The $1 Billion Question: Is Your Research Actually Lying to You?

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The research industry is experiencing a pivotal moment where synthetic data is proving its worth, AI is moving from experimental to essential, and the companies that survive will be those that balance innovation speed with research integrity. This episode reveals why quality trumps scale in synthetic research, how academic partnerships are becoming competitive weapons, and why Walmart's AI assistants represent the future of human-machine collaboration.

We're witnessing the birth of specialized research ecosystems where AI agents handle routine work while humans focus on strategy—but only companies that maintain ethical foundations while embracing startup-level agility will thrive in this new landscape.

Many thanks to our producer, Karley Dartouzos. 

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Transcript

Lenny Murphy: And we're live.

Karen Lynch: Hi, everybody. I haven't been here in a long time.

Lenny Murphy: I know. Two weeks. I know. It's crazy. We've missed you. We miss those who tuned into the like spur of the moment solo, you're probably incredibly grateful. Like don't ever do that again. Karen's back. Because Lenny's boring, uh, by himself.

Karen Lynch: So, uh, no, I'm sure it was great. Full disclosure. I didn't catch that episode or one last week although I know they existed. I have been catching up all week. I was out for a long time. And it shows in my brain activity this week also. There are things where I'm like, remind me about this because I really unplugged quite beautifully.

Lenny Murphy: And good. And for the audience, Karen was just showing me a picture from her vacation. We're not going to do that because it's going to make everybody jealous. So it looks like you did have a great time. In a wonderful location, and we're glad that you're back now. Back to the grind.

Karen Lynch: Yeah, no, absolutely. I'll be smiling about my vacation for, you know, for weeks to come, probably, because it was extraordinary. And, you know, full disclosure, I was away with all of my children, including my oldest son with his wife and their baby. So, I met my daughter-in-law's entire family for the first time. So it was like this extraordinary adventure for me.

Lenny Murphy: Do you want to say where? Just give a context.

Karen Lynch: I was in Brazil. I was in Brazil. And so it involved not only being kind of in the city of Sao Paulo, but getting off to the beach because you know, this is me we're talking about. There's really no vacation that doesn't include some sort of beach activity.

Lenny Murphy: You're back jumping into the deep end of the pool because my goodness, it's, it seems to me, I mean, you may be unplugged, but like the last three weeks of just boom, boom, boom. I mean, lots of stuff happening. Lots of the series we've talked about, we condense this down. I know we throw a lot at you, but there's twice as much. Uh, normally we leave on the cutting room floor this week, probably three times as much. So you tell me, are you ready to talk about these things? You're like, Lenny, I'm just still catching up. No, I am.

Karen Lynch: So what's interesting is today my brain has pretty much caught up with things. And actually, it's really good, you talk about vacations being good to kind of mentally refresh with your work. But at the rate of change in the industry and in just the tech specifically, it was really good to take a mental break from all of that also and to kind of come back. And so it feels, actually, everything feels really interesting to me right now because I'm like, oh, because I allowed my brain to step back for a little bit. We really love that. So I, you know, And, you know, and there's also something about, give yourself a break if it feels overwhelming, because then you can come back to it and, you know, have just a different perspective on it. So, you know, and I think we should get right into it, because my big perspective right now, which is some of our lead articles are about the synthetic data, which kind of bubbled up this week. And I don't know that I would have been able to wrangle it quite as well as I can right now, having not thought about synthetic data for, you know, two weeks. So let's go. Yeah, let's go. Let's go. So Qualtrics and Pure Spectrum have partnered to deliver synthetic research capabilities. And what I thought was really interesting about this is, you know, Pure Spectrum selected Qualtrics as its synthetic panel provider. So there's this kind of quid pro quo happening, but it's basically talking about how Qualtrics synthetic model, and this is all in the press release, how synthetic model is built upon their repository of very industry-specific experience data. So Qualtrics, you know, kind of then working with Pure Spectrum, you know, for their kind of trading data and that partnership, I just think it's really interesting that not only are they, have they totally bought in to what we need to do, but they're leveraging their two strong suits to come together to do something great for mutual mutual clients, I just think it's a really interesting partnership. What did you think?

