Digital Social Hour
AI Will Change Everything: Insights from Zeta Global CEO | David Steinberg DSH #1182
Sat, 15 Feb
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AI is reshaping our world, and this episode of Digital Social Hour with Sean Kelly dives into how! 🚀 Join us as David Steinberg, CEO of Zeta Global, shares eye-opening insights on AI’s transformative power, from revolutionizing marketing to the future of education, encryption, and even the metaverse. 🌍💡 Discover how Zeta’s cutting-edge AI platform is helping Fortune 100 companies lower marketing costs and drive revenue. 💼✨ Plus, David reveals his personal strategies for success, the power of networking, and why adaptability is key for entrepreneurs. 🙌 Don’t miss out on this packed episode filled with valuable insights and real talk about entrepreneurship, AI innovation, and the future of industries like blockchain, live shopping, and more. 🔑 Tune in now and get inspired by one of the tech world’s most forward-thinking leaders! DISCLAIMER: All references to “this quarter” refer to Q3 2024, and all references to “this year” refer to the first three quarters of 2024. 📺 Watch now and subscribe for more insider secrets. Hit that subscribe button and stay tuned for more eye-opening stories on the Digital Social Hour with Sean Kelly! 🚀 CHAPTERS: 00:00 - Intro 00:38 - ChatGPT Overview 04:59 - Specialized Recruiting Group Insights 10:55 - Midsize Language Models Explained 14:00 - Zeta’s Marketing Platform Features 16:32 - Self Funding vs Raising Capital 19:42 - Live Shopping & Innovative Commerce 22:21 - Exploring the Metaverse 24:33 - Understanding Blockchain Technology 27:14 - Learning from Failure 31:39 - Employee Treatment by David 33:40 - Importance of Networking 38:40 - The Role of Mentorship 40:14 - Where to Find David Online 40:58 - Outro APPLY TO BE ON THE PODCAST: https://www.digitalsocialhour.com/application BUSINESS INQUIRIES/SPONSORS: [email protected] GUEST: David Steinberg https://www.instagram.com/david_a_steinberg https://www.linkedin.com/in/dsteinberg1/ LISTEN ON: Apple Podcasts: https://podcasts.apple.com/us/podcast/digital-social-hour/id1676846015 Spotify: https://open.spotify.com/show/5Jn7LXarRlI8Hc0GtTn759 Sean Kelly Instagram: https://www.instagram.com/seanmikekelly/ #aiautomationagency #aiautomation #aiagency #aitools #zetaglobal #aiautomationagency #aiautomation #ainews #marketingautomation #aitools
Chapter 1: How is AI changing the tech landscape?
Any trends? No, you know, listen, everything right now is about artificial intelligence, right? It sort of really exploded with the launch of ChatGPT last fall. Und wir sehen jetzt, dass es wirklich durch jede Technologie rippelt. Und du wirst viel darüber hören, CES.
Ich bin gespannt, weil ich lernen liebe. Und ChatGPT hat das Lernen zehnmal schneller gemacht. Ich stimme. Es hat sicherlich die Antworten zehnmal schneller gemacht. Richtig. I'm summarizing books, because books take a while to read, let's be honest. And like 80% of books are kind of fluff. There's really only like key messages within books, in my opinion.
I learned when I was a kid, read the first paragraph of every chapter and the first sentence of every paragraph. Oh, wow. And I just started reading books like that. when I was much younger, which sped it up for me. The funny thing is, I would bet you that if you went into the average ChatGPT query and said, summarize this book, it will literally give you a lot of that.
Wow, I need to try that. Yeah. Well, I took the last week off of work and I was just doing personal development and I summarized 50 books.
Chapter 2: How can AI revolutionize learning?
Isn't everything you're doing here today personal development show? Pretty much, yeah. I mean, we're developing together. Yeah. But yeah, I summarized 50 books on ChatGPT. That would have taken me a full year to read. Oh, I'm sure. So I got all those key points and... Ich fĂĽhle mich viel klĂĽger.
Es ist unglaublich. Ich liebe es. Ich benutze Gemini in meinem Google. Ich benutze ChatGPT auf der Regel. Ich meine, natürlich, unsere Firma ist einer der größten Entwickler der Artifizierten Intelligenz. Und wir haben ein AI-Programm vor sieben Jahren begonnen. Wow. Nicht vor sieben Monaten. Wie hast du diese Vorsicht vor sieben Jahren?
