From Advisor to Decision-Maker: AI's Next Power Move

Check out the full episode below! Enjoy The Exchange? Don't forget to tune in live Friday at 12 pm EST on the Greenbook LinkedIn and Youtube Channel!

The line between AI advisor and AI decision-maker is disappearing fast, and in this episode Karen Lynch and Lenny Murphy track it across three fronts: a funding round that reveals what qualitative research is really worth now, a wave of measurement tools racing to keep pace with fragmented attribution, and an AI quietly running inventory decisions in a real store.

Thanks to our producer, Karley Dartouzos. 

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Transcript

Lenny Murphy: Nielsen dropped this morning. There we go. We're live. We were running through the show notes and here we are.

Karen Lynch: It's all good. It's all good. Oh my gosh, Lenny.

Lenny Murphy: That's hilarious. I know. Happy Friday. It's been a heck of a week for you. Glad that you're back and life is stable and good, I guess.

Karen Lynch: Yeah, stable and good. They're all relative terms. Yes. Family. Stable. Stable and good. No, I got a wonderful picture of my grandson in a cast today.

Lenny Murphy: Oh, no. Well, the first, the first cast.

Karen Lynch: The first cast.

Lenny Murphy: Family, first, and last. Oh, what did he do?

Karen Lynch: Do you know what? When I was there, he refused to put weight on his left leg. And so, but it just was the sort of thing that we couldn't quite process what's going on. But they did take him to the doctor yesterday and he had a fractured little leg. And I guess like toddler bones break sometimes. There was no real injury to speak of that anybody knew. But he had a little broken, little baby, broken bone, little baby.

Lenny Murphy: Yeah. Never had the baby broken a bone. I had, but I've had a few, including the worst. I'll tell the story real quick. My daughter fell off a slide. She was three, four. Um, I took her to the doctor. Oh, no, everything's fine. The next day, we went hiking, and Oh, my arm hurts, dad.

Karen Lynch: My dad's like, Oh, shut up, you're fine.

Lenny Murphy: Yeah, I wasn't that me. Go back to the doctor. Oh, no, she did have a fracture, they just didn't catch it the first time.

Karen Lynch: So, you know. Well, that must have been the sort of thing that happened here, there must have been a fall and no, no over, no reaction bigger than maybe just a fall. And then the next day or so stopped putting weight on it. And so it was like, what's going on? Why isn't the baby not putting weight on the leg? But then you know, I had some other reasons, other distractions, to say the least, with my daughter-in-law not being well. So we were like, What's going on? He's particularly clingy. Maybe he just wants to be held. So we were kind of just saying, Maybe he just, you know, misses his mom, wants to be held. And then, you know, just not really sure what to do. And then we were like, well, maybe when, you know, when Isabella gets home. We'll get a better gauge, but still clingy, wanting to be held when she is home. And then it was like, you know, once she was back, they were like, let's go to the doctor because it's not just that anymore. And still doesn't want to put weight on it. And the doctor's like, yeah, that's actually the indication. When a baby doesn't want to put weight on their leg. Or a toddler doesn't want to put weight on the leg, that's actually the symptom of a broken bone because their instincts are don't put weight on this leg. But that's sometimes the only way you can tell if a toddler has a broken bone because they don't, they don't have. Have an adult reaction to a break remote. There's no swelling because they're like baby bones. I guess they're that soft or something. And there would have been no indication that it was sort of like falling off the slide. Like they just get a boo-boo, you brush it off, and they react the same way they would with any other fall.

Lenny Murphy: Well, that's a good segue.

Karen Lynch: It's been so much fun.

Lenny Murphy: Tara's got a lot going on. I got stuff going on. We actually must end at 45 because I have to. Go to have a bunch of medical tests run.

Karen Lynch: Life, man. Life is life.

Lenny Murphy: Life, right? So, life.