Lenny Murphy: Sorry, I agree. I've been waiting to see something like this, this integration between a platform like Qualtrics, leveraging their data assets on behalf of their customers with augmentation externally, and that's going to change the research process. Obviously, right? No surprise. Synthetic first, exploratory, et cetera, et cetera. Then you go ask questions, you know, using Qualtrics and probably sampling when it's not CX related off of Pure Spectrum.

Karen Lynch: And here's what took me a hot second though, is when I read, when I read in there, um, Pure Spectrum selected Qualtrics as its exclusive synthetic panel provider, my brain did a little like, wait, panel provider? Like, categorizing Qualtrics as a panel provider, I got tripped up, right?

Lenny Murphy: I was like, well, they had talked about doing panel members that they were going to put on. I do not know, maybe they did. And maybe they were working with Pure Spectrum on that piece where they were going to empanelize, you know, folks, I do not know. And they didn't talk about it. But it always made sense. To me for Qualtrics to have that type of capability had been rumored for years of, you know, that maybe they were gonna buy so-and-so or whatever, this seems like they've accomplished the goal of that synthesis and integration without the need to actually do an acquisition at this point. So it's all about the data.

Karen Lynch: Yeah and this idea of synthetic panel suddenly, again this is sort of what I feel like the two weeks distance really did for me, was of course synthetic panel is only gonna be as good as what it's built on. And yes, there are going to be some companies that are going to have a better synthetic data panel than others. And so if you're wanting to shop for a synthetic panel, you're going to be thinking, anyway, it just was one of those, you know, kind of moments where, you know, and then yeah, let's talk about what Ipsos is doing. It's two big players making moves.

Lenny Murphy: Where they've talked about this, there's a Stanford paper on synthetic, not so long ago, where we're effectively the same thing. And I think it's, we need a new term than synthetic. It's a broad bucket category, but what Qualtrics is, you know, and Pure Spectrum and what Ipsos is doing, it is not, oh, let's create a persona off of chat GPT. You know, that is not the case. These are built off of first party data, structured data, data sets, specific, you know, deep profiling of consumers, attitudinal, behavioral, the Ipsos panel, I don't think they called this out specifically, but I suspect that it's off of the, I always forget the name of it, it was the GFK asset that they bought, that is an incredibly high quality panel based off of consumption. So these are, these are, high quality digital personas built, basically digital twins, and that's what Ipsos is called, theirs. I mean, that has, I'm not denigrating, that has its use cases. I would argue that this is far more, far more predictive, far. It's not the same thing as some of the other stuff that's out there that's just pulling off of the internet.

Karen Lynch: I think the Ipsos move, again, this is when I'm super reflective today, friends, so forgive me for wanting to indulge these conversations a little more. The idea that Ipsos is choosing to partner with academia, I think that's really, that is worth taking a moment for because they're bringing in different brains, different level of thinking to how they're going about this, this very mindful approach approach to this, because I feel like for Ipsos, so much of what they're doing is public opinion research, they 100% need to do it right. The stakes are high for them, so they need to bring in this type of thinking. Well, I should point too, both of these depend on, It's kind of where I netted out with this story.

Lenny Murphy: Ongoing data feed. So to your point on public opinion, do I think that that can become highly predictive? I do. As long as it is based on real time, or close to real time, current data as things change, and that's what they're building. And we should, I'm gonna hypothesize for Ipsos, at this point, really effectively the last company standing from the big full serve as global companies, right? I mean, Cantor and Nielsen, everybody else can have done some other stuff. Uh, for them to do this is very indicative of their view on where the industry is going. Um, which probably looks a whole lot more like a subscription business with digital, digital, the synthetic sample first, and then augmenting with real follow-on research, which is probably going to look a lot more qualitative and in-depth. I'm just guessing. I'm trying to get Ben Page to actually do an interview, and maybe we can validate this. But pay attention when a company like Ipsos, a multi-billion dollar global company, is making these moves. That is very indicative of where the market is going. Yeah, yeah.

