Right? And you throw in all your your buzzwords in there, you know, and, you know, rag, fine tuning, you know, large language models. These models are bad. No, your startup idea is bad.

Jordan Wilson [00:21:58]:
It's terrible. You know, if you think if you think that you're gonna be able to get dozens or hundreds of enterprise customers, I don't think you understand what's happening with large language models. The giant companies are going to squash you. Consider this free advice out there, AI startups, venture VC firms, PE groups working with quote unquote AI powered startups. Can first of all, can we stop just using AI powered blank? Please stop. Right. Big companies are going to squash you. They're They're gonna squash your company.

Jordan Wilson [00:22:33]:
They're going to squash your investment in those startups. Stop creating startups with such flimsy value props. They're not good. Alright? Let's talk about what's happened recently. Anthropic Claude just released projects. Right? Much larger context window. You can train, kind of the, your projects. You can put in your own knowledge base.

Jordan Wilson [00:22:56]:
Alright? GPTs, we already know that from ChatGPT, allows companies to do the same thing. Google Gemini coming out with gems. They announced this not released yet. So we've already seen from Anthropic Claude, this is available. We've seen this available out of GPTs. I think GPTs actually aren't as good as people hope, but the the technology is only going to improve. So, hey, for all you thousands, literally thousands of startups out there who are trying to create, you know, specialized, fine tuned, rag models, you know, specific large language models. Do you really think you can compete with Anthropic? Do you think you can compete with OpenAI? Do you think you can Stop doing this.

Jordan Wilson [00:23:49]:
Come Stop doing this. Come up with uniquely valuable SaaS companies. Come up with uniquely valuable products. Don't have it rely on just one thing. Enough on that. Alright. Another thing. Prompt engineering 101 is so sorely needed.

Jordan Wilson [00:24:11]:
So many, you know, quote, unquote experts. You know? You know, I've aside from listening to, you know, 30 or so different panelists talk, all these startups pitch, I've, you know, even in the last 2 days, had dozens of conversations with leaders, and this goes back. Right? I talk to people on the show almost every day. Right? We have guests about 3 days a week. I've talked to 100 of people. I I I go to these conferences all the time. Prompt engineering 101 is sorely needed. Even, you know, quote, unquote AI experts are getting the basics wrong.

Jordan Wilson [00:24:48]:
Right? Why do I know this? Well, the examples they're talking about, the screenshots they're sharing. Right? Oh, look at look at this response from this model. Right? And, hey, I asked ChatGPT to do this, and I got this response. Well, yeah. If you put in a a 10 word response into ChatGPT, and if you think it's going to, you know, spit out your, your your company's KPIs for the next 3 quarters, you have it wrong. And so many, quote, unquote, AI experts still do not understand how large language models work. They don't understand tokenization. They don't understand context windows.

Jordan Wilson [00:25:27]:
They don't understand transformers. They they don't understand so much. So I also say this as a word of caution. Right? Because when people stay in their specialties, AI experts, it's great. But now, you know, AI experts, quote, unquote, are being asked to talk about more and more things that may not be inside of their specialty, y'all. If there's ever something I don't understand on the show, that's why I bring on experts, right, in their specialties. I've spent thousands of hours talking about large language models prompting. Right? And I'm still not gonna say I am the the the expert.

Jordan Wilson [00:25:59]:
I'm not. Right? But people, companies, you need to be investing into prompt engineering 101. Yes. Models are going to get better. Right? This concept of prompt engineering is going to get easier and more intuitive as models get more capable. However, so much of the future of work is interfacing with large language models. And I think we're gonna see a lot of small language models from big companies for specific purposes. You need to understand how models work, prompt engineering 101.

Jordan Wilson [00:26:32]:
Alright. Also, another thing that I think, well, I don't know if this is something experts are getting wrong, but more, versus just an observation is there's very few generalists out there. Right? I would consider myself a generative AI generalist. Right? I know a little bit about a lot. There's not a lot of people out there. Right? Maybe there's not a market for it yet, but I think it is going to be a in demand market in the future. The ability to be able to speak generative AI. Right? If you're a listener of the show, if if if you read our podcast, you're in good company Or read our podcast, listen to our podcast, read our newsletter, you're in good company.

Jordan Wilson [00:27:11]:
Right? Because I've I've noticed because of great guests that have come on this show, I can speak generative AI fairly well. Right? I can go chair a panel on legal tech, do a pretty good job, because I've spent hours talking to experts, reading, listening. Right? But I've I've noticed there's very few generalists. Right? So when an expert that works in a specific niche gets asked a question that is slightly outside of their niche, sometimes their answer is not very good, which is surprising to me. Yeah. And I've been seeing this for, you know, years. Right? I follow the space very closely. But that's just something important to keep in mind for the average everyday person out there.