Karen Lynch: Life is life. But we're going to quickly plug our things as we do. If there's new listeners tuning in, we've got two big events coming up. Our AI event, Karley, will throw that up first because that is first. Oh my gosh, it's coming up in just a couple of weeks now because this is our September event. We're really excited for it. I'm not going to expand upon the content as I do every other week, but come to this one. You know, we are just excited about it. We've got hundreds. We'll probably cross a thousand registrants by the time we get there. People are joining us from around the world, speakers joining us from around the world. It's going to be a fantastic event. Tune into that one. Thanks for putting that up, Karley. And, you know, super exciting. And then, you know, the following, later this fall, the following month in October, we've got IIEX West coming up, which is a really unique and interesting event with some fantastic speakers talking about really cool topics in a really great city full of innovation. Energy that comes in the Silicon Valley, you know, sponsored by Listen, which we'll be talking about a little bit today, not sponsored by, but our title sponsored, sponsored by a lot of sponsors, but our title sponsors, Listen, will be talking about how special this event is be with their title sponsorship. And, we'll have the Insights Innovation competition, which we've got a couple of people to talk about today. Startup Alley. It's just going to be a really great place if you're tapped into innovation. And certainly, what's to me, this event feels like the spirit of IIEX, like coming back to life in a new venue, but all of them like renewed energy. So I think that's why I'm so excited about it. Like, it's going to be like the epitome of everything that is IIEX. So I feel like it's a camp miss event.

Lenny Murphy: I'm really psyched for it. Yeah. Very cool. Very cool. Well, you know what? Let's go and just listen.

Karen Lynch: That's yeah.

Lenny Murphy: Yeah, let's start there. Yeah.

Karen Lynch: Yeah.

Lenny Murphy: We don't normally do this. This is a rumor, but it is a rumor being news.

Karen Lynch: Yes, being reported in the trade press.

Lenny Murphy: So I suspect that it's, you know, was an authorized leak.

Karen Lynch: Anyway, point is. Anyway, Lisman was our 2024 Insights Innovation Competition winner at IIEX North America. Alfred was also, you know, a future list honoree. So he's been on our radar twofold, right, for two separate reasons. And you know, this is, they've received, I think they're up to, you know, 100 million in funding at this point.

Lenny Murphy: They raised 100 million last year and this leak is raising another 125 million. Yeah. Yeah. That 100 million, they put them at roughly a 500 million valuation. So this 125 will probably put them at a 1.5 billion valuation in two years. In two years.

Karen Lynch: Yeah. Yeah. So the bet here, the bet, is that the right word? I don't know if that's the right word. If this particular round goes through, you know, what's happening here is that investors are putting money on the fact that we can scale qualitative feedback. Right? Which is in a very reliable way. Listen has proven it with their platform. It's not that they're the only ones doing it. It's just that what they have is that these AI-led interviews are something that anybody can tap into with confidence. They've done a great job showing this technology to the right people. And it's showing that feedback, that this type of feedback, which is the breakthrough of AI, is different from the Qualtrics type of tools, for that kind of feedback. They're buying, these investors are buying into getting the voice of the customer. To be able to query it at any time and get and get that kind of customer feedback. And it's working, it's selling.

Lenny Murphy: It is. Well, I think there's a broader proof point.

Karen Lynch: I'm sorry. I mean, no, no, no. I just think it's fascinating and I think it's important. And it's a beacon for the entire industry, actually. They may be getting the big bucks because they've done it, but they are leading the way towards credibility for a lot of platforms. Like, you know, it's credibility for AI-powered Gual, in my opinion.

Lenny Murphy: Its credibility for human data to power systems.

Karen Lynch: All right. So too, if we take a broader level, combine that last week with Simile and their big range, et cetera, et cetera.

Lenny Murphy: So, but it is to you it is a different spin. They are not selling themselves and never have a research solution per se. They have positioned themselves as a solution to. Engage and extract human data and feed into systems and all the stuff that they've been doing. So, very instructive. Let's see what happens. Again, it is not, there's not, this is not a formal announcement. It is a rumor being reported in the Trade Press. So, yeah, that was going to not be our Trade Press, but yeah, it came from, I think, TechCrunch originally. But yeah. So, we'll see. But, hats off to them. And again, as an insight innovation exchange winner, right? And we've known them since they were just a concept. Yeah.