Karen Lynch: Yeah, for real. And we've been saying for a long time, qualitative validation of synthetic data sets. I don't know if that's the right term, but data that is informed using a synthetic panel, for example, that's going to become very important. So qualitative researchers out there are listening, sorry about that. I'm telling you, it's been grand central. So how would my son know I'm recording live right now if he were to pay any attention to my schedule? Anyway, qualitative researchers should really be thinking about what does that qual look like when you're validating something else? Like, and really focus on your ability to make sure that, because qualitative research is often so expansive, and we go wide so that you can kind of connect dots and threads, but validation, different needs that clients will have. So what are the qualitative skills and capabilities you need to be able to validate what they're seeing, or invalidate what they're seeing? Yeah, absolutely, like, this is just more data, I don't need more data, I wanted something else.

Lenny Murphy: So 100% all the companies that are doing all the qualitative platforms that are there, whether it's community or, you know, online groups, or whatever, that are, they are all going that direction to build have those data assets, the transcript effectively, and feeding that into personas. They're all working on it. I think we got the point, I don't know about you, if you've experimented with this, like reading, read AI in meetings. I will incorporate the transcript often. If I need to do a follow-up and have AI create a persona of the, so fed off of that for my follow-up, Maybe so, you know, I mean that it's maybe So what I'm saying is there's a persona in your system that's based on me. That's not yet. You're complicated. I can't Be nice that's uh, anyway, yeah I Inside joke, kind of, not joke. Things get interesting around here, don't they, sometimes?

Karen Lynch: We live, Brent. We are.

Lenny Murphy: All right, so let's go through these others...

Karen Lynch: You know I kind of do those sorts of things on purpose, just because I like to see... I know, I know. I like to see you turn a little red.

Lenny Murphy: I know, I know.

Karen Lynch: Yeah, let's talk about this next one, because you mentioned... I'm going to bring you back, don't worry. These next two kind of, you know, funding-related stories, I want to get them out there, but I really am anxious to move into some of the new product launches because you talked about the need to be predictive with the research that we're doing and some of the synthetic data we're trying to figure out if it can be predictive. So I want to cover these two funding things, but let's get back to the importance of predictive tools, which is what I see in some of this. So I don't know enough about Harmonia to talk too extensively about their investment from WT3 Global, but on retail and CPG insights.

Lenny Murphy: I read the press release too.

Karen Lynch: And it's vague, right? It doesn't really say, you know, how much of an investment it's, it's, you know, there's something buttoned up about it, but, um, you know, AI powered retail and CPG insights, you know, spoiler alert, uh, doesn't Walmart also, you know, we know what they're doing. Um, we know that this is what's happening, right. Is these, uh, these retail insights and the data, this first, you know, first party data that is coming out of those is important in the future.

Lenny Murphy: Yeah, follow the money. And the same thing. Metaforms, I thought, were interesting. Well, it was a little more clear. Yeah, similar to niche fire and, or sorry, not the fire net. So we've been talking about that for the, uh, and now we're seeing, you know, the emergence of funded platforms, right. Raising a lot of money to create this, these agentic operating systems basically, um, uh, within tailor made for insights. So there's going to, we're, we're going to see a lot more of that. Actually, it's interesting that we are seeing those specific, uh, kind of vertically aligned businesses. Because something's going to happen in procurement or whatever, health care. We'll see very specific ones. Where do they fit into broader solutions? But pay attention. This is the beginning of developing ecosystems of agents that are performing different functions. And we're seeing that play out.

Karen Lynch: And jump ahead. We have a couple of different things that are agent-related. Rival Technology, they are, I'm just going to jump to that bullet, Karley, just so you know, they rolled out a suite of enhancements, including new unstructured data agent, AI smart probe, pixel tracking, WhatsApp survey distribution, but it is all about this kind of agentic work. I also happen to know they're coming to IIX AI talking, demoing some of their agent technology in there. So they are really ahead of the curve in talking about what they're doing and they are so full disclosure.

