This week on The Marketing AI Show, the guys discuss responsible AI, do a deeper dive into Meta’s CICERO (after a short discussion in Ep. 25 of the podcast), and the job posting Mike came across for an AI Marketing Specialist.
A manifesto for responsible AI—for companies to use for themselves
Last week on the Marketing AI Institute blog, you may have seen our Responsible AI Manifesto for Marketing and Business. In it, Paul lays out the 12 principles that we’re using to guide us in the responsible use of AI within our organization. From this blog post and Paul’s subsequent LinkedIn post, we received feedback, comments, and some praise on taking this step. Much of the feedback asked if we had considered a certain principle, or questioned one of the bullet points in the article. On the podcast, Paul and Mike walk through each principle and break down their thoughts and how businesses and marketing leaders can use this document to create a manifesto of their own.
What is CICERO…and what are the implications?
In November 2022, Meta AI introduced CICERO, the first AI to play at a human level in Diplomacy, a strategy game that requires building trust, negotiating, and cooperating with multiple players…essentially trying to make it fundamentally honest and collaborative. Is there a place for CICERO in business and life? Will AI assistants be able to help us negotiate and navigate through life? Many of these questions touch on conversations Paul has had, and posts he’s shared: there’s a much bigger story to these AI developments, and the implications for business and society are huge.
The first (that we’ve seen) AI marketing job listing
Tomorrow.io’s CMO Dan Slagen shared his company’s most recent job posting for an AI Marketing Specialist. The good news is that this is a junior role, and years of experience aren’t needed. It’s interesting and exciting that one function of this role will be to stay up to date on the latest AI developments and learn to pilot and scale AI programs as they learn. What a great way for businesses to stay ahead of the AI curve and bring on interested, enthusiastic talent.
This podcast episode ends with rapid-fire questions talking about Big Tech’s Q1 earnings calls, updates on Microsoft and Bing, ChatGPT breaking records, and Runway Gen-1’s big announcement.
Listen to this week’s episode on your favorite podcast player and be sure to explore the links below for more thoughts and perspective on these important topics.
00:02:57 — The Responsible AI Manifesto
00:20:43 — Meta’s CICERO and its implications
00:31:22 — The first marketing AI job posting
Links referenced in the show
Watch the Video
Read the Interview Transcription
Disclaimer: This transcription was written by AI, thanks to Descript, and has not been edited for content.
[00:00:00] Paul Roetzer: It is much safer at the moment to assume in legal situations and in ethical situations, the human is going to be held responsible for whatever the output is.
[00:00:09] Paul Roetzer: Thus the point, like you can’t let them run autonomously. Because you are going to be held legally liable for whatever they do.
[00:00:15] Paul Roetzer: Welcome to the Marketing AI Show, the podcast that helps your business grow smarter by making artificial intelligence approachable and actionable. You’ll hear from top authors, entrepreneurs, researchers, and executives as they share case studies, strategies, and technologies that have the power to transform your business and your career.
[00:00:36] Paul Roetzer: My name is Paul Roetzer. I’m the founder of Marketing AI Institute, and I’m your host.
[00:00:45] Paul Roetzer: welcome to episode 33 of the Marketing AI Show. I’m your host, Paul Roetzer, along with my co-host Mike Kaput, Chief Content Officer at Marketing AI Institute and co-author of our book, marketing Artificial Intelligence, AI Marketing in the Future of Business. Today’s episode is brought to you by the Piloting AI for Marketers Online Course series.
[00:01:04] Paul Roetzer: This is a series that we launched in December of 2022. It’s a step-by-step learning journey for marketers and business leaders. We’ve had actually a lot of non marketers taking the course saying it’s super valuable. So I guess marketers and others to guide them through adopting AI to advance their companies and careers.
[00:01:22] Paul Roetzer: There are 17 on-demand courses that, again, we recorded in mid-December. So this is post ChatGPT. We actually created all this. There’s dozens of AI use case and technologies, collection of templates, frameworks to help marketers understand and apply ai. Basically put more than a decade of our lives, our research into hundreds of hours of planning and production for this series.
[00:01:43] Paul Roetzer: You can check it firstname.lastname@example.org and use AI pod 50 promo code for $50. Registration. So again, that is piloting ai.com, AI pod 50. It’s not case sensitive, I don’t think. I think you can use it all caps, non caps, whatever. $50 off registration if you’re new to the show. This is our weekly format where Mike and I pick three hot topics in AI and we talk about ’em.
[00:02:11] Paul Roetzer: We usually spend about 40, 45 minutes on the topics. Mike walks us through each topic. I add a little narrative. We were locked in on our three topics, and then we added like four rapid fire ones this morning. , there has been a lot happening since last Wednesday. So we’re going to do our three, and then we’re going to hit on, four quick rapid fire items at the end just to keep you in the loop of the latest stuff happening in artificial intelligence.
[00:02:37] Paul Roetzer: It is wild as always. All right, Mike, it’s all you. Thanks
[00:02:41] Mike Kaput: Paul. I’m glad to be back this week. Like you said, a ton is going on, so we have a lot to cover. So I will try to move us through these topics because I think even, you know, in the rapid fire, rapid paste world of ai, the past week or so, we’ve done a lot.
[00:02:57] Mike Kaput: So first up, at the institute we. Have this belief, a deeply held belief that AI is going to have a disproportionate net positive impact on business and society, but we also foresee it altering career paths, displacing jobs, and chipping away at privacy. That we as consumers have if we let it. And we’ve always talked about the need to have hard conversations as an industry and as a business and as professionals now so that we don’t ruin what can be and is shaping up to be one of the most transformative technological shifts in human history.
[00:03:39] Mike Kaput: So as AI capabilities and news races forward, We really feel that leaders must clearly define their principles, their policies, and their procedures around artificial intelligence. So in the past week, we made some pretty serious strides towards. Looking at what those principles, policies and procedures might be.
[00:04:00] Mike Kaput: And the first form of this is we created a manifesto that we’re calling the Responsible AI Manifesto for marketing and Business. Now, we published this on our website as a blog post, and it’s a document that outlines and codies our responsible AI principles here at Marketing AI Institute. And in the process, it’s actually a really good template, an open template for.
[00:04:26] Mike Kaput: Businesses and leaders who want to pilot and scale AI in an ethical way. So we’ll link to that manifesto in the show notes so you can read through all the principles we came up with, and you can actually use it yourself under a Creative Commons license as a starting point for your own responsible AI policies and practices.
[00:04:44] Mike Kaput: So as people listen along and read along in that manifesto. I wanted to ask you right outta the gate, Paul, why a manifesto? Why this manifesto? Why now?
[00:04:58] Paul Roetzer: This is something that, as you were saying, we’ve thought about a lot through the years. I mean, even back to 2016 when we started Marketing Eye Institute, I, I felt like we needed something like this.
[00:05:09] Paul Roetzer: 2019, the first marketing AI conference, Macon 2019. We had an AI for ethics panel that was actually led by Karen Howell at the time was an m i t Tech review, is now, AI writer covering China for the Wall Street Journal. And my thinking was AI was, Early. I mean, I guess you could say we’re still very early in AI understanding and adoption, but in 2019 when we launched our AI conference, it was very early in retrospect, and I thought that it was critical that while we were teaching people the fundamentals of AI and showing them how to infuse it into their marketing and business, we were forcing them to, take head on the challenges of doing it ethically and responsibly.