Karen Lynch: Yeah. When they when he when Alfred dropped the, you know, the, you know, the survey, you know, the paper survey that was this long on stage with that dramatic effect and was like, here's, you don't have to do this and dropped it on the stage, wearing the lab, the lab coat. It was like, you don't have to do this. And, you know, here's it, here's a, here's a different way. And it was very, it was a dramatic effect and it was a very exciting kind of moment to see. And as soon as that happened, it was like, oh, this is going to be good. And you can feel it. You could feel it in that crowd. And, you know, there was sort of like this palpable moment where that's off. That's off. That's off. So.

Lenny Murphy: Yeah cool stuff gosh that competition is exciting okay all right medallia medallia speaking of feedback yeah right well let's follow up remember they they you know a couple months ago uh they was like yeah we're in trouble uh they've gone gone through that they reduced their debt got another 150 million we should know the companies do this um yeah uh and of course the new capital is to invest in yeah dun duna, the AI road transformation, right? So, um, the uh whole other piece of the conversation, right? I mean, I remember die first came along, innovative, yeah, blah, blah, became the big SaaS platform. Uh, but what? Private equity, that kind. You know, so there wasn't a lot of money to invest. Here came AI, it changed things, yada, yada, yada. Yeah, so they're coming through that retrench to be a healthier business now and see what happens.

Karen Lynch: So, yeah, yeah, so it makes sense. It's there, it's not the only um industry organization that has to reset around AI to stay relevant, it's just yes, that's what has to happen.

Lenny Murphy: So, um, yeah, yep, yep. Uh, so. 55 Blue, which was Canton Media, right?

Karen Lynch: Okay.

Lenny Murphy: Taking a minority stake in ISBA cross-media measure. So ISBA is a quasi-nonprofit, you know, media measurement reporting and standards organization. So this is interesting. There's another news we'll talk more about next week, but today, just this morning, Nielsen bought Double Verify. The point is, we'll talk more about that next week. And there's other stuff in here about media measurement, but we are seeing an interesting congruence now of platforms and providers engaging with the in a deeper way with the it's kind of like the fox watching the headhouse.

Karen Lynch: So it's interesting.

Lenny Murphy: They're engaged with these standards organizations in a different way. I don't know. There's enough happening to see that's a trend.

Karen Lynch: Yeah. Well, I think, and I feel like we talked about this. I wasn't here last week, right? Two weeks ago. I feel like we talked about this two weeks ago. There's so many different channels right now, and we have more to talk about even today, if we can get to it with media measurement in general. There has to be a way. It's so complicated right now to kind of track what's working where, right? It is a complicated playing field. And where my mind wandered to when I was looking at some of this and kind of connecting some dots is, I was just thinking, this is a rough time to be in that field, thinking of just, you know, how to pull all of those threads together and make sense of it. And, you know, again, like what's working where, and I don't know, it just feels like that's a challenging space to be in right now. So, I think all of the tools that are going to help with that, yeah, that's really important. Those are important tools to have in your toolbox to help those marketers make sense to answer those questions.

Lenny Murphy: What I'm saying, companies that have the capital are building the stack. Kublais is buying a live ramp, et cetera, et cetera. The Zeta of Palantir, you know, we see these companies that play on the activation, marketing, advertising, activation side of things building the connective tissue to really get to real attribution. And people could argue against whether that's good or bad. I don't know whether it is or is not. Having an independent third party to watch and observe and all that good stuff is a good thing, I guess. But the world's changing to your point. Yeah. Let's dive into these other things.

Karen Lynch: The new product. Yes. Well, speaking of the competition, right? So, yeah, Blue Pill, who was a finalist. A competition finalist this year in North America. So they did not walk away with a prize, but they were definitely a finalist. So we saw them online, you know, and in that synthetic respondent space. But this is talking about the marketplace model, right? So this is sort of merging the synthetic data in a marketplace model. And I'm like, all right, cool.

Lenny Murphy: Yeah, a thousand twins, yeah you know at ten bucks a twin, yeah I mean you know so they're going right for the economics, they're yeah that's that's interesting of you know they're embracing the CPI economic basis of the industry, and so rather than fighting it they're saying yeah all right like when Google Surveys first came out and it was you know 10 cents a question, uh period, yeah.

