The Five Rules for B2B Branding Success: Unlocking the Power of Memory

Being able to attend LinkedIn’s first B2B Marketing conference, B2Believe was a real privilege and amazing experience. Hearing from the wealth and depth of B2B marketing and business expertise that exists within LinkedIn was equally informative and inspiring. One of the presentations that really stuck with me was about the power of Memory for B2B branding.

In the fast-paced world of B2B branding, standing out from the competition and being remembered is crucial. In this blog post, I will share the key rules for effective B2B branding, drawing insights from a presentation by Mimi Turner, Head of EMEA & Latin America, The B2B Institute at LinkedIn.

I think we can all agree that by understanding the power of memory and leveraging strategic techniques, B2B businesses can gain access to the untapped opportunities in brand building. Here’s a summary of the five essential rules Mimi shared that can help shape your B2B branding strategy.

Rule 1: The 95/5 Rule – Understanding the Buying Cycle

One of the fundamental insights revealed in Mimi’s presentation was the 95/5 rule. I’ve heard Ty Heath also talk about this concept. It states that at any given moment, only 5% of B2B buyers are actively in the market, considering a purchase. The remaining 95% are not actively engaged in the buying process. This highlights the need for two distinct strategies: one for in-market buyers and another for out-of-market buyers. By recognizing these two groups and tailoring approaches to each, businesses can effectively capture attention and create brand recall.

Rule 2: The Power of Memory and Consideration

Memory plays a pivotal role in B2B branding. To be considered during the decision-making process, a brand must be remembered by potential buyers. Research indicates that buyers often start with a shortlist of familiar vendors when making a purchase. Therefore, being part of the consideration set is critical. Building memory structures through storytelling, colors, codes, and even catchy jingles can enhance brand recall and increase the chances of being selected.

Rule 3: Emotional Context in B2B Decision Making

Contrary to the belief that B2B decisions are solely rational, emotions and social considerations heavily influence the choices made. B2B purchases have far-reaching consequences, impacting teams, bosses, and job security. Acknowledging the emotional and social dimensions of these decisions allows brands to connect with buyers on a deeper level. By understanding the context and motivations of B2B decision-makers, brands can develop messaging that resonates and fosters stronger relationships.

Rule 4: Reach Maximization vs. Reach Minimization

B2B and B2C branding strategies exhibit distinct differences. B2C brands tend to adopt a reach maximization approach, utilizing a wide range of channels and creative strategies. In contrast, B2B brands often adopt a reach minimization approach, narrowing their focus to specific channels and emphasizing informational and educational content. However, to truly stand out and reach potential buyers, B2B brands can benefit from adopting a broader reach maximization strategy, effectively leveraging various channels and creative techniques.

Rule 5: Building Strategic Assets

While many B2B brands focus on short-term, response-driven campaigns, the true opportunity lies in building long-term strategic assets. These assets are ideas or campaigns that are committed to over time, maximizing reach, and creating lasting brand recall. Surprisingly, only a small percentage of B2B marketers focus on these strategic assets, presenting a significant opportunity for businesses that embrace this approach.

Making B2B Marketing memorable with AJ Wilcox and Mimi Turner at B2Believe 22

As you can see, B2B branding success can depend a lot on understanding the rules that govern the memory and decision-making processes of buyers. By embracing the 95/5 rule, optimizing for memory, recognizing the emotional context of decisions, adopting a reach maximization strategy, and building strategic assets, B2B businesses can position themselves for success. The untapped potential in B2B branding is vast, and those who take a proactive and strategic approach can differentiate themselves and leave a lasting impression in the minds of buyers.

Connect with Mimi on LinkedIn and The B2B Institute here.

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Elevate B2B Marketing News Weekly Roundup: CMO Tech Budgets Hold Steady Ad Index Grows & LinkedIns AI Push

CMOs’ Major Resource Allocations to Remain Steady Amid Budget Pressures
Marketing technology budgets have held steady from 2022 to 2023, as 75 percent of chief marketing officers say they are confronted by pressures to do more with less, while 49 percent expect to increase their influencer marketing spending — the area least likely to see budget cuts, according to newly-published CMO survey data. MarketingCharts

U.S. Ad Index Expands For First Time In 11 Months In May
60 percent of overall U.S. media spending came from the digital sector during May, 2023 — up from 56 percent a year earlier, as the overall ad spending level increased for the first time in 11 months, according to recent ad index data. MediaPost

LinkedIn Launches Live Test of Generative AI Posts
Microsoft-owned LinkedIn has expanded its testing of optional generative AI technology for the creation of posts on the professional social platform, offering first-draft suggestions to certain users, LinkedIn recently announced. Social Media Today