[00:05:57] Paul Roetzer: So anytime we’ve done conferences, we’ve made sure that responsible AI and ethics was a theme that was infused into what we were doing. That’s, that’s where the tagline, more intelligent, more human came from for the conference. So, We made an attempt, I would say, when we were writing our book. It was very much in our minds to try and create something like this, some sort of industry standard that people could build off of, and we just didn’t get there.
[00:06:24] Paul Roetzer: I, I mentally don’t think I was. At a place yet to get there. I don’t think I had formed enough points of view on the different critical aspects to, to get there. So instead of publishing in the book, you know, here’s our 12 principles, we cited Adobe and Google. You know, we basically said, here’s what they look like.
[00:06:43] Paul Roetzer: If you’re going to build a policy in your organization, I think it’s chapter. What Mike 16 maybe was like the more human chapter, the responsibility I chapter. So we addressed the need to do this within an organization, but we didn’t have our own policies to share at the time. So fast forward to, you know, two weeks ago, January 27th, I don’t remember what triggered it.
[00:07:08] Paul Roetzer: I think I was at the gym that morning. It was a Friday. And I just got the inspiration to do this, and I had a bunch of stuff I was supposed to be doing that day and I just cleared my schedule that morning and I just wrote it and so it, it was basically 11 years of thinking and researching and writing and speaking and all these things that basically boiled down into about 60 minutes of writing 12.
[00:07:32] Paul Roetzer: Principles in essence. And then the way it transpired, as you’re fully aware, is I sent it to you and was like, dude, I want to, I want to like get this out now. What do you think? And I shared it with some other members of our team and basically just said, if you, if you all have time to review this, do it.
[00:07:48] Paul Roetzer: If not, we’re going live with it tomorrow. Like, I, we just need to get this out. And so I think it was a lot of thinking, a lot of spending a decade or more worrying about this, pondering how it would be done responsibly, not knowing for sure how it would, and I think the rate of acceleration right now just created the need to put something out that we know is imperfect, but would at least force the conversation and debate and hopefully give people something to start with so we don’t have a bunch.
[00:08:19] Paul Roetzer: Marketers who are now diving into AI with no guidelines whatsoever. So
[00:08:25] Mike Kaput: if I’m a business or a marketer reading through these principles, these all sound really great. But why do we need to act on this as businesses now? Why do we need responsible AI principles, especially for people who are just getting started with the technology?
[00:08:42] Mike Kaput: Yeah.
[00:08:42] Paul Roetzer: What we know. Government is going to lag behind. Regulations and laws are going to lag behind AI more than they traditionally do. I mean, government’s always behind in technology adoption and understanding, but I think in the case of ai, it’s going to be. Unlike anything we’ve experienced before, it’s going to be very, very complicated for government to step in and do anything here in the foreseeable future.
[00:09:07] Paul Roetzer: And we see that right now with the AI Act in, in the European Union. You know, they moved earlier than the US obviously, and other governments to try and enact something. And they’re running into obstacles, potentially insurmountable obstacles on the technical aspects of, it’s great to have the policies, but how do you enforce them?
[00:09:25] Paul Roetzer: And that’s where they’re running into major issues in the eu. is like, is the AI act even feasible? And if that can’t succeed, then how are we going to do it in the US or other countries? Hmm. I think that it’s just essential that we accept there’s going to need to be self-governance at the company level, at the individual level, you know, first at the individual level.
[00:09:49] Paul Roetzer: I think there’s going to, there’s going to be a lot of cases where people are going to be asked at their place of employment to do something with AI that they’re not going to agree with. Mm-hmm. , but there’s going to be no policies to tell them that there’s going to be no laws to prevent them from doing it. I saw so.
[00:10:07] Paul Roetzer: Oh, as a guy I follow on Twitter last night that at Buzz, Buzzfeed, a data scientist that Buzzfeed mm-hmm. , and he basically said like, if I didn’t have to follow ethical guidelines for ai, I could do things right now that would like blow people’s minds. Hmm. But he’s limiting himself within his own ethical guidelines as well as probably those of, of, Buzzfeed and potentially some legal
[00:10:32] Paul Roetzer: It’s the Wild West right now, and it is coming down to a lot of individuals and individual organizations to sort of self-govern in this. And I, I don’t see that changing in the near future at all. I think there’s going to be a lot more pressure to break those ethical guidelines mm-hmm. Because you’re going to see other people doing it.
[00:10:50] Paul Roetzer: And I’m not saying like what OpenAI is doing is unethical per se. I’m not taking like a, a point of view one way or the other on what they’re doing with ChatGPT and, and releasing. Things before other organizations are willing to, but you’re going to see competitive pressure where OpenAI is maybe in the eyes of Google doing something unethical that they maybe shouldn’t have put those models into the world.
[00:11:12] Paul Roetzer: So you have already these like ethical lines being drawn where Meta and Google are, which you may or may not think they’re ethical companies to start with. Maybe, maybe your view is they’re unethical organizations, but whatever your view. Right now, at least OpenAI is releasing things that other organizations have deemed unsafe.
[00:11:34] Paul Roetzer: And so the ethic, the ethical choice moves like it’s a gray area as to what do you exactly consider ethical. And so as other organizations push forward and are willing to use AI in ways that maybe you or your organization haven’t been, there’s going to be constant pressure to maybe reconsider where the ethical lines get drawn.
[00:11:53] Paul Roetzer: And that’s why I think it’s essential. That organizations have very clear policies for their employees. Otherwise, we’re going to be, putting people in very difficult positions to have to make decisions without guardrails.
[00:12:05] Mike Kaput: Hmm. So I think our manifesto provides a really solid start for most organizations that are trying to figure this out.
[00:12:15] Mike Kaput: But obviously every company, every organization has its own unique needs. What types of questions should I be asking at my company? The use of AI or the potential use of AI to build on top of these principles that we’ve published.
[00:12:31] Paul Roetzer: So the first thing I think you have to do is are you building or are you buying it?
[00:12:36] Paul Roetzer: You know, if you’re an organization that’s actually building AI tech and leveraging APIs from these like language model companies or image gen companies, or video generation or audio generation, , you know, if you’re building the tech, it’s one thing. If you’re buying it, it, it’s another, and the policies and principles are probably going to be similar.
[00:12:57] Paul Roetzer: But you have to make these choices around am I going to build this tool that enables this thing or not? And I think part of that comes into play around data and, you know, what data did they use to build it? If you’re buying it, or what data are you buying to enrich? You know, the solutions. So I think that those are key and it, it, it might be helpful, I’ll just run through the 12 principles we have real quick.
[00:13:21] Paul Roetzer: Yep. And, and provide real quick context if, if the, if it’s relevant. But I don’t want to spend too much time, cause again, people can go read these and download it themselves. But I’ll kind of give a little color as to why I picked the 12 I picked. So our first one is we believe in the responsible design, development, deployment, and operation of AI technologies.