Karen Lynch: That was it. Yeah. Yeah. It's kind of the same idea. So yeah. Yeah. So you can buy them and test them and not just think, think about it, right? You're like, go ahead, go ahead, give it a go. Yeah, pretty cool, pretty cool, pretty cool thing to launch, in my opinion. Like, let's get on in there and give it a go.

Lenny Murphy: Yeah. Yeah. I mean, that could become, you know, the survey monkey of

Karen Lynch: Digital trends, for instance, right?

Lenny Murphy: Low cost, low barrier to entry, you know, not a hell of a lot of risk. Yeah. So people keep innovating in that category. So, yeah, interesting stuff.

Karen Lynch: Yeah.

Lenny Murphy: Do you?

Karen Lynch: Yeah, the opposite, the opposite of low risk. This is a category where it's high risk. Every time you see healthcare, every time you see healthcare, you're like, oh gosh, we're talking about AI and healthcare. So, PulsePoint launched something called Hatch, a Genetic AI platform for healthcare marketing. You know, it's an AI category where you just can't really, I don't know, like this, this. Every time I think about this, I start to get just a little bit more unsettled because you cannot, you can't afford risk in when you're talking about healthcare. It just gets a little more, I don't know, you know, it's got to be supported. You just can't take chances. I don't know. You know, anyway, I don't know if more about it. If you dug in a little bit deeper, I did not. But you're, you know, healthcare data is a whole different ballgame here.

Lenny Murphy: Other than that, I didn't dig far deep, the healthcare, but its provenance. And this week, the EU regulations went into effect, EU AI, which was all about proving data provenance in AI systems, which means basically everything any company does. So that, yeah, you get it right for something like in highly regulated, high-risk issues like healthcare. Yeah. That's something that applies everywhere. So I think that we're going to see more of that emergence of the focus on provenance, which affects quality, you know, the whole shebang. Yeah.

Karen Lynch: So, yeah, interesting that we saw that it's so funny. Every time I log into ChatGPT for use and it's like, you know, ChatGPT health. And I'm like, yeah, no. Like, I just kind of have a, I have an own, my own mental block around it because I'm just like, just don't want to trust health, health, you know, and I, and I have an aura ring for heaven's sakes. Like, I have, I, I use Apple Health. Like I, I'm pretty tapped into it on some level, but then I also do have a barrier. Um. And you know, I know it's happening out there, but there is something, it's just the risks, the stakes get a little bit higher when you're talking about health data, you know.

Lenny Murphy: So, um, yep, yep, I get it.

Karen Lynch: Good luck with Hatch.

Lenny Murphy: Good luck, yep. Um, Kaplana, uh, MCP, another MCP, which is what, like the 20th, yeah, yeah, exactly, exactly. It's not a it, it's a trend, guys. No, it's not a trend, it's a defining trend, I would say. So some hats off to them. Embedded in the workflows, which to go back to Listen Labs, that's what they did early on, right? They embedded there in Notion and Slack and et cetera, et cetera. That's what this means to MCP. It's making the tool accessible where somebody else or the user wants to access it.

Karen Lynch: Right. So if you're an insights provide, if you're a supplier out there and you're, you're not thinking about how do you get your, um, your, your insights, your answers, your findings to show up where your customers are actually working and making decisions and, you know, kind of following through on the next step, you know, you're missing that opportunity. You have to, you have to be thinking through that.

Lenny Murphy: Yep. Yep. Um. Same very short theme, this NTT data AI agent service for early stage product planning.

Karen Lynch: So that's Agentic first.

Lenny Murphy: So, and an outside entrant.

Karen Lynch: I never heard of these guys before. Well, here's what's interesting. Their clients are very high. They're Microsoft, SAP, Salesforce, AWS, Cisco. If you click, if you like to read more, like when you go to those are just the ones that like they're at the top of their list. Then, when you like to read more, it's these, it's like these heavy, heavy hitters. They are consulting big technology firms. Um, and I started thinking about that. I'm like, that's very interesting because if those big technology firms are kind of buying insights at that very high level, um, think about, think, just think about that. What is what? That's an interesting opportunity for who's buying insights work and who's, I don't know, how they're tapping into AI for insights at that very high level. I don't know. I just thought, I'm like, it's just more about these large consultancies. I don't know. It's just, you know. I don't know. I just think it's really interesting. So, granted, they're using AI and they're using agentic AI at this early stage, but these very high-level tech firms, I thought, were fascinating.