Most Social Media Marketers Are Confident in Their Ability to Adopt AI for Marketing
49 percent of social media marketing professionals have said that they see customer behavioral segmenting and targeting as the top use for AI, with 45 percent pointing to predictive analytics and the use of dynamic pricing based on real-time data — three of the findings contained in recently-published survey data of interest to B2B marketers. MarketingCharts

Long taglines using ‘rare’ words are most memorable but least liked, study reveals
Choosing whether to focus on being remembered or being liked is a key decision when it comes to brand slogans, as brands seeking long-term recognition benefit from slogans that incorporate unusual and concrete words, according to newly-released research data. MarketingWeek

Forrester: Nearly One-Third Of Ad Agency Jobs Will Be “At Risk” From Automation By 2030
Despite almost of third of advertising agency jobs being at risk from automation by 2030, double-digit growth for market research and marketing specialists is expected by 2030, according to recent Forrester and U.S. Bureau of Labor data. MediaPost

Marketing When Budgets Are Down
When it comes to marketing effectively during challenging times, clarity, courage, and connection hold increasing importance in 2023’s era of less, and the Harvard Business Review recently took a look at measures to deliver marketing results and grow business despite economic challenges. Harvard Business Review

Google In Hot Water: Billions At Stake As YouTube Ads Found To Violate Terms Of Service
Search giant Google has come under pressure for having possibly misled businesses advertising on its YouTube and other properties through its Google Video Partners program, according to newly-published report data, as Google has in turn rejected the report findings as inaccurate. Search Engine Journal

YouTube Launches First Stage of Thumbnail A/B Testing in YouTube Studio
Google’s YouTube has begun tests that allow users of the video platform to perform comparison performance tests between several different video thumbnail images, which could lead to new opportunities for B2B brands to conduct A/B testing, YouTube recently announced. Social Media Today

How AI is impacting search advertising’s growth
Search engine advertising has begun seeing shifts due to the incorporation of generative AI technology in offerings from Google and Microsoft’s Bing, as spending for search advertising was expected to climb to $279.3 billion in 2023 — up from $251.7 billion in 2022, according to recently-published search advertising data of interest to digital marketers. DigiDay

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“The turmoil unleashed by new AI tools and a changed landscape will be the best thing ever for SEO.” — Eli Schwartz @5le
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ON THE LIGHTER SIDE:

A lighthearted look at “Innovation and TikTok” by Marketoonist Tom Fishburne — Marketoonist

Argonne Aurora A21: All’s Well That Ends Better — The Next Platform

TOPRANK MARKETING & CLIENTS IN THE NEWS:

• Ty Heath / LinkedIn — B2B advertising doesn’t need to be boring: why creativity is a key driver of profitability — ClickZ
• Lee Odden — Here Are 6 Reasons Social Media Is Terrible: Why You Should Still Use It — Spartan Alliance
• Lane R. Ellis — The Happiest Man in Social Media & Marketing [Podcast] — Lane Ellis — Are You Happy Podcast

FRIDAY FIVE B2B MARKETING FAVORITES TO FOLLOW:

Carla Johnson @CarlaJohnson
Gini Dietrich @ginidietrich
Ardath Albee @ardath421
Joe Lazauskas @joelazauskas
Zontee Hou @ZonteeHou

Learn more about TopRank Marketing‘s mission to help elevate the B2B marketing industry.

Have you uncovered a key B2B marketing news item that we haven’t yet covered? If so, please don’t hesitate to drop us a line in the comments below.

Thank you for taking the time to join us for this week’s edition of the Elevate B2B Marketing News, and we hope that you will return next Friday for another array of the most up-to-date and relevant B2B and digital marketing industry news. In the meantime, you can follow us on our LinkedIn page, or at @toprank on Twitter for even more timely daily news.

The post Elevate B2B Marketing News Weekly Roundup: CMO Tech Budgets Hold Steady, Ad Index Grows, & LinkedIn’s AI Push appeared first on B2B Marketing Blog - TopRank®.

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AI & Creativity: Key B2B Marketing Insights From The 2023 Cannes Creative B2B Lions

As more B2B marketers than ever gathered recently for the Cannes Creative B2B Lions at the Cannes Lions International Festival of Creativity, it’s natural to wonder — just what are the key insights that emerged, and how can B2B marketers best put them to use?

Although the event celebrated its 70th anniversary in 2023, it was only the second year where B2B marketers had their own special section of the festivities in the form of the Creative B2B Lions, including an array of B2B-specific marketing award categories.

Let’s jump right in and examine some of the key themes and trends from this year’s second-annual Cannes Creative B2B Lions.

AI Top of Mind & Poised To Touch Every Aspect of Marketing

Generative AI continued its run as 2023’s centerpiece topic at Cannes just as it has in nearly all segments of society, as marketers in B2C and B2B have continued grappling with how to best use the technology while maintaining — and growing — brand authenticity and trust.