Lenny Murphy: They're a client. So I just miss out on this, but I would just say what's interesting, everything you said, but there's also another piece of this is, you know, in this, this race that we're seeing of like literally every week, a new thing that in the tech world, they call that shipping, right? Shipping product. I mean, rival pure profile, you know, there's a couple that they're just, they're shipping. Product, they're just not sitting right. They are literally every couple of weeks, a whole new suite of solutions, which speaks to the pace of development is shorter. You can do that. I mean, these guys, they, they, it's not like they've expanded to have a hundred developers or anything. It's still got the core. Um, they're just knocking stuff out really fast because they can, and that is a competitive advantage. Yeah, so it's and so yeah, check out rivals. It's really cool. They're doing some stuff like the Pinterest pixel tracking that's cool, you know Yeah, and not trying to say how awesome the rival is although they are Andrew. I love you. It's a sight there. Because of the buried entry the lift is lower to experiment and try new things because of the development of AI, it gives them a chance to like, hey, that would be cool. You know, let's try that, you know, and expanding use cases and features and capabilities rather than being stuck on this very specific product roadmap. Rival is an example right. Companies can be very agile.

Karen Lynch: And I mean, obviously, you know, one of the reasons why we talk about it or talk about them or talk about this type of behavior is, look, we are predisposed to like insight innovation, right? It's sort of part of how IIX got founded in the beginning, right? So we like this. We get excited by people who are, you know, have this mindset, this innovative mindset where they're going to try new things and not all of them will be successful. Some of them will, and they've got to just keep churning stuff out to see what sticks and what lands.

Lenny Murphy: That's the differentiator.

Karen Lynch: Because they're also competing against startups, right? So there are so many startups, like this time last week, and we can share some of these. I'm like, I don't even know, you know, it's hard to even talk about all the startups in the research space, because there are a lot of them. And these are not necessarily people who have a background in And they're coming out, you know, hitting the ground running. These are people who have a background in And that's who companies that have been out there a while are competing against as well. So anyway.

Lenny Murphy: And there's so many. Well, let's, for a bit, there's a bunch of others, we jumped to Rival because of the agentic component. There are a bunch of other product releases. Let's run through those really quickly. AIBODs, very accurate descriptive names. They're all, again, examples of Screening optimization tools to decide which ideas merit human testing. That's really cool. Ideation platform. That's, duh.

Karen Lynch: Screening, let's rule some ideas out before you go for and do some more testing, I think, I'm like, all right, cool concept, right?

Lenny Murphy: Yep, absolutely. The Perspective AI, so they didn't describe this as agentic, but I would say that it probably is.

Karen Lynch: Sounds agentic, you know, spotted on Product Hunt, an AI research platform that both plans, studies, conducts, and delivers insights. So it's kind of in minutes. Whenever it says in minutes, that leads you to believe there's not necessarily a human slowing that process down. So we'd have to look a little bit more about perspective AI, but it's a great example of a debut product. And then this next one, artificial societies launching AS, a platform using 500,000 AI personas to stimulate societies and predict audience reactions. That also is interesting to me because I'm like, okay, There's a lot going on in our ecosystem right now for you to track, for you to take a look at. This is just a few of the things that Lenny and I might spot during the course of a week, but it goes back to this prediction. The predicting need has always been there, but now we're getting closer with technology to do more prediction. And I think that it's a really exciting time to think about what that means.

Lenny Murphy: I thought that was really cool. Ray Porner called that out as well. I mean, that's almost, uh, years ago there was this idea of agent based modeling. Um, it was used to try and mimic and predict things like call center volume and things like that. So not, not agents where we use it now. Um, and this is, I take that on steroids, but with synthetic samples and you're exploring the scenario planning, uh, for at a macro level, very cool stuff.

Karen Lynch: And hopefully, at a fraction of, using a fraction of your budget, your research spend, to do this first, right? And saving the money for what you really need. So with this first one, with the AI bots, if you're screening ideas first, you don't have to test as many, right? So hopefully then you can get more bang for your buck down the road, because you've done some preliminary work with AI. So the possibilities, I think, are really exciting when you think about all your use cases for these new tools.

Lenny Murphy: Yeah, did we include the link to my Day in the Life post here? I don't think we did. Karley, if you could grab that off of the blog.