Lenny Murphy: I agree. The, and that was, the, it goes back to kind of the MCP, you know, this idea of, you know, as AI becomes the operating system, yeah, integrated into them. And, but the, the, the the sas platform isn't the most right the capability can be duplicated by smart people who understand so it is defining what is your moat yeah um uh but it doesn't mean that category expertise or that's not necessarily the most um and there's an example of that yeah so yeah yeah cool stuff you want to run through uh the stuff real quick.

Karen Lynch: Yeah. So, two quick hits. These are like commerce related. So, the e-commerce story, I think, is really interesting because we've talked a bit about how AI is affecting e-commerce, right? So, this, I don't know if it's pronounced rocket, rocked, R-O-K-T, rocket, rocket. They have this AI engine, an AI engine for e-commerce that's affecting. Transactions. So, you know, without really knowing too much about how it works, it's an AI influencing point of purchase decision making in e-commerce. But their clients, again, I keep looking at who's using this technology now. And it's like, all right, PayPal, Fanatics, Ulta Beauty, Cineplex, Albertsons, Macy's. So, okay, we're talking about major brands who are buying into AI engines affecting point of purchase. Decision making. They are disrupting, like they are, they are, they have been disrupted that they're like accepting of it. So, okay. So this is, it's just, it's just happening. All of the things that we've been talking about are happening, happening. Like, like, like there is, there's the AI, AI disruption to point of purchase decision making happening already. It's there. And, um, are they helping the customer? They're definitely affecting it. You know, customers are not making decisions the same way anymore. And to me, that's where the research has to be happening. Like, you know, get in there and find out how your customers are making decisions. Like if you, I don't care if Albert, if you're not Albertsons, if you're, if you're somebody else, you know, for heaven's sakes you better be talking to customers who might be Albertson's customers and find out how they're being influenced, because you need to understand that if you're not using this technology, because you may have to be that may be coming soon. How are customers, how is the decision making being influenced? All of it.

Lenny Murphy: Yeah. It's the same thing, all the end cap, the checkout stand, right? I mean, there is a whole science you know of like, how do you position at the checkout to find your kids go through? That's why the candy's right there, right? That kid level view.

Karen Lynch: Yeah, yeah, it's like I just bought something online, you to a beauty product, speaking of beauty products. I just bought something online and they asked me if I wanted samples, so I was like, sure. Like I was confused at the, during the checkup, I was confused because they were free samples. And I was like, sure, I'll, sure, I'll take the free samples, but I was confused by the offering of the free samples because I wasn't used to being offered free samples in an e-commerce way. And there was more happening around me. Like there were impulse buys happening online in this particular on this particular beauty site brand. And I didn't have that kind of time. I just wanted to go in and buy my blush and move on. Anyway, the point is there was a whole new world happening for me buying online. I just didn't have time to get out there to the store. Anyway, it's just a new world. And I feel like all of the decisions that we are making are changing because of AI. And we are, our brains haven't figured it out yet. Anyway, our brains haven't figured it out yet. And just when you think, I'll move us on quickly to the next one, which I had read in the New York Times, and I don't want to talk too much about it, but I do want to point out that it's out there because it's another experiment that's happening that I think people should know about because it might. I'm not saying it's going to happen, but they're experimenting and running research on a different model, which is a San Francisco store that is being run by an AI boss. It's an autonomous manager that is running the operations at a store. There are human employees, but the AI is the boss. It's not going very well. The boss is really nice. So, the people are late, and the boss is saying, That's fine, or they're asking for lots of time off, and the boss is giving them. So it's not really efficient. He is a very kind manager. You know how, like, your own personal AI is super nice and forgiving and gracious with you. That this AI manager is very gracious.

Lenny Murphy: Um, and it's actually written as a skill for me to be an asshole.