[00:13:38] Paul Roetzer: So that was meant to be all encompassing, whether you’re building it or buying it. That overall, we’re, we’re taking a responsible approach to this. The second is we believe in a human-centered approach to AI that empowers and augments professionals, AI technologies should be assistive, not autonomous.
[00:13:53] Paul Roetzer: Now, I’ve gotten pushback on this one more than any of the other 11. And the people who have pushed back are the people building the technology. So, My basic premise here is I don’t think we should be trying to remove the human from the loop. I don’t think full autonomy with zero human inputs or oversight should be the goal.
[00:14:12] Paul Roetzer: Now, I’m, I could probably be, Moved on this in the months and years ahead when we see safe applications of a full autonomy. But I have yet to personally see anything close to full autonomy in marketing or in society. Like it doesn’t exist on autonomous cars, is the main thing we look at. And there aren’t cars without steering wheels that can drive in all conditions with no human involvement.
[00:14:37] Paul Roetzer: That’s full autonomy in the rain, in the sleet, in the snow, in untrained, you know, off-road on. That’s full autonomy. I don’t see that in business and marketing software today. Again, I I, I’m happy to be proven wrong on this one, but as of today, I don’t think that should it exists, nor should it be the goal at the moment.
[00:14:55] Paul Roetzer: The third is we believe that humans remain accountable for all decisions and actions, even when assisted by ai, the human must remain in the loop at all applications, sort of building on number two, I, I believe that very strongly at the moment that, I, again, the AI. If you, even if you play this out from a legal, legal perspective, if the AI does something that causes harm in any way, you know, and, and you’re the person that bought the software, let the software run on its own.
[00:15:23] Paul Roetzer: You’re going to be held responsible. Like there’s no legal precedent to charge the machine with something. And so you’re going to get into these situations. Well, is it the company that built the software? Is it us that allowed the software to run autonomously? Is it So I think. It is much safer at the moment to assume in legal situations and in ethical situations, the human is going to be held responsible for whatever the output is.
[00:15:46] Paul Roetzer: Thus the point, like you can’t let them run autonomously. Because you are going to be held legally liable for whatever they do. Hmm. So I just, and, and not even, not even legal, like from a brand perception, think back about, what was that chatbot, Microsoft Release years ago? Tey or, yeah, something like that that just went haywire, and like the first 24 hours.
[00:16:05] Paul Roetzer: Yeah. What damaged Microsoft’s brand? Was it unethical? Was it illegal? Probably not. Like, I mean, they’re not going to get sued over it necessarily. , but it was a very questionable decision for the health of the brand if you knew what could go wrong. Mm-hmm. . So there’s just lots of reasons why I think that’s important.
[00:16:20] Paul Roetzer: Four, we believe in the critical role of human knowledge, experience, emotion, and imagination and creativity. And we seek to explore and promote emerging career paths and opportunities for creative professionals. That one sort of stands on its own. We’re not trying to get humans out of the equation here.
[00:16:34] Paul Roetzer: We’re trying to enhance what they’re capable of. Number five. We believe in the power of language, images and videos to educate, influence and affect change. We commit to never knowingly use generative AI technology. I’m going to repeat that part. Never knowingly use generative AI technology to deceive, to produce content for the sole benefit of financial gain or to spread falsehoods, misinformation, disinformation, or propaganda.
[00:16:58] Paul Roetzer: Hmm. This one has also gotten a little push. Because you get the obvious in the state of society today, well, what’s your misinformation? Is our regular information or facts or whatever. Mm-hmm. . The point is whatever you consider misinformation or disinformation to be, if you will willfully do it, if you use AI to spread what you know to be incorrect information, that would be knowingly doing it, in my opinion.
[00:17:24] Paul Roetzer: It’s not a political statement. I don’t care what side of the aisle you’re on, like this is a, if you are knowingly deceiving people, we do not believe in that. All right, I’ll just, I feel like we might have to spend an entire episode in the future just on number five, but I’ll leave it at that for right now.
[00:17:40] Paul Roetzer: number six. We believe in understanding the limitations and dangers of AI and considering those factors in all of our decisions and. This is one where I think we are failing as a society at the moment. I don’t think most leaders, most government leaders, most business leaders understand the limits and dangers of ai.
[00:17:55] Paul Roetzer: I think this is a very critical, point. So again, re think about that one. Seven. We believe that transparency and data collection and AI use usage is essential in order to maintain the trust of our audiences and stakeholders. Let that one stand on its own. Eight. We believe in personalization without invasion of privacy, including strict adherence to data, privacy laws, mitigation of privacy risks for consumers, and following our moral compass when legal precedent lags behind AI innovation.
[00:18:22] Paul Roetzer: I know you, that one jumped out to you when you edited it. Yep, and I think based on what we were already talking about upfront with the challenges of keeping up with laws here, the moral compass is going to be critical. Now, this is obviously a very subjective. One, but I think if you’re a brand, if you’re a market or business leader, your organization either has a stated moral compass, it’s in the culture code.
[00:18:45] Paul Roetzer: it’s, it’s embedded somewhere within that organization, and people need to understand that and believe in that. Whatever you define your moral compass to be. . Number nine, we believe in intelligent automation without dehumanization and the potential of AI to have profound benefits for humanity in society.
[00:19:03] Paul Roetzer: 10. We believe in an open approach to sharing our AI research, knowledge, ideas, experiences, and processes in order to advance the industry and society. Putting this out there as an open source document is part of that process. We try and we default to being open about the things we’re learning and thinking to try and advance people even if it doesn’t, if it may harm us from a financial perspective, down the road.
[00:19:27] Paul Roetzer: You know, it, it’s just overall guides. 11. We believe in the importance of upskilling and re-skilling professionals and using AI to build more fulfilling careers and lives. That is essential. You cannot go find a bunch of AI savvy marketers in business professionals out of school right now, or being trained in mass anywhere.
[00:19:45] Paul Roetzer: You have to commit to upskilling them yourselves. And then the final is we believe in partnering with organizations and people who share our principles. So again, go check out the link in the show notes. You can read the whole thing as well as how we’re using AI today, sort of our. Being transparent about our use of AI in the organization, and then if you have ideas and ways to improve it, you know, we’re, we’d love to hear it.
[00:20:07] Paul Roetzer: That’s, that’s part of the reason we put it out there.
[00:20:10] Mike Kaput: Yeah, absolutely. I think we fully intend to start and have a conversation, not, you know, just drop these principles down from on high
[00:20:18] Paul Roetzer: on people. So, yeah, it’s not a holier than thou thing. This is a, we’re seeing a lot talking to a lot of people. These are things we think are critical for every organization to address.
[00:20:26] Paul Roetzer: They may expand, they may contract, they may evolve, but we’ll share whatever direction we go with.
[00:20:33] Mike Kaput: Excellent. And again, you can check that out on the website and we will have it in the show notes for you to read fully and also use for your own organization. Next up Paul is something really interesting that I think you might have been probably the first, if not the only person to really hit on in a, in a big way.