Karen Lynch: Grab it, grab it. And not by design for any particular reason. No, I actually really like it. It's on my editor's note. I think it's cool.

Lenny Murphy: I only mentioned it to kind of wrap that up, this idea, right? That was the point. I wrote a blog with AI to kind of, what does this world look like, a few months from now, maybe not a few years, literally a few months, where things like the perspective AI, and as you were saying, that there's just a different workflow, and we're using different tools, and also traditional tools, and what does that look like, So it's an imagination piece, but I think it's grounded on some pretty good stuff. It may be able to just get you thinking, so.

Karen Lynch: Yeah, yeah.

Lenny Murphy: Let me just, I'm just gonna help Karley for 30 seconds, Here's that yes, she got off of the Lincoln so All right, let's call out We always get the name wrong. Is it dick? I think it's David. I'm sorry guys. It's wrong.

Karen Lynch: Call us email us They know it's the I did Mary Schitt's Creek like for me every time I think about it, you know Alex I don't know if you even know what I'm talking about But fans of Schitt's Creek will understand that there's a whole thing about David and the way it's pronounced so every time Every time we trip up on a word that's like that, I'm like, oh, it's so shit-freak. There's David and video research launching Emoliizer, an AI-powered creative testing tool in the Japanese market. But anyway, no, these three, there's kind of three, another kind of three boom, boom, So again, AI-powered creative testing. Amplified introduced creative testing AI. Also trying to get at that, you know, kind of quick creative recommendations. And then InnovateMR upgraded its text analyzer. It's related to this kind of creativity in my brain to detect AI-generated content and deeper contextual analysis. When it comes to creative or content or responses, text analysis, it's like on steroids right now. And so, I don't know, it's just the, to me, that's what struck me is, you know, we're not just talking about earlier stage screening of ideas, which creative ideas, but we're also talking about, you know, kind of this whole idea that this is a skill set that AI has, and we should, it makes so much sense to leverage things like that in this way.

Lenny Murphy: Well, think of it as a qualitative guru, right? I mean, think about these tools. How much time would this have saved, you know, five years ago?

Karen Lynch: It's like, what do you think about this paragraph or this paragraph? Every time I think about it, every time I think about focus Or here's five concepts. And we're the whole idea of not having to do that work for people. Like, what do we think about this tagline? Like, here's a, here's a magazine, which we don't really do that much of anymore, but you know, here's this ad copy line or this ad copy line. Like we're, we're, we're AB testing in a focus group setting, you know, because we're, we're desperate to try to figure out which one's better because our own gut checks aren't the right ones when it comes to quantity and all. Anyway, all of that stuff, like the idea that we can, we can also then kind of analyze the text on the other side of it. It just, it's, yeah. It's financial savings. Don't resist. Lean in.

Lenny Murphy: Before we jump into the big tech developments real quick, I want to actually frame that up. I was in a conversation yesterday, and we were talking about adoption. And what occurred to me was that we're used to one adoption curve. That's not the world that we are in. There's multiple lines now. And there's still, and I think it's around use cases, right? So we're probably 30, 40% now on AI for process use cases from an adoption standpoint. But that ship has sailed. But then off of that, there's a whole other line now that is on revolutionizing not just process, but function. Um, and that's one. And then there's this whole other one where like you're unlocking stuff, which we're going to get you down to the tech developments of like, Holy crap, you could do that. Um, like science fiction. Um, and that's the bleeding edge of things, but they're all running in parallel. Um, which is just, I don't know. I hope you can, you can imagine what I'm talking about. Like imagine three line graphs, right. That is just kind of all stacked. And that's the world that we are in. There's not, it's not just one.

Karen Lynch: So yeah. And there's no escaping this. There's no escaping the tech developments. So no.

Lenny Murphy: So let's, let's go. Because there were a bunch.