Karen Lynch: It's not true, it holds me accountable. It's not nice. Well, in some, in some ways, mine, mine, anyway, but in general, that is what is happening to most people, unless it's trained a certain way. But this particular manager, they're doing research on it. So they're not training for it, they're just doing research on it. So they're. They're showing, um, they're just kind of showing what it would be like, um, in an untrained way. And so it's a research experiment. They've bought into it. They're paying like $7,500 a month and they've committed to it for a few years for an AI manager. Anyway, I called it out and wanted to discuss it because this is a thought experiment and we have e-commerce. Commerce. We have e-commerce with AI agentic oversight. And now we've got an experiment with AI oversight in a non-e-commerce site, but a brick-and-mortar site. So there are people who are imagining the agentic forces at work in a brick and mortar way as well. And I just think it's worth saying. Think through all that and what that could mean for us because we've talked about robots, but this isn't really a robot. This is a managerial system in place. It'll be in a robot by like next year. It could be in a robot at some point, but this is still an agent, you know, that's a human typing and asking questions, it is handling the inventory, it is ordering products to stock on the shelves. The products are showing up, and the employees are unboxing and they're saying, Seriously, this is what we're stocking. Like, it's very eclectic and interesting. Um, and it's managing the supply chain, like it's doing all of the um it's managing the purchases and and um again that the supply chain and the inventory and stocking. And yet, there are humans that have to do that, um. Anyway, I just think it's, we are, we are in a, we are in an interesting time, friends. That is all.

Lenny Murphy: We are. We are. Let's circle back to the, we kind of hinted at it, the whole media measurement.

Karen Lynch: Media measurement. Let's talk about tech.

Lenny Murphy: I think there, well, there were three stories that mention of

Karen Lynch: Oh, yeah, yeah, yeah. Yeah. Talk about them quickly. We're okay.

Lenny Murphy: We're okay. Yeah. Live ramp, which bear in mind is about to be bought by Publisis, right? That's still out there. During cross-media intelligence within meta CTV programmatic, social and audio channels. So they're expanding their data to have a more omni-channel approach. So that's interesting. Because that's another point of the complications, fragmenting.

Karen Lynch: Yeah.

Lenny Murphy: Yeah did this campaign work you know yep uh increasingly I'm this interesting of app flyer measurement and chat gpt ads yeah directly inside its platform because that's a modern you know a modernization channel advertising platform now of uh the the ai so now we got to record it uh what's happening there not just that the complication of AI recommendation and AI disruption to buyer journey and all that, but actually, you know, when you're exposed to the ad within these systems.

Karen Lynch: Yeah.

Lenny Murphy: Yeah. And then the IAB, which is the oh, hell. I want to say interactive, interactive advertising bureau. Tech Lab released. Some new infrastructure and privacy diligence for the agenda were capitalized. So the same mentioned earlier about 55 Blue taking a stake in the kind of the equivalent of IEB and in the UK. This is what in the US, the IEB, releasing tech, right? I mean, really getting in there to help measure this. So it works both ways, right? The suppliers influencing the trade organizations or the trade organizations influencing the suppliers. So I thought that was interesting.

Karen Lynch: Yeah. Yeah. All right. Well, it's all interesting because it's all again, what's influencing the buying decision, you know, and then how do we track that influence because, you know, or the effectiveness of that influence. You know, it used to be fairly straightforward. Did this ad affect purchase or influence? Somebody's, you know, intention to buy or purchase intent. And now it's just a little bit blurrier. Right. It's a little more complicated.

Lenny Murphy: Speaking of purchase intent, it is interesting in the chat to have someone trying to pitch to us, utterly ineffective, dude. So utterly ineffective. So, friendly advice, go the hell away because it doesn't work. You need to learn how to do this a hell of a lot better than you are.