Also lese ich viel. Ich lese hunderte verschiedene Dinge pro Monat und ich mache das, was ich Triangulation nenne. Wenn man drei einzelne Punkte mit einem zentralen Thema trianguliert, dann glaube ich, dass dieses Thema Dinge verändern wird. Und vor acht, neun Jahren habe ich angefangen zu lesen,
Wir arbeiteten bereits stark in der Automatik bei Zeta und wir dachten ĂĽber Maschinenlernung, Deep Learning und wir waren immer eine groĂźe Datenplattform. Mit all diesen Daten konnte kein Mensch sie mehr umsetzen. Und als wir ĂĽber die Zukunft nachgedacht haben, haben wir wirklich angefangen, Sean, auf natĂĽrliches Sprachlernen zu konzentrieren.
Die Fähigkeit, Trillionen von Datenpunkten zu ingestieren und sie in Intent zu verwandeln. Was wollen die Individuen jetzt tun? Und es war lustig, denn als wir Zeta im Juni 2021 öffentlich genommen haben, hatten wir ein großes Zeichen. Du hast ein Zeichen auf der Seite des New York Stock Exchange. Es ist eine Sache, die zu tun ist. Our sign said data plus AI equals intent in June of 2021.
Put it in perspective. People were asking me, who's Al and why is he in charge of your data strategy? It was that important. Far into people, even three years ago. That's fascinating. Well, they were probably working on OpenAI for years, right?
Oh, yeah, yeah, yeah. They'd been working on OpenAI for many years. And listen, AI has been around for a long time. The big leap was truly the launch of ChatGPT.
Yeah.
And I look at it and I think we're going to look back 10 years from now and say this was the renaissance moment for artificial intelligence. It's when AI went from science fiction to boardroom conversation.
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Chapter 3: What are mid-sized language models?
Nun, es gab dieses Kind in Princeton, an Princeton Universität. Hast du diese Geschichte gesehen? Nein. My theory on AI is you're going to have people using it for stuff they shouldn't use it for. My counter theory is we're going to have algorithms that protect us and algorithms that say whether something started its creation process with AI or with a human. It's all coming.
This young person at Princeton – I shouldn't say kid – Wow. Wow. Somebody asked me the other day, how is AI going to affect encryption? Because one day, quantitative computing is going to match with AI. In fact, not to sound like a total name dropper, recently I was talking to Elon Musk about this. Elon and I were sort of riffing on, how is quantum and AI going to come together?
I believe that the creation of quantum computing coupled with artificial intelligence will get us ten orders of magnitude greater than we are with AI today. But what's going to happen is as soon as that launches, every single piece of encryption, every passcode you have today is crackable in seconds.
Because quantum computing, which will think on a non-linear basis, will allow it to crack any code. So we're going to need to create algorithms that protect us. Und es wird ein bisschen so sein, wenn das passiert, dann musst du das haben. That's scary. As someone in the crypto space, if your seed phrase gets leaked, that's your whole bank account. They could send it in a second.
Well, once again, you're going to have an algorithm that will protect your crypto.
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Chapter 4: How does Zeta Global reduce marketing costs?
Yeah, so platforms need to start looking into that, right? They're already doing it. It's interesting because so often technology is adopted by people who want to do stuff with it that we might not like, right? More nefarious stuff. Yeah. Und oft dauert es eine Weile, bis die Technik, um uns zu schĂĽtzen, rauskommt.
Ich denke, wir werden hier ein bisschen einen Paradigmschiff sehen, weil ich schon Organisationen sehe, die Algorithmen bauen, um zu sagen, ob etwas mit AI angefangen hat oder nicht. Und ich denke, du wirst eine sehr ähnliche Sache mit Inkubation sehen. Elon ist sehr beschäftigt mit AI, Michael Haywire, richtig?
Wartest du mit ihm darĂĽber gesprochen? Wir sind ein bisschen dazu eingegangen. Die Wahrheit ist, wir haben mehr darĂĽber gesprochen, wie man in den Raum geht und die Wahl und wirklich auf AI konzentriert ist, was ich wirklich konzentriert bin und was wir mit Zeta tun. Aber...