Karen Lynch: Cause it's like we're 27 minutes in here. We knew this would have happened, right? Um, so yesterday, you know, open AI announced GPT five. And, um, and then everybody, you know, everybody who's like kind of a, you know, Tim and I talk all the time about being like kind of power users. Of OpenAI's product, ChatGPT, you know, we're anxiously awaiting our upgrade and then to get in and see what it does for you. And at first I was like, okay, I'm upgraded and now I'm not really seeing it, right? But the second you, the second you go into it and you, you recognize that it's choosing the model and it's maybe, it's doing things that show its advanced reasoning and critical thinking even in a basic task. This morning I was looking to try to come up with something. I saw a prompt on LinkedIn and I went in there to try to ask it for a value prop for a product of ours. And what it gave me was so freaking good. And it took my breath away because it did all of this critical thinking without asking me, without coming back and saying, would you like me to look at it this way? And I know that you've done some of that stuff too, but really good stuff. And then another thing that happened when in a different use case, I have a custom GPT and it said to me, I'll in the thread, it said, I'll update my instructions now. And it was like, thank you. Because I didn't have to say, I didn't have to then go in and update the instructions. Therefore, I'm just going to do that without asking her. It said, her next step is going to be to And that's very cool. So like, when you start to level up in the GPTs, if you are a power user, you will start to see it. And if you haven't, you know, that's just one tool, because I think right on the heels of it is all of these other developments. So let's rifle through all this, you know, let's rifle through, go.

Lenny Murphy: Well, did we pull out the other piece on OpenAI though? I don't know if we called that out specifically, just to, in S5 we didn't have to like, It's not just through GPT-5. There was also this open source solution that they released this week That like, you know edge for edge computer like on your phone. So imagine While they're you know, I got two lines, right? I mean, they're progressing forward with the you know, GPT-5 they're also I Assume it's like GPT-4 that is now they're open sourcing and saying now go play with it go do all types of stuff that on your phone, so they continue to push the boundaries across the board.

Karen Lynch: They're all, and we'll talk about these wars, right? We have these, we are seeing wartime plans being executed because it's sort of out of control. But yeah, what's happening is, of course, they're going to be building AI interfaces into every phone, every product, everything. And it's just a matter of who's partnering with whom. So I'm glad I'm not in those boardrooms, because that would be really stressful. Because they also have to take a risk in saying, this is going to be the right platform for our product. There are predictions of exponential new product launches, whether it's your laptops, or your refrigerators, or your whatevers that are going to be built in AI interfaces. I have to tell you, when I was in Brazil, I had to do laundry, and the washer dryer was a two-in-one, and it was all in Portuguese. And these are not words that Duolingo can help me with. That's for sure, right? So, crap, I have to do laundry. I have no idea how to operate this machine. I'm at an Airbnb. And it walked me through step by step exactly what to do. And it was, I was like, thank the good Lord this product I took a picture of the panel and said, chat GPT, you know, Just a matter of time before the interface is right on the washer dryer, right? Where it says, what do you need to do? And I, you know, I type in, I need this look, you know, I need this load of laundry done by tomorrow at two is it'll say gotcha, you know, it's just gonna happen.

Lenny Murphy: Well, next, I'll just be the robots, right? That is because that's, that's next.

Karen Lynch: I don't think we're gonna need robots. I think our machines are gonna be scheduled themselves. I think I think I pulled it out because I was like, we don't have time to talk about it. But sorry, Karley, there was this link to the video with the man in a wheelchair whose micro movements are telling the direction micro movements leading the way and I was like, that's way down a tech trail, we don't need to talk about it. But I think I don't even know that we'll need robots. I think that we're going to have technology where we'll be able to do everything with micro movements, we'll be able to talk to our machines ourselves, we will be robots.

Lenny Murphy: Maybe I saw another one. Guys, I forget them. We'll put it out. I'll post on my LinkedIn or something. But like, yeah, it's like an earbud that is in your control system for micro movements. There was another one that I saw that a guy had put it like, almost like a retainer, you know, that you put in your mouth. And it's just through tongue movements, and you're controlling everything through the freaking tongue movements.

Karen Lynch: Now, and I mean, um, oh, my gosh, it was the physicist that had a lesson doing that. Thank you. Like, we know that technology, that technology has existed. Do you know how much better that will be like, the technology that the lifestyle improves, but also what this means for what our life is like, okay, anyway, let's go on.