[00:20:51] Mike Kaput: So, In November of 2022, meta ai. So you know, formerly Facebook introduced something called Cicero, the first AI to play at a human level in diplomacy, a strategy game that requires building trust, negotiating, and cooperating with multiple players. Now that news isn’t exactly new and it’s a pretty impressive achievement, but what you really pointed out, Some commentary on LinkedIn is that in essence, meta has built an AI agent with the goal of making it fundamentally honest and fundamentally collaborative.
[00:21:29] Mike Kaput: And you wrote that this has much, much bigger implications outside of mastering a strategy game. And you said quote. This sort of technology may find its way into your business and life, perhaps within the next several years. And quote, in the not so distant future, you will have AI assistance that help negotiate everything in real time based on your optimal desired outcome.
[00:21:55] Mike Kaput: Can you unpack a bit more for us, the wider implications of something like Cicero in real world business, applic.
[00:22:04] Paul Roetzer: This one came from just a lot of the conversations I’m having. So I, I’ve mentioned in past episodes, once Chat c p t came out, I just started getting the calls, text messages, LinkedIn messages, Twitter dms, like people at major software companies, venture capitalists, friends, people building AI software.
[00:22:26] Paul Roetzer: And so for the last couple months, I, I’ve just been. Not, overwhelmed isn’t the right word. There’s been a, a, a flood of, of in inquiries and conversations, and the thing I’m struck by is how many of them are solely focused on solving for ChatGPT and related generative AI tools. That ChatGPT as we’ve talked about before, was the inflection point where the mass audience of marketers and business leaders.
[00:22:59] Paul Roetzer: Took note of artificial intelligence and if they stop at ChatGPT, then their perception of what AI is and the roadmap they have to solve for is to figure out language technology or generative ai. You know, a wider scale view involve images and videos and audio and. What I kept guiding my friends, especially investors, and SaaS executives, is if, if you’re only solving for ChatGPT and AI writing tools, you are missing the much larger picture that, you know, as we said in the previous episode.
[00:23:32] Paul Roetzer: It’s just the tip of the iceberg, like it really is, and it’s great because it got people to pay attention, but I think the bigger opportunity is so much more massive than people understand as is the. And so in the case of Cicero, like I’ve shared this with, again, a few people privately and explained what I thought was the significance of this moment, and then I finally decided like, okay, I just have to, like, I have to play this out in my mind.
[00:23:57] Paul Roetzer: And I think I even reached out to you, I was like, did we already talk about this on the show? Like, I feel like this has been in my head for a while. And we were like, no, we didn’t really go in depth. I was like, all right, well, I guess we which time to go in depth. So the thing. That’s key is like I, I know that, for years in the major AI research labs, they’ve been working on the ability to give the AI deeper understanding of human language and the ability to reason, the ability to have like a chain of thought, chain of logic.
[00:24:26] Paul Roetzer: To like think through thoughts and outcomes and things like that. And so when I saw the Cicero moment and then I listened to the Lex Friedman podcast where the guy who kind of co-created Cicero was sharing the background story, it just started to connect some dots for me about the significance of what was about to happen.
[00:24:46] Paul Roetzer: And so I think like if I go into that, the original LinkedIn post, I made a note that in November 22, meta introduced Cicero first day outta play at the human level, as you mentioned. Then I used the quote from Jan Lacoon, who we’ve mentioned on the show many times, the VP and chief AI scientist at Meta, and he said on, on the Cicero announcement, this breakthrough rest in the achievement of combining two different areas of ai, strategic reasoning and natural language processing.
[00:25:13] Paul Roetzer: The integration of these techniques gives Cicero the ability to reason and strategize with regard to player’s motivat. Then use natural language to communicate, reach agreements, to achieve shared objectives, form alliances and coordinate plans. And I just like when I think about that and you realize how prevalent those things are in business and you know, in our lives and in business, and you start to think, wait a second, what if like in my mind, I immediately.
[00:25:44] Paul Roetzer: A salesperson either on a call or an email, let’s say it’s a call, and the AI is listening to the call, recommending to the salesperson what to say, because what happens in any negotiation, again, whether it’s buying software or merger and acquisition or the examples I gave, in business like sales merger and acquisition, fundraising, contract, negoti.
[00:26:06] Paul Roetzer: or in your life, which may be like home buying, legal disputes, contracts, compensation, when you’re negotiating your comp, fantasy sports trades, like it could be, get kind of crazy. You’re, you’re negotiating between two or more parties and there’s likely misaligned goals. So as the salesperson, I want you to buy my software for a thousand dollars a month.
[00:26:25] Paul Roetzer: You want to buy it, but you won’t, you don’t want to spend more than $800 a month. And so we’re going to go back and forth and we’re going to try and figure it out. So our goals are a little bit different, but we want a mutually beneficial outcome. . And so in sales, you’re going through these processes and usually you’re just reading off of a playbook.
[00:26:40] Paul Roetzer: Okay? If they, if they don’t agree to this, then I’ll, from that, if they, where the ai, what they’re proposing within Cicero is it’s going to, in real time, be able to analyze the intentions, the emotions, the behaviors, the signals of the other party, and recommend you the best way to achieve a mutually beneficial outcome with that individual.
[00:27:00] Paul Roetzer: And so I just started thinking about this, and so what I wrote. That these agents may be present through a chatbot email, client browser extension, AirPods AR glasses, or other app that’s listening quotes in the background and making recommendations of what to do and say, and to me, When we think about this, it seems like this very human process.
[00:27:21] Paul Roetzer: Like I could totally understand people being like, yeah, I don’t buy into this one. Like I get AI writing stuff, but this humans can’t, you know, they can’t do what humans are doing here. Hmm. And so I said like, we use language to communicate. We tap into experience and knowledge. We use instinct and judgment.
[00:27:34] Paul Roetzer: We read and understand emotions and behaviors and motivations of others through their words and actions. And it just doesn’t seem real that an AI can do this, and yet if you read the paper or if you listen to the people that built it, it seems like we’re not far from this. And so my whole point with talking about Cicero and sort of trying to connect some dots in very practical use cases for people is that.
[00:28:01] Paul Roetzer: The impact and opportunity and threats of AI are so much greater than what most people realize. And Cicero, to me is a very practical, a period, apparently semi near term application because they open source this research. So there’s, there’s nothing stopping someone from like reading the same stuff I did or listening to this podcast and be like, oh, should I go?
[00:28:26] Paul Roetzer: Hmm. And like, and just building an app just for salespeople. Yeah. Or building it for a specific solution. So yeah. I, I just think it’s a really tangible example of AI being way bigger than, Just solving for writing tools.
[00:28:40] Mike Kaput: Yeah, for sure. And it’s worth reminding people, especially those newer to the space, that when you read an article that says something like AI mastered the game of Go, or diplomacy or whatever, that’s really interesting and impressive.
[00:28:54] Mike Kaput: But the way a lot of the models underlying these technologies work, there are much wider applications. This the game is a test of much wider and bigger. Skills that, to your point, can be used in so many other real world contexts.
[00:29:11] Paul Roetzer: Yeah, and it just goes back, as we talked about in the responsible ai, you have to understand the true potential of what AI can do.