Er hat sicherlich eine bedeutende Zeit darüber gesprochen, wie er glaubt, dass wir, wenn wir keine Geräte drauf haben, eine Herausforderung haben werden. Nun, natürlich hat er X-AI. Und dann hast du OpenAI und du hast, weißt du, irgendwie alle da draußen. Er hat auch Grock, oder? Korrekt. Ich habe noch nicht Grock benutzt. Hast du Grock benutzt?
Nicht persönlich. Wir haben damit viel gespielt. Wir machen viel mit OpenAI. Wir machen viel mit Gemini und mit einigen anderen Algorithmen. Wir bei Zeta haben unsere eigenen Algorithmen, die wir auf Python gebaut haben. Obwohl ich lache, das sind mittelgrössische Sprachmodelle. Was bedeutet das? Ich werde dir sagen, was das bedeutet, Sean.
Viele Leute sprechen ĂĽber groĂźe Sprachmodelle, was effektiv das gesamte Internet ist. Then you get into small language models, which a lot of people are talking about as the future, right? The ability to really hyper build and allow the algorithm to explore.
At Zeta, because 245 million people in the United States are in our data cloud, and because we're ingesting a trillion pages of content a day, I joke that's a mid-sized model. Right. Right. Unternehmen zeigen immer Ads zu Leuten, die nicht für ihre Produkte kreditabschätzt werden. Das ist eine Waste von Geld und es wird den Kunden scheißen.
Also versuchen wir das vor unserer Software, die ihre Marketing fĂĽr sie deployiert hat, zu eliminieren. Wir tun das, indem wir all diese Informationen investieren. Wir bauen etwas, was wir als CDP oder Konsumdatenplattform nennen. Wir investieren all ihre Daten. and we match it to the 245 million people in our data cloud. Brilliant.
We then ingest between 5 and 7 thousand incremental data elements in addition to pulling in a trillion pages of available content into the algorithm. And then there's no data exhaust. So by way of example, all of this stays proprietary to our enterprise clients. Unternehmen sind sehr besorgt ĂĽber ihre Informationen, die sie mit anderen Modellen teilen.
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Chapter 5: What is the secret to successful entrepreneurship?
Ich habe die erste Firma gestartet, als ich 21 war. Wow. Yeah, I didn't know any better. Yeah, right out of college, right?
Yeah, right. I came out of school. I went to work on the hill for about eight months. I read about this whole new thing called wireless back in 1990 and I started a series of wireless companies. So you attribute a lot of your success to reading. I would tell you that reading is a very important component of how I've built the strategy for the businesses that I've wanted to start.
The single biggest differentiator in what separates winning businesses from losing businesses, in my opinion, is execution. It's probably the most undervalued and most important component of any business. So, you know, the good news is for an ADD dyslexic like me, I've been able to surround myself with some of the world's greatest people.
And I bring in operators who can run their components of the business substantially better than I can. And I do something that's hard for a lot of entrepreneurs. I let them do their jobs. You're not a micromanager.
You know, there's this whole founder mode thing. And there are times I go into founder mode. I'll go very deep if there's an issue on something. But, you know, and I know the metrics of our business as well as anybody. But I try to focus on the things I'm really good at. And then I try to hire the world's greatest people to do what they do best.
Yeah, when you study the top companies, it seems like they got a visionary, like an Elon, a Bezos, someone like you. And then they have operators around them.
Ja, und mein Partner Steve Gerber, der Präsident und Chef-Operator ist der beste Operator, mit dem ich je gearbeitet habe. Mein CFO Chris Greiner ist der beste CFO, mit dem ich je gearbeitet habe. Mein General-Counsel Steve Vine, mein CTO Chris Monberg, unser Chef-Data-Officer Nish Gore. Diese Jungs, jeder von ihnen könnte ihre eigenen Firmen an diesem Punkt runnen.
Aber sie wählen, Teil unseres Kollektivs zu sein. Ich liebe es. Hast du dich zuerst selbst gefundet? Yeah, I did. So for this company, I put up the first capital, which is one of the reasons I think I'm the control investor in the company. Wow. A lot of people are quick to raise these days. Yeah.
You know, listen, it sounds great to raise a lot of money and there's a big benefit in it because you can go fast. I would tell you that if you looked at a chart of entrepreneurs who raised substantially more money than they needed, not only did they get diluted faster than they might have wanted to, but what happens is there's this sort of intrinsic pressure to spend the money.
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