Karen Lynch: So, anyway, yeah, totally tuning it out. And probably, probably close to blocking. Anyway, yeah, let's get into some tech developments because we were watching the clock, but there are really two big stories here. OpenAI's next model, Astra. Interesting. So, Astra has claimed that they've broken through on 10 long-standing math and theoretical computer science problems, hinting at faster verified reasoning workflows. You know, without being a math geek myself. You know, looking into this, to me, it's not that interesting that they're better at math problems because, it's yes, sure, it's great for math geeks, but what that's interesting for to me, the interesting thing about it is what does all of this advanced, these advanced models mean for the analytics professionals in our industry? We're getting closer and closer to AI. Helping them think through their work even better, right? And helping them think through what's actually going on here, you know, helping them with the analysis, not just with data synthesis, but helping them think through, what am I seeing in the data? You know, what, you know, not just what are the outliers, but what are the anomalies? You know, how do I structure my analysis? Like, really, like the more they can look, the better it can get at. The math, the better it's going to be at looking at the data and the numbers and helping analysts do their job better. We talk so much about the synthesis of insights work. And, you know, I just think for data analysts and data scientists, this is a good, this is good news for them that the machines can help them better.

Lenny Murphy: They agree because traditionally AI sucked at math and getting consistent results. Has been a real problem. They're solving that, right? So, yes, that is the end point because of the resistance to this about replicability.

Karen Lynch: Yeah. Now, obviously, it's getting better.

Lenny Murphy: Yeah. Which I would say is true. I don't dive into the math stuff that often, but I, but I have lately, I've had to build some pretty complex spread workbooks and I definitely noticed that the math is more trustworthy. Yeah. So good news for those folks. Absolutely. And then now, speaking of getting better, so this was the Google four senior people at Google left to launch Discovery Loop. Now, they didn't really leave because Google's investing in them.

Karen Lynch: Did you read it? Did you read where it said Dean and Gimawat, who were among the company's first hires, is equivalent to Mick Jagger and Keith Richards ditching the Rolling Stones to start a new band?

Lenny Murphy: I didn't see that.

Karen Lynch: That's awesome. What a great analogy. I just thought that was a great analogy, so it's still like all right, sure, so Google's investing, but it's still a burn, right? It's still like, oh, sure, we'll listen to the music, but you're still, you know, it's still a bummer that you're leaving, you know.

Lenny Murphy: Um, well, they've been there forever. I mean, the one, uh, the one guy who left it 27 years ago, yeah, at Google. But the um, but what I thought was cool about this is that they want to apply the scientific method— my takeaway was to apply the scientific method for the next generation of AI development.

Karen Lynch: So test and learn, test and learn, test and learn. Yeah, yeah. Yeah, it's an innovation story. And I think that the takeaway for us and for our industry is don't think that, don't think that the breakthroughs have all happened. Like, what, like, they haven't, right? Like, what are we looking for? There's, there's, you know. There are other innovations that are yet to happen in our industry, right? But you know, like there's an urgency to just keep looking and keep thinking about what's possible. Like, sure, okay, AI has sped up our workflows, and sure, there's AI qual and sure, you know, listen-tapped into something great, but what are the other challenges we can overcome? What are the others, you know. What are the other possibilities for the work that we're doing? What else? Like, let's, let's not get out of discovery mode. Like, sure, synthetic twins are great, but that doesn't mean we have, we have, it doesn't mean we're tapped, you know, like, I, I don't want people we have figured it all out. Um, we're not, we're not done. Like, let's, let's, you know, let's come up with our own, you know, discovery loop, if you will.

Lenny Murphy: 100%. Test and learn, test and learn, test and learn.

Karen Lynch: And I'm sure somebody listening has that entrepreneurial spirit still and is like, all right, I got you. Let's go do it. So go do it, people.

Lenny Murphy: Go do it. Go do it.

Karen Lynch: Absolutely.

Lenny Murphy: All right. We got a couple reading lists and then we'll wrap up.

Karen Lynch: Yeah. Yeah. Well, I'd rather not, but I know. I know. Yeah, real, truly, truly read more. Insights has analyzed 50 synthetic data companies, speaking of synthetic data, 50 synthetic data companies and found stalled funding, but fresh demand. So I thought that was really interesting. You know, I think just from things that we've seen at events, we are past synthetic data being good or bad. We are at the when is synthetic data the right, when is the right to use synthetic data, what are the right use cases? But I, and I, and I think that, I think that there are very appropriate use cases. Obviously, there's companies, like Blue Pill, making it accessible. You know, so I think it's interesting. You know, I just checked it out. I just think it's worth looking at and starting your use cases. Agree.