[00:29:20] Paul Roetzer: You have to understand its limitations. You have to understand its dangers, otherwise, you’re not going to be able to truly comprehend the impact it’s going to have on your organization and your own career. And I just. I think I said in that post that this could be, what did I say at the end? It could be in, within a year or maybe five to 10, like we don’t know.
[00:29:43] Paul Roetzer: What generally happens is these AI researchers have these breakthroughs or envision these breakthroughs, and they’re really horrible at actually knowing when they’re going to either truly achieve a breakthrough they’re proposing. Like AGI would be an example. Artificial general intelligence is the hot one has been for 10 years.
[00:29:59] Paul Roetzer: When are we going to get. You’ll get all these differing opinions. Could be in 12 months, could be in 12 years, could be in 50 years. They, they’re terrible at actually predicting when it’s going to happen or when it’s going to be commercialized. And I think this is an example of if you pulled a bunch of top AI researchers that says, what are we going to see the first real life application of Cicero in business, you might get, I think you could do it in three months or you might get, I don’t know, five, 10 years maybe.
[00:30:30] Paul Roetzer: They’re not right or wrong. Like no one knows . And I think that’s a big theme. You’ll, if you listen to this show often we don’t know, they don’t know. We just try and pay attention to what’s going on, connect the dots and give listeners the best information we have available so that you can figure out the impact on your own path.
[00:30:52] Paul Roetzer: And like, do you want to go learn about Cicero? That’s up to you. Like if you’re curious about you want to explore it, go down that. If you don’t then keep planning out with AI writing tools, like there’s no right or wrong path right now. Mm-hmm. , we’re just trying to give people a, a few different roads to pursue, I would say.
[00:31:09] Paul Roetzer: You
[00:31:09] Mike Kaput: know, and that’s a perfect lead in to our third main topic today, because this will give you just a sense of how quickly some of this stuff can come to pass. And so what we’ve seen. We’ve seen the first, at least on our end, that I’ve seen the first AI specific marketing job posting. So this was brought to our attention on LinkedIn.
[00:31:33] Mike Kaput: It comes from a climate tech company called tomorrow.io, and the job that they are hiring for is quote AI marketing specialist. So we’ll link to the full description in the show notes, but. Some highlights here, in addition to kind of your standard marketing specialist duties, things like creating and distributing content, managing social, et cetera.
[00:31:55] Mike Kaput: This role specifically calls out a couple of ai. Focus duties that an AI marketing specialist they want would have two of them include. First, stay up to date on the latest developments in AI and related technology to catapult our go-to-market organization forward at scale. And also envision the next iteration of tomorrow do iOS social media presence across channels using AI technologies such as natural language processing and machine learning.
[00:32:26] Mike Kaput: And so I first saw this because the CM email@example.com, Dan Slagan, who I don’t know personally, but have now since connected with on LinkedIn, he had a really amazing way to. This job and he said quote, let’s be honest, the future of marketing is knowing how to use AI to one plus one equals three.
[00:32:47] Mike Kaput: Everything. Knowing when to push AI further, knowing when to back off and be more human. But overall, embracing the fact that thinking AI first before doing anything is the best way to 10 x impact. And one other note here before I get your thoughts, Paul is. It’s also interesting to note this is a relatively junior role.
[00:33:07] Mike Kaput: This isn’t, expecting decades of deep experience in ai. Instead, it’s expecting you to have a couple years of marketing, experience and then having kind of the hunger, the knowledge, and the drive to leverage AI technology to go make an outsized impact. So I’m going to get your take on, you know, this job specifically, but also what does it mean for marketing work going forward.
[00:33:34] Paul Roetzer: We’ve talked about before that I think this is the year where we start seeing demand for AI savvy marketers skyrocket. Hmm. Because marketing leaders, business leaders, are under a lot of pressure from boards, from investors to figure out ai. And so when you turn to your organization, you’re going to see maybe some technical people.
[00:33:54] Paul Roetzer: Maybe you have data scientists, maybe you have a cio, maybe you had of digital transformation. If fantasize your company, you, you may have people who have been thinking about ai, machine learning, applications in particular for years who have not thought about its application at a business case level.
[00:34:10] Paul Roetzer: Like their job isn’t to sit around pondering the infusion of AI into marketing and sales and service and ops and product and HR and finance and legal. . And so once you realize AI’s potential and you turn to your organization, organization and say, well, who can figure this out? Like, all right, let’s start with marketing and sales and service.
[00:34:28] Paul Roetzer: Like let’s find a few use cases in tech in there. Who can do it? It’s not me, the data scientist, like it’s not going to be the CIO you need. You need the practitioners, like you’re going to need people who spend their day doing email or social media or advertising or communications or analytics or pr, whatever it.
[00:34:47] Paul Roetzer: To go find smarter technology. This is what we’ve been saying all along, AI’s just smarter technology. The best people to find the tools are the people who do the job every day. Hmm. So, okay, Mike, you’re spending 15 hours a week doing an email newsletter. Go find us a tool that can help us do that job in three hours better than we’re doing it.
[00:35:09] Paul Roetzer: Okay, who’s the best person to do that? It’s going to be Mike. Like it’s going to be the person who can sit there and say, well, here’s the 25 things I do every week related to our email, from list segmentation to subject line writing, to figuring out what time to send the things, to writing the emails, to designing emails, to picking images, to like all this stuff.
[00:35:27] Paul Roetzer: Log goes in email. The best people to solve for how to do that smarter, faster, are going to be the people who do it. So it makes sense that you’re going to want a bunch of AI savvy people on your team who aren’t afraid to go find and try new technologies. Hmm. And be able to analyze in a critical thinking way, which machines don’t have.
[00:35:46] Paul Roetzer: Critical thinking is a, is a human trait right now. Here’s what my work looks like today. Here’s my user story today. Here’s what it could look like tomorrow, three months, six months, 12 months from now when we get this tech. Hmm. So this is why we have been so bullish. That it was only a matter of time until marketing leaders figured out the importance of ai.
[00:36:08] Paul Roetzer: And then the next step would be demand for AI savvy talent. And it’s also why we built the piloting AI for Marketer series. Like we knew that there was going to come a time in the not so distant future where marketers in mass were going to have to figure this stuff out really fast. Hmm. And so we’re like, well, let’s build a step by step learning journey.
[00:36:26] Paul Roetzer: Eight hours of content, 17 on-demand courses they can learn in an end day. So that’s been our bet all along as we were going to get to this moment. And I think, you know, the post Dan shared and the summary great. Like, I think that’s the kind of thing you’re going to see a lot more marketers do. And it’s, it, it’s going to, we’re going to need the wider scale demand from the executive level, which we’re starting to see happen.
[00:36:50] Paul Roetzer: I mean, our AI for Writer Summit that we announced two weeks ago, Like 1200 people registered already. Yeah. Yeah. And it’s a lot of big brands and it’s like four or five people from these enterprises. Yeah. Like director level plus. And so we’re seeing it now where the director level and above, leaders are now jumping in to figure out specific areas.
[00:37:13] Paul Roetzer: And as soon as they do, they’re going to understand all the other implications and they’re going to have to look for this kind of,
[00:37:20] Mike Kaput: So it sounds like based on that analysis that we would expect to see at some point AI focused or AI specialized marketing jobs basically at every level of companies. I mean, the jobs that they already need people to do now will be the levels of jobs we see in quote AI marketing, correct.