Lenny Murphy: So it's a little deeper. Well, Karley, go and put Perplexity launched Comet, Microsoft Edge, and Why do we talk about agents? A couple of weeks ago, I had to buy a new pool robot. I used Perplexity. Compare, contrast, and here's what I'm looking for. It did it all for me, and clicked the button, and I bought it. I mean, it would have taken hours of research to be done in just a couple minutes. Walmart is centralizing AI into super agents, already helping 900,000 associates, so all of that, and here's the real sign of the times. So Walmart, the largest retailer in the world, is leaning into it. And they love data. They're really good at data. Remember our friends at Scintilla, Walmart Data Ventures, they're all in.

Karen Lynch: And, and when you think about this, you know what this means with the associates, just picture it. So picture an associate who's being asked a question from a customer and it's, do we have this in stock? And they've always been able to maybe check a stock by, you know, checking to see what's in stock, but now they won't have to ask. They'll say no. And you know, sometimes they're like, if you, if you're in retail, they'll say, no, we don't have it. Um, maybe the next question would be, does another store have it or, you know, can it, can to my home? There's always these questions. But I imagine the agent will just do all that. And the associate will have all the information they could possibly need without having to... It's going to be streamlined.

Lenny Murphy: Let's do the... On other AI wars, and we'll just get through that really quickly, Google released Gemini 2.5 DeepThink. So it's like a workhorse for So that's out there. Anthropic related or updated Clawed. Clawed Opus 4.1. Again, that's like a lot of developers use that. It's really good. And then Google again, their DeepMind. Genie a 3, world model. Interactive 3D environments from text prompts. I mean, that's still, it still can't do like an hour, right? It takes a few minutes. But I mean, the examples are just insane.

Karen Lynch: So just when it's like, all right, we have this, you know, I talk about like this GP three, GPT five update for open AI, that's going to keep happening with all the platforms. They are all going to keep getting better. Um, and you know, it's, you might have the one that you've leaned into or whatever, for whatever reason, but all of the platforms are going to keep getting better.

Lenny Murphy: They're all just leapfrogging.

Karen Lynch: It is just rolling right along. As much as I love this incremental update, I still need to have use cases where I'm using the other ones also. Now you have a whole new AI tech stack that you have to sort through and figure out what is my use case for everything.

Lenny Murphy: Even the ones that just get better and better. This morning, I continue, even if there hasn't been an update on Grok 4 Grok 4, but yet, it does, which is my favorite right this minute, but it changes. It's better at doing some things today than it was a couple days ago. So there's all this background, we're thinking about updates, but there's also just this expansive capability, and it's true for all of them. Perplexity as well. Perplexity surprised the hell out of me this week. It did something, I was trying to do some segmentation. I didn't expect it to do it, I was just testing it. And it was better than I had seen on others. And there was perplexity. I don't expect perfection to do those types of things, right? But yet it was.

Karen Lynch: Yeah, and let's take this a step back to kind of, okay, we talk high level about tech developments, but what does this mean for the insights and analytics industry, aside from our day-to-day use of them for our roles, or our jobs, or our personal life, or whatever you use it for? There's also this concept, play of, I use such and such research platform, I used to use such and such research platform, but now, so say, I currently use B, I used to use A, but now A has added this AI functionality that might be far superior than what I'm currently using. This is a great time to kind of sit back and reflect and say, is there a better option for me? Or are you truly like, I'm using the team that I'm comfortable with? No shame on that, right? But if you are looking for capabilities, you have to reassess what the capabilities are of different vendors, because those are stepping up. They're getting better and better also.