“AI has the potential to revolutionize every single part of marketing,” Marie Gulin-Merle, global vice president of ads marketing at Google, suggested after presenting curing Cannes.

Because of the AI innovations 2023 has seen, Guilin-Merle called this an exciting time for marketers. “Marketing is about connecting brands and products to people,” she noted. “The ‘what’ remains the same. The ‘how’ is changing again. Marketers, we can finally get back to marketing,” she observed, while offering up a list of some of the AI tools that Google’s own marketing teams are working with, including:

• Bard experimental conversational AI service
• Imagen and Phenaki text-to-image and text-to-video tools
• PaLM API for generating social media copy
• Gmail and Google Docs “Help me write” feature

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“AI has the potential to revolutionize every single part of marketing. The ‘what’ remains the same. The ‘how’ is changing again. Marketers, we can finally get back to marketing.” — Marie Gulin-Merle @MarieGulin
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Our own CEO Lee Odden recently delivered a keynote about AI’s impact on B2B marketing, presenting “Human vs Machine: The Future of B2B Content Marketing” during the BtoB Summit Paris 2023 conference.

Lee began his presentation explaining how generative AI essentially “makes you more of what you already are,” with poor content simply being turned into even more sub-par content if that’s what a marketer brings to the AI table, while those who instead present creativity and imagination to AI tools will be rewarded with even more quality B2B marketing content that is creative and imaginative.

As the team at Think With Google recently looked at as its weekly “big topic,” it’s more a matter of AI plus creativity, and not AI versus creativity.

As a hot topic at Cannes, AI and how it can best be used by B2B marketers is an issue we’ve spent considerable time effort to explore here on the TopRank Marketing blog, including the following pieces:

• A Home-Run for Humanizing B2B Content: Why Generative AI Can Only Get Your Business to First Base
• Top 5 Insights B2B Marketers Need To Know About Google’s AI Search Future
• Humanize, Organize, Strategize & Personalize: 4 Ways To Boost B2B Influencer Marketing With Generative AI
• 5 Key Ways Generative AI is Changing the Future of SEO from Google’s Bard to Microsoft’s Prometheus-Based Bing
• Standing Out From AI: Why Humanizing B2B Marketing Is Key In 2023
• The Prompt Whisperer: ChatGPT’s Rising Reach In B2B Marketing & The AI Revolution

Creativity Drives Profitability And Pushes Boring B2B Aside

Creativity is playing an even more important role in B2B marketing in the age of generative AI, simultaneously helping to increase brand awareness and drive profitability — all qualities that surfaced time and again during Cannes.

The Creative B2B Lions event and awards were established in 2022 in conjunction with the B2B community — most notably The B2B Institute — the industry think tank by LinkedIn* that researches the future of B2B marketing and decision making.

Tyrona Heath, director of market engagement at The B2B Institute at LinkedIn, shared some of the many ways that creativity adds value to today’s B2B marketing efforts, in “B2B advertising doesn’t need to be boring: why creativity is a key driver of profitability.”

“Creativity plays a significant role in building and expanding your brand size,” Heath explained.

“It leads to increased brand recognition, differentiation, customer loyalty, and ultimately having a larger market presence. And investing in creativity has a positive impact on financial performance because it serves as a multiplier,” Heath added.

As Cannes wrapped up, Heath further reflected on the increasing power of creativity.

“In this second year of the Creative B2B Lions, I am inspired by the caliber of work we encountered. Imagining what the future holds, I can’t wait to see how B2B creativity will continue to evolve 5, 10, and 15 years from now,” Heath — who served as a juror during the event — noted.

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“In this second year of the Creative B2B Lions, I am inspired by the caliber of work we encountered. Imagining what the future holds, I can’t wait to see how B2B creativity will continue to evolve 5, 10, and 15 years from now.” — @Tyrona
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During Cannes Lions the LinkedIn Collective broadcast live from the event, with a variety of LinkedIn Live sessions exploring the trends and challenges surrounding AI in B2B marketing, now available on-demand in, “AI-Powered B2B Marketing: Trends & Dangers,” and a lively conversation about diversity, equity, and inclusion (DEI) within the B2B marketing landscape, in “Prioritizing DEI in B2B Organizations.”

B2B marketing is undergoing significant shifts, if not an outright renaissance, as Tom Stein, chairman and chief growth officer at Stein IAS and Creative B2B Lions jury president, noted that, “This is B2B’s decade. It started on stage in Cannes last night.”

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“This is B2B’s decade. It started on stage in Cannes last night.” — Tom Stein @Tom_Stein
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As another of the key trends at Cannes this year, the