[00:37:41] Paul Roetzer: Yeah, and you and I theorized this in the book even, so I mean we had like, what are the jobs of the future, the roles in the future in marketing. We were sort of trying to guess and look out, you know, example right now would be, and this goes back to the responsible ai, like the number, whatever, 11 or 12 about upskilling and reskilling.
[00:37:57] Paul Roetzer: So let’s say, It’s universally accepted at the moment that to get value out of AI writing tools, generative AI writing tools, you need to be good at prompting them. Mm-hmm. . So you could look at your team and say, okay, well we need people who are really good at prompting the ai, what to write and how to do it, and in what style and format and voice and tone and all these things.
[00:38:17] Paul Roetzer: Well, who can do that? Are you going to go hire that person? No, because they don’t exist. There’s no one coming out of university that is trained as a AI writing. Engineer or prompt associate, or whatever you want to call it. So your immediate thing is like, well, we need somebody who’s AI savvy, who wants to learn how to work with the machines.
[00:38:35] Paul Roetzer: Let’s look at our own team. Do we have somebody we can train to do this? Is it our existing writers? Are they willing to embrace AI tools or are they refusing to use them? So I, I don’t know. I think we’re in this really interesting phase where the talent is going to evolve. As we’ve said, AI’s not going to replace the writers, but writers who adopt AI will replace writers who don’t, or mm-hmm.
[00:38:54] Paul Roetzer: insert marketers, designers, whatever you want into that. And I think that’s what’s going to happen. And, and based on the pace of generative ai in particular, AI’s going to happen really fast. Like, not chat g B T level fast, but what we’re hearing from these enterprises, these businesses, Is they’re waking up to the need for people who can figure this stuff out and they, they don’t have time to wait.
[00:39:18] Paul Roetzer: So I hope that it’s a tipping point. I hope that we start seeing massive demand for AI savvy marketers, because that’s been our belief all along, is we need gen next Gen marketers, people who embrace this stuff and are willing to continually adapt what they do and how they.
[00:39:34] Mike Kaput: That’s a great point, and I think it’s probably worth, you know, before we dive into our rapid fire topics, I want to maybe just end this part of the discussion by, maybe we should set some expectations for the companies, maybe listening and thinking about this, especially if you’re new to the space, you’re, you’re not getting people that are being formally trained in school to hire for this.
[00:39:55] Mike Kaput: Correct. Yet, what should we, as. Companies and employers be thinking about in terms of the expectations of where to find this talent, how we get it, how we train it, et cetera.
[00:40:06] Paul Roetzer: Yeah, I would. I mean, again, I haven’t thought deeply about this. We haven’t been hiring a lot at the institute. Like, it’s not like we’re hiring a bunch of people, but even going back to my running my agency days, you know, the kinds of questions we would ask, like, I was always looking at strategic thinking, critical thinking.
[00:40:22] Paul Roetzer: I would get into things like, what was the last, you know, two business books or non fiction books you’ve read, like business book, marketing books. I would try. And, what blogs do you, read? What podcast do you listen? Like I was asking questions to understand their curiosity mm-hmm. And their commitment to ongoing learning.
[00:40:40] Paul Roetzer: I think you could probably do something very simple like that in your hiring and recruiting process. Have you tried ChatGPT yet? What did you use it for? What did you think about it when you used it? Mm-hmm. , what other AI technology have? You know, tested, have you played on with any of the Image General and just find people who obviously are curious.
[00:40:58] Paul Roetzer: If you’re interviewing a writer, a marketer who hasn’t tried ChatGPT yet, that’s not a good sign. Like , that’s, that would, that would tell me that they’re either not. Following very closely what is happening in the world and in the industry. Hmm. And they have a very low level of curiosity. Hmm. Like I mean, I hadn’t, again, until I’m saying it out loud, I haven’t thought about that.
[00:41:22] Paul Roetzer: But if I was interviewing a marketer right now and I asked, have you tried chat G B T? And they said, no, , I would probably end the interview . It’s, so I think you’re trying to hire people who are curious. Like who, who want to understand what’s possible and are constantly learning and testing things. And, and, and when you talk about ai, they, they have that like kind of high interest level to understand it because as long as you have that, then you can teach the rest.
[00:41:54] Paul Roetzer: Like you said, you’re not going to go find the people who’ve already taught this stuff. It’s going to be all self-taught at this point. Yeah, I would just find people who are curious, who are experimenting without getting paid to do it. Yep. That’s a great
[00:42:06] Mike Kaput: point. Yeah. The experimentation is so crucial. I just think of even our journey over the last, formally five or so years at the institute and well before that where it’s like I.
[00:42:16] Mike Kaput: Even we can’t predict where all this stuff was going. We had to idea, get our hands dirty and actually use it and see what was possible. And honestly, you have to do that constantly because what I learned three months ago May may no longer be
[00:42:29] Paul Roetzer: applicable today, as, as we’ll find out momentarily in the rapid fire section with an innovation that happened.
[00:42:35] Paul Roetzer: 30 minutes before we came on today. Yeah.
[00:42:37] Mike Kaput: And whatever innovations are happening while we are recording . Yeah. Seriously. I’m going to find out when we’re done. So let’s dive into the rapid fire because we have a bunch of really interesting things that have come down the line. So I’ll try to run through these quick and just get your.
[00:42:52] Mike Kaput: Initial thoughts on them, but we saw a round of earnings calls, you know, quarterly earnings calls from public companies, from big tech companies, some of the big names and leaders, and they’re all talking about ai. Now, I know Economically Tech has just gotten hammered in the last, you know, six to 12 months, but they’re.
[00:43:11] Mike Kaput: There’s so much bullish talk about the use of AI from companies like Google, Microsoft, and Meta, and I won’t, you know, go in depth on each of their positions. But yeah, Sundar Pichai, the c e O of Alphabet and Google saying, he’s excited about the AI driven leaps they are about to unveil in search and beyond.
[00:43:30] Mike Kaput: And there’s been tons and tons of commentary around. Google’s response to
[00:43:34] Paul Roetzer: chat e p T. And by the way, they have an event on February 8th, the day this comes out. So if , we may need a special like real time episode to talk about whatever Google announces on the eighth. We’re recording this on Monday the sixth, by the way, just for timestamp purposes.
[00:43:53] Mike Kaput: And so you also have, you know, Microsoft has been huge in the news, obviously with their partnership with OpenAI. Satya Andela, the c e o has said everything from the age of AI is upon us and Microsoft is powering it. He’s outlined how AI is being baked into, you know, many, many different Microsoft products in different.
[00:44:13] Mike Kaput: Areas of the business. I mean, we just saw some announcements around AI being incorporated into teams as well. And even, you know, meadow was getting that game as well, saying that, you know, Zuckerberg had said on the latest earnings call AI and the Metaverse are the company’s future. He specifically called out that these are the two major technological waves driving their roadmap.