Lenny Murphy: And point out this particular article is, there's lots of synthetic. This is like capital S synthetic. I mean, there's lots of other use cases that don't necessarily fit how we think about it. But the point is, it's creating data, replicating it and testing it for all types of stuff. So but same.

Karen Lynch: Principle. Yeah. 

Lenny Murphy: Insights does such great stuff. If you don't subscribe to the newsletter, you subscribe. Yeah, yeah, yeah. Yeah. Oh, I mean, the daily, especially when the founder was doing it, I always signed off with I love you.

Karen Lynch: Yeah. Good stuff. Good stuff.

Lenny Murphy: The ARF, interesting research released what consumers really think about AI. And we can. There is still a chasm between consumers and business um because my take on that was consumers were like yeah I'm still pretty sketched out by all this uh yeah yeah uh yeah not like we're talking about the wearables like not according to the this these data the consumers are not on board with wearables and augmented reality and all of those things all the stuff that we talk about on the front end Yeah, there's still a big old divide. What did you take anything else out of that?

Karen Lynch: Yeah, no, just you know, that the B2B world is very different. And I'm, I mean, I think that we just have to keep in mind that we our audience is a B2B, if we are B2B, kind of we are talking to businesses, but businesses that are talking to consumers, tread lightly. The suppliers in our field are largely B2B companies. So they have a different POV. But yes, brands that are out there that market to consumers tread lightly. I think that's true. That's really the key. They may be afraid. They may be a little more afraid of AI, so be careful with your, with how vocal you are about it. And just because we think it's cool, they may not want to see your AI creations. It's a little scary for people because they still think it's like, doo-doo-doo-doo. You know, it's not as embraced.

Lenny Murphy: So absolutely. And professionals have a different relationship with it. Right. We're about, we see the efficiency. Right. I mean, we're thinking of the gains. Consumers are, yeah, even put on my own, it's consumer. I am more focused on the experience than anything else. So, yeah, interesting. And then, ongoing, the IAB again released measuring visibility in the AI era continues to be an issue we talked about week after week. Yep. And today as well, right? This whole disruptive system. So, yeah, good stuff. That's it for this week. Next week, yep, we did. So, next week, you're going to have to record early, right?

Karen Lynch: Because we're pre-order on Thursday night, friends. We'll still be, we'll still have a show, but we're, we'll, we're full disclosure, we're going to pre-record on Thursday. We will still air it on Friday, but I will be heading to the shore. So, and if you're from the area, if I say, down the shore, you might know what I mean.

Lenny Murphy: And then the following week, we'll have a guest host.

Karen Lynch: Yeah, so there's a guest host. Yeah. So, we'll see you next Friday. And yeah, I need a vacation super bad.

Lenny Murphy: So, um, you know, yeah, you've had a hell of a hell of a run recently. Yes, you do.

Karen Lynch: So, so, um, so, yeah, but we'll see you next week.

Lenny Murphy: Have a great weekend, everybody. Bye, everybody. Take care.

Links from the episode:

Listen Labs is in Talks For $125 Million Financing Led By Anthropic Investor 

Medallia completed its recapitalization 

Fifty5Blue to Take Minority Stake in ISBA's Origin 

BluePill Launches World's First Marketplace to Recruit Synthetic Respondents 

PulsePoint launched Hatch 

Introducing the Caplena MCP 

NTT DATA launched an AI-agent service to accelerate early-stage product planning for CPG companies 

Rokt introduced Brain V4 

These Employees Like Their A.I. Boss. Its Shop Is Kind of a Disaster. 

LiveRamp Adds Meta, Other Data to Cross-Media Intell 

AppsFlyer Brings Independent Measurement to ChatGPT Ads 

IAB Tech Lab Releases AAMP 2.3 

OpenAI's next major model Astra claims breakthroughs on 10 long-standing math problems 

4 of Google’s Top AI Brains Are Leaving—and Launching Their Own AI Startup 

CB Insights analyzed 50 synthetic data companies and found stalled funding but fresh demand signals as big tech moves in 

AI in Advertising: How Marketers Are Adopting It—And What Consumers Really Think 

IAB Releases "Measuring Visibility in the AI Era"