Jordan Wilson [00:27:52]:
Right? Just because if you hear someone from a a meta or, you know, a big company, you know, a Google, give a response on something, you need to be careful. You need to say, is this their expertise, or are they just being asked questions about things that are maybe outside of their their scope? Right? You need to be careful. Alright? And also experts out there, you need to start understanding the basics of generative AI 101. Right? You don't need to, you you know, know the ins and outs of, diffusion models, but you need to the difference between a mid journey and a and a DALL E, the basics. Right? You don't have to, you know, be an expert at, you know, chain of thought prompting, but you need to understand the difference between a zero shot and few shot prompting, okay? You need to understand the basics. If you are an AI expert, if you fancy yourself that, if that's the hat you put on in the morning, you need to understand things outside of your specific scope as well. Alright. Some other things that I think experts are getting wrong is there's too much focus on the creation and not enough on the curation or what goes into large language models.

Jordan Wilson [00:29:04]:
I'm talking about large language models. So much of the discussion, even experts, is focused on what you can create with a large language model, which is great. Don't get me wrong. Right? Again, that's what fills the seeds. But I think the conversation needs to be more focused on the curation or what is going in or what is not going into models. Again, your creation and what you are able to produce with generative AI is going to exponentially increase when you understand what goes into it. Again, just another thing that we're getting wrong is, instead of us, business leaders, enterprise companies taking time to understand and explain the black box of generative AI, instead, they're just giving more and more people access to it. Right? Because there's pressure.

Jordan Wilson [00:29:55]:
I get it. Right? Oh, we're, you know, we're paying $60 a month per seat, you know, for this enterprise, model. So we need to just give it to everyone. Okay. Sure. Companies should be hiring us to train them, FYI. But beside that, you need to understand. You need to have people on your team really taking the time to understand models and what is actually going into them, right? Small example, small example.

Jordan Wilson [00:30:22]:
You know, I sat in on a panel on, the future of AI and kind of media and journalism. It's my background. I was a journalist. I was expecting to hear some talk on, as an example, oh, OpenAI's partnerships with Axel Springer, with the Associated Press, with the Financial Times. Right? Because this is impacting. What goes into the model impacts your ability to actually use it. Right? And I think future models, relied on a lot of sources that they maybe are no longer going to have access to, right? Seems like that wasn't really talked about, which is fine, Right? Because we're always talking about what we can create and all the cool things we can create. It's kinda it kinda goes back to this concept of offense versus defense.

Jordan Wilson [00:31:04]:
Right? We need to also talk more about and understand the inputs of these large language models. What is going into them that wasn't there before? What are our next models of the future, not going to be trained on that they previously were, you have to understand the models. Right? It's like no one knows, you know, the Internet. Right? We all know the Internet. Right? Now you connect to you know, you have a service provider. There's you know, or I don't know. Maybe we don't know the Internet very well. You know, but we've had 30 years to to understand it.

Jordan Wilson [00:31:40]:
You don't have 30 years to understand generative AI. You have to commit time and resources for your company to to understand it now. Another thing I think people got wrong, I kinda touched on this, I think AI experts aren't doing a very good job of staying well informed outside of their specialty. Right? Even when it comes to AI news, when when when it comes to, you know, big partnerships, when it comes to things that are impacting, you know, energy, climate, safety, etcetera. It doesn't seem like AI experts are staying well informed, you know, outside of their one very specific specialty. Right? Again, just a general observation from many, many months of attending conferences, listening to, quote, unquote, AI experts speak. But I get it. It's hard.

Jordan Wilson [00:32:32]:
Right? Because there is so much happening in this space. And then last, I think last but not least, what people are getting wrong, and I'll try not to go on a law a a long, rant on this. AI content detection is not real. Let me repeat that, and we kinda talked about this with this, University of Reading study, that we read at the top of the AI news. AI content detection is not real, period. So many companies I mean, experts are are talking about it. You know, there's, you know, startups that are trying to integrate something like this into their products. If you are a decision maker at your business, if you are, in charge of, GenAI implementation, large language model training, whatever, Just know that's not real.

Jordan Wilson [00:33:21]:
There is literally no such thing. That is not how large language models work. Period. Alright? You know, they say, oh, we can detect burstiness, and, you know, no. No. You you you can't. So you you know what? I'll put a challenge out there. Any AI content detection platform, you won't wanna do this, but, we you know, you know, we're we're starting to sell sponsorships here at everyday AI.