[00:44:36] Mike Kaput: They’ve seen a ton of success in the short term. Investing in AI for their ads business. It’s done a huge amount to help them get more conversions for their ad product. Facebook and Instagram, he specifically said, are shifting from being organized solely around people and accounts you follow to increasingly showing more relevant content recommended by our AI systems.
[00:44:59] Mike Kaput: So Paul, when you see all this talk of ai. In earnings calls, what does that tell you about kind of the near future direction of where these companies are going?
[00:45:09] Paul Roetzer: Yeah. The other one I would throw in there is Apple, don’t sleep on them. Yes, Apple’s been doing some insane stuff with AI that they never talk about it as ai, but if just think about your iPhone and all the capabilities baked into the camera, and it’s actually gotten pretty good at voice to text.
[00:45:22] Paul Roetzer: I’ve noticed in recent weeks, I don’t know when that update got pushed out. Hmm. But they’re making some major improve. I think there’s major acquisitions on the horizon. Big tech’s going to move fast. Google put 300 million into Anthro Anthro last week, I think. Mm-hmm. , which is basically, going to compete with OpenAI in ways.
[00:45:40] Paul Roetzer: I think we’re going to kind of roll that capability in, become the cloud provider like Microsoft did with OpenAI. It’s going to move so fast. I, we’ve been talking about the Google Learnings call last week. I think we said watch for February 2nd. Yep. But yeah, if you look at, if you follow the transcripts and you look at the mentions of AI in the last week of these transcripts, it’s just like off the charts, you know, versus the norm.
[00:46:05] Paul Roetzer: So, yeah. Welcome to the future. This is . They’re all going to be, be this, it’s all analysts are going to want to know about in the, you know, months ahead, quarters. And like we started our book out. You know, that’s why we told the story of Microsoft, Google, and Amazon to start Apple. You know, we mentioned as a secondary player from a marketing perspective, but certainly not from a business perspective.
[00:46:26] Paul Roetzer: You have to follow what is happening at the big tech companies. Mm-hmm. to understand what is really going on and where this is all going. You, you can monitor all these startup gen, you know, generative AI companies and that’s great. We do it too. But the story is going to come from the big tech companies.
[00:46:44] Paul Roetzer: And it’s, I think it’s going to happen way faster than maybe we expect. Yeah.
[00:46:49] Mike Kaput: And another, related topic here is that in terms of how fast things are moving is that, feels like we’ve gone, Microsoft has just gone from zero to a hundred these days with ai, especially with their OpenAI partnership. And they actually have announced the day it’s been formally leaked.
[00:47:06] Mike Kaput: At least I think that, yeah. They plan to update Bing with a faster version of ChatGPT in the coming weeks. So they are, this is known as potentially G P T four that will be suddenly baked into Bing, which, you know, I don’t think a lot of people have historically thought of as a leading search engine, but really
[00:47:25] Paul Roetzer: incorporated.
[00:47:26] Paul Roetzer: I’ve never searched on Bing. Have you ever used Bing once?
[00:47:28] Mike Kaput: I have now because I was curious if they were, if they were incorporating anything Honestly. I have to say my first time using it was last
[00:47:36] Paul Roetzer: week. , I, I will, I will try it. And that, that same article or a different article. I also mentioned that a ChatGPT app is in the works, like a mobile app for ChatGPT and yes, the mythical G p T four that we’ve all heard about and seen the meme of the big, you know, parameters versus the small parameters.
[00:47:54] Paul Roetzer: It, it does seem like possibly our first interaction with G P T four could come through Microsoft product. No official word on from OpenAI on that one, but there was also a Forbes interview with Sam Altman that I, I know we shared over the weekend. Mm-hmm. . And then there was a New York Times article on the inside story of the launch of ChatGPT, which I think we get into in a moment as well.
[00:48:16] Paul Roetzer: But it, there, there’s so much. Going on. The other one not to sleep on is Microsoft Teams, you know? Yep. The, we don’t use it. We use, zoom and, we tried Google for a little while, but, you know, I think that someone asked me about what I thought the impact of ai, like G P T 3.5 for whatever it’s going to be, chat G B T into Microsoft Teams would do.
[00:48:40] Paul Roetzer: Mm-hmm. . And my response was, I think you have to assume Google and Zoom do the same thing within six months. So they’re going to feel arch. Like you’re going to get so used to the ai as long as you get over the privacy concerns. Like, I still don’t like when people jump into meetings and automatically start recording it.
[00:48:57] Paul Roetzer: That bothers me actually. . Yeah. When the AI note taker shows up without permission. But I think it’s going to, we’ll, we will break through that and you’re going to just accept that the AI’s there, taking notes, summarizing in real time, the call notes, finding tasks, and Recommenda recommended actions within the call notes.
[00:49:16] Paul Roetzer: I think that’s going to become, So accepted in such a short period of time. Yeah. That if you’re on a platform like Zoom or Google that don’t have that, it’s going to feel really old fast.
[00:49:30] Mike Kaput: Yeah. I think there’s probably a bigger trend here too, where it’s like, if you look at these two stories and you think, okay, if the biggest tech companies in the world with the most innovative businesses are facing this kind of pressure from shareholders, board members, executives, Answer the question, what are you doing with AI’s?
[00:49:49] Mike Kaput: A pretty good chance. You’re probably going to get similar questions at some point in your own business,
[00:49:55] Paul Roetzer: no doubt. .
[00:49:57] Mike Kaput: So another ChatGPT related story, and this is just pretty crazy, is that ChatGPT is estimated to have reached in January 100 million monthly active users, and that’s just two months after launch and it’s.
[00:50:14] Mike Kaput: Mine bot going to me, it’s only been two months. It just feels like a new era. This makes it according to, ubs, which I believe is a bank investment bank. This makes it the fastest growing consumer application in history. And for some context, it took TikTok about nine months to reach the same milestone, and it took Instagram two and a half years.
[00:50:37] Mike Kaput: What does the speed of growth here tell us about AI
[00:50:41] Paul Roetzer: adoption? Well, the craziest thing to me was, I actually, I think I shared this the day this came out, and then two days later was when the New York Times article about the inside story of the origin of ChatGPT emerged. Hmm. And in my post I’d said, I, I wonder what their stretch goal was, like, how many users they thought they might get.
[00:51:00] Paul Roetzer: Mm-hmm. when you reach a hundred million, like, did they think a million was crazy? And then you realize when you read the New York Times articles, they probably didn’t even know because Sam Altman basically mandated in a two week time to launch a chatbot. They took two year old technology and launched chat G B T in two weeks time.
[00:51:18] Paul Roetzer: So this wasn’t some like grand scheme that they looked out a year ahead and said, on November 30th, Lynch launched this thing called ChatGPT. They were worried that other, that competitors were going to launch something fast. Mm-hmm. . And so they scrambled to release something. That was, I think, originally called chat with G P T 3.5 was the actual internal working name.
[00:51:40] Paul Roetzer: So to think that this was a, a last minute decision that many people in OpenAI apparently didn’t think was going to work because they’d been playing with this AI for two years and didn’t think people would care or find it impressive that they hit a hundred million users almost by accident. Yeah. Is what makes this number even crazy.