Lenny Murphy: Well, we can go off on a whole thing on that, but you do bring up a point that I think is... So Carla, I don't know if we have a GRIT logo we can bring up. If not, that's fine. We're in the field with the new GRIT survey right now. I'm going to say something about that in a second. There we go. We're really trying to get a handle on where we are from that adoption standpoint. But there is a, and the drivers of selection. I believe that in this era of life, I don't know what to do. There's so much coming at me. I think trust really is a major asset. So the, so if you, so we may be moving towards an executional model that is more agentic, but trust in the brand, trust in the team of a known entity, I think is, is going to be hugely important. And then the burden on the trusted resources, you also have to make sure that you're maintaining parity. So, um, uh, so it's a really interesting time real quick on the grit stuff. If you were trying to bribe people to take it, knock that shit off. It's not okay. It's never okay. We say it every year. And when we catch you, we actually remove the complete. So you're, So please take You're hurting everything. You're actually going to, we will go through and we see you doing it and we're going to remove the complete. That's what we do, right? Because you're pissing in the well and we got to filter it out and get it out. So guys don't take the survey, but stop the promotional stuff. You're not helping anybody.

Karen Lynch: Knock that shit off, friends.

Lenny Murphy: Knock that shit off. Knock that shit off. That was the second time I've come so close to dropping an F-bomb. So you can know, stop. But we need, please take the survey, because we want to understand where people are on all these topics from an adoption standpoint.

Karen Lynch: And also to everybody else who's kind of listening and thinking, oh, I never thought to do that. Don't do it. But also know that we're on it. We're not going to let people get away with that. That's the real big takeaway is it's, it's a shame, but like, like the team is on it. Nelson works really hard and you will, if, if you do not know Nelson, um, if it's one thing we can say about Nelson, it is that he takes that seriously and hard for the integrity of that, that initiative.

Lenny Murphy: And the way that works, we'll keep the survey complete as long as it's a real person. We just won't count the mentions in the GRIP50. So when we know that you have been, it is all fine. Send it to your network. Please just take the GRIP50, you know, take the survey. Leave it at that. It includes the GRIP50. Don't do anything else. Just put it out there.

Karen Lynch: And most people do.

Lenny Murphy: Most people do, but there's a few, and I'm not, I'm not saying bad motives. It's just, but it does, just contaminates that. One last thing, there was a really interesting article that Microsoft did about the future of work. It's also one of those terrifying things as well, truly. It's worth taking a look at.

Karen Lynch: Implications of generative AI. Good for further reading.

Lenny Murphy: What can be automated will be automated and if there's a task that a person is doing today that doesn't require, you know, a lot of critical thinking and intuition and all those things. It shouldn't be a surprise guys. Um, uh, so take a look at that. This may be our longest one ever. Um, but you're back from vacation. There was a lot.

Karen Lynch: Definitely blame it on me, for the wheel.

Lenny Murphy: No, no, no. I'm not blaming you because I get, I get going as well. But the, uh, uh, And guys we may Actually, it would be great if you comment and let us know because things are just happening so fast again. We leave a lot on the floor. We really do yeah And we want to try and keep this short There's gonna be times if we just try and cover we think it's important. It's gonna go a little bit longer. Let us know if you're like not to keep it 30 minutes. Damn it.

Karen Lynch: I know it's better 30 minutes of a more compact show or we expand it to, you know, 40 42, 42 minutes and 35 seconds, you know, who knows, to cover more. So, we don't wanna, you don't wanna hear us for that long. We could easily talk for an hour, but we don't wanna do so, yeah, theexchangeatgreenbook.org is a great place for that feedback. We'll take it. You know, we've been doing this for about two years.

Lenny Murphy: I know, that's crazy. We have an anniversary coming up.

Karen Lynch: That's nuts. Those two years. It's so hard for me to even fathom that we show up week after week. It's really, and we do this, and it's the highlight of our week, so.

Lenny Murphy: It is, and it's growing, and we thank you for that. By the way, like and subscribe, hit that notification bell if you're on YouTube.

Karen Lynch: Share, encourage others, give us that feedback. Karley, thank you for sharing the email address. We will not just read your releases, we will also read your feedback in there. So yeah, we welcome it. We appreciate it. Bring it on.

Lenny Murphy: Everybody, have a wonderful rest of your Friday and great weekend.

Karen Lynch: Happy Friday and summer. We're deep in August. If you're vacationing, glad you're back.

Lenny Murphy: Bye, everybody.

Links from the episode:

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Google released Gemini 2.5 Deep Think

Anthropic updated Claude Opus to version 4.1

DeepMind unveiled Genie 3