Jordan Wilson [00:33:47]:
I will give you a $10,000 sponsorship here on the show. You can get your your your product out to, literally hundreds of thousands of people. We have a pretty wide audience across our podcast, livestream, newsletter, website, etcetera. I will give you a $10,000 sponsorship if you will come on the show and allow me to break your model, guess what? Number 1, you won't do it because I will expose it. Right? There's a reason why OpenAI. Right? There's there's marketing reasons. They they initially put out an AI content, detection platform. I think it was to give people that ease.

Jordan Wilson [00:34:28]:
Right? Oh, it's okay. Right? And then they obviously shut it down because studies found it was less, I I believe, 26 percent accurate. So it was worse than flipping a coin. It was worse than worse than if you asked an animal at the zoo, choose if this is, this if this content is created by AI or not. No such thing. Literally no such thing. Right? Models, yes. There's there's certain trends and patterns, but there's no such thing.

Jordan Wilson [00:34:56]:
Alright? I can both write as a human to sound like an AI model. Right? And I'll say, in an ever changing world of technology, let's join together as we delve into these exciting topics. I can write that. The model is gonna say, oh, AI AI generated. Right? 100%. 100%. But then if you know what you're doing with large language models, which I do. Right? I give talks literally all across the country.

Jordan Wilson [00:35:24]:
Companies pay us a lot of money to teach them how to get ChatTBT to write more like a human. If you Google that, you're probably gonna find everyday AI or myself near the top of the search results. It's my background. I was a journalist, award winning journalist. Yeah. You can do that. Right? You have to understand the tokenization process. You have to understand next token prediction.

Jordan Wilson [00:35:46]:
You have to understand, temperature. You have to understand top p. If you understand those things, you can get a quote, unquote, large language model. This sound extremely human, and to get a 0% content detection score. Right? We did this. We busted every single one about a year ago so, you know, with false positive, false negatives. Not a thing, doesn't exist, right? But companies are trying to do this. There are things, you know, that originality scores, plagiarism scores.

Jordan Wilson [00:36:13]:
Yeah. Those have been around for decades. AI content detection, not a thing. So if you are working at a university, if you're a decision maker, at an enterprise company and you say you need this, right? Oh, we need this to, you know, make sure it's our content's not AI generated. Right? No. No such thing. Yeah. Alright.

Jordan Wilson [00:36:33]:
And we're gonna end today's show, with a little bit of a hot take. Alright. So if you listen to our podcast, if you engage, right, with, the guests, you know, you can come in and when we have guests, you can ask them questions and they'll answer them. If you listen to this podcast daily, if you engage with the guests, if you read our daily newsletter, I'm gonna go ahead and say you are putting yourself in the top 1% of people that attend these AI conferences. Right? Period. I, you know, I go to a lot of these. I listen to the speakers. I talk to the speakers.

Jordan Wilson [00:37:14]:
I talk to, you know, random attendees. I always go go around, network, introduce myself, trying to get get a get a heartbeat of where the general public, where the business public is when it comes to generative AI. If you listen to our show every day, if you engage, come on LinkedIn, ask experts questions. Right? They'll answer them. We might answer them live on the show. Read our daily newsletter. Right? Where we look at the latest studies, we break them down. I'm a human.

Jordan Wilson [00:37:44]:
I write this. I write our daily newsletter. Former, like I said, former, award winning journalist. If you do those things every day, you are putting yourself in the top 1%. Alright? So we always talk about how can we learn AI? How can we leverage it? How can we use it to get ahead in our career? I know I go on rants sometimes, but y'all, we bring you some of the best minds in artificial intelligence on the show, covering topics all across the spectrum. Sales, education, marketing, nonprofit, society, ethics, responsible AI, people who are large language model experts. We cover health care, automotive, robotics. We cover dozens of sectors.

Jordan Wilson [00:38:34]:
The leading experts in the world, we bring you them every single day. So if you can't go to all these conferences and yeah. You can hear me, you know, riff on them, but if you tune in, if you engage, if you read our newsletter every day, you are putting yourself. I'm saying this with confidence. I've talked to, I don't wanna say 1,000, but hundreds of people at all of these conferences. You're putting yourself in the top 1%. So if you wanna know how you can not get left behind but get ahead, I'm letting you know right now. You are in the right place.

Jordan Wilson [00:39:09]:
Alright. That's it for today, y'all. Going over some things AI experts are getting wrong, but also getting right, when it comes to AI. So if this was helpful, please share this with someone. I know our LinkedIn isn't working today. But please share this with someone. Also, if you're listening on the podcast, please, give us a rating and subscribe to the show and go to your everydayai.com. Sign up for the free daily newsletter.

Jordan Wilson [00:39:35]:
I'm I'm signing off now, but I'm gonna go write that newsletter. I'm a human. I'm gonna go write it. So thanks for tuning in. Hope to see you back tomorrow and everyday for more everyday AI.

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