[00:52:01] Paul Roetzer: And probably drives a bunch of SaaS executives, wild like , like all the time and energy put into product launches and planning. And here these guys. Fell into a hundred million users, so that’s, that’s
[00:52:13] Mike Kaput: incredible. . All right, so last but not least here, we added this after seeing it today. Runway ml, another, major player in the AI space released something called gen one.
[00:52:29] Mike Kaput: And based on the demo video, this is basically video to video AI that is able to generate videos in essentially any style and alter them. Based on your proms. Paul, do you want to tell us a little more about this and why it’s so
[00:52:44] Paul Roetzer: impressive? I mean, we’ve talked about runway numerous times on this show. It’s one of the more impressive AI companies I’ve ever seen.
[00:52:51] Paul Roetzer: I mean, I’ve been following ’em since 2019. We’ve played around with their image generation tech. I’m a subscriber. They’re not a sponsor of ours. Like I just talk about ’em cause it’s awesome tech. They have this AI magic tool suite that has like 30 pre-trained tools. If you’ve taken our piloting AI for marketer series, you’ve seen like infinite image is one of the.
[00:53:07] Paul Roetzer: The ones I showed within there. Mm-hmm. . So just an awesome company. Raised 50 million in December of 2022. I think that was their series C I don’t remember. But they’ve raised a bunch of money and it’s just, it’s awesome. Like just go to the link, check it out, or just search Gen one runway or whatever you need to search to get there.
[00:53:27] Paul Roetzer: Watch the minute and a half trailer video. It is wild. It’s basically you just take any video and you can layer over and like they show a video turned into Claymation and you. Text prompted to turn it into a claymation. So they have five, initial use cases or modes. One is stylization, two is storyboarding.
[00:53:46] Paul Roetzer: Three is masking where you isolate subjects in your video and modify them with te text prompts. Four is render where you turn on textured renders into realistic outputs by applying an an input image or prompt. And the last one was customization. So, Yeah, I mean, again, we talk all the time about the speed of change.
[00:54:05] Paul Roetzer: Ironically, I’m going down to Ohio University this week to do a talk on AI in the future of media to students and professors and administrators. And it’s like, what, what better demo to like pull into that presentation and just like, you know, you all do video and you do multimedia like, Here’s your future.
[00:54:22] Paul Roetzer: Like right now it’s happening. So just crazy. Like again, there’s, we see this stuff all day long and, and sometimes I see things and I’m just, you gotta stop for a minute and be like, really? Like this is wild . Yeah. And that’s, that was one of those tech where I just watched the video and thought, my gosh, like, this is hard to comprehend where we’re headed.
[00:54:41] Paul Roetzer: Yeah, I’m sure we’ll
[00:54:42] Mike Kaput: explore. Many different use cases for this as it’s really rolled out. But I just, it’s stunning to me, you know, from our background in the agency world. It’s not like we had always the ability to do this kind of really professional video creation and editing and on our own, or it was extremely expensive to do and I just have to believe there’s going to open up so many creative possibilities with this technology.
[00:55:07] Paul Roetzer: Yeah. Like anything else. You know, I think there’s two sides to this story. So there’s, you know, one of our friends commented right away, that his son is a professional video producer, looking forward to his comments. And I was like, yeah, me too. Hmm. So I think there is the. Us, the non-professional videographers who look at this like, mm-hmm.
[00:55:28] Paul Roetzer: Oh my gosh, what can we do now with a video that we couldn’t do before? Yeah, like you, your mind starts racing of possibilities. Like we could never do storyboarding at our agency. We didn’t have those capabilities, could you? Now, if we were still working in the agency, could we do that? Can we do that at the institute?
[00:55:43] Paul Roetzer: So you start thinking about the non-professional use cases and the creative possibilities that become possible. But what about the professionals? Professional videographers, vi video producers. Yep. You know, you’re going to look at this from an entirely different perspective. Your first reaction may be like, oh my God, like, I can’t believe it’s co possible.
[00:56:02] Paul Roetzer: I charge $10,000 to do what they’re doing with a text prompt. That’s one possibility. The other is, oh my gosh, what can I now do? Yeah. For, for clients, for my, my team, with these capabilities. So I think every time we’re going to have these generative AI advancements, there’s going to be these. A non-professional who looks at it says, I can now do things I couldn’t do before as we had with Dolly and Mid journey and stable diffusion.
[00:56:26] Paul Roetzer: And then you’re going to have the professional who either looks at it afraid or looks at it as, you know, a massive opportunity for themselves and their businesses. So, yeah, it’s crazy
[00:56:36] Mike Kaput: stuff to see. It’s, and it’s interesting to think through there. You know, it comes back to that thing about expectations. You, you have the big tech companies being grilled on how they’re using AI and why, what’s possible.
[00:56:47] Mike Kaput: I mean, if you are doing anything with a client or producing video for people, it’s like, Those expectations are going to change. If you’re an agency and you don’t historically do video, and a client asks, well why? Why can’t you? These tools exist. You’re going to get questions about what you can and can’t do with ai.
[00:57:05] Paul Roetzer: So, you and I were sort of half joking over the coffee machine this morning about who buys runway. I’m just going to, yeah, I’m going to throw this out there for fun. So now I’m wondering, like as we’re talking, you know, first my reaction was like, oh, Adobe or someone like that buys. I’m actually wondering if it isn’t like Pixar or Epic Games.
[00:57:23] Paul Roetzer: Like if, if actually like a, a video movie producer, video game production company. I just can’t, I can’t see a company like runway not getting bought up so fast. Right. And again, we have no Inside Knowledge. I don’t know anybody at runway. I talk to anybody at Runway. But when you look at tech like this and you think about the team and how much they’ve released, like go look at their release schedule.
[00:57:43] Paul Roetzer: Yeah, it’s crazy. Their products crazy over the last like eight weeks. It’s insane. Yeah. I don’t know. It’ll be, it’ll be crazy, but, I would be shocked if they’re not acquired this year. I don’t know if that’s their intention, but you see stuff like this and you think, man songs, they, they’ve gotta have like 10 calls this morning.
[00:58:02] Paul Roetzer: from Riot, right? From VCs, from acquisition targets, man, a lot of money sitting in these big companies that would kill for stuff like this. Yep. All right. Anyway. Good stuff, .
[00:58:14] Mike Kaput: Yep. Well, thank you again, Paul, really appreciate the insight and your take on this week in ai. So, until next week, we will, we’ll keep on top of everything so that we can inform the audience what’s going on in the world
[00:58:27] Paul Roetzer: of ai.
[00:58:28] Paul Roetzer: Thanks everyone for listening and watching. And be sure to, you know, leave a, a review and a rating on the podcast. We’ve had just amazing. Numbers in terms of the growth of the podcast, and we’d love to, you know, see it continue to grow and hear from our community, so we appreciate all your support.
[00:58:43] Paul Roetzer: Thanks for listening to the Marketing AI Show. If you like what you heard, you can subscribe on your favorite podcast app, and if you’re ready to continue your learning, head over to marketing ai institute.com. Be sure to subscribe to our weekly newsletter, check out our free monthly webinars, and explore dozens of online courses and professional certifications.
[00:59:04] Paul Roetzer: Until next time, stay curious and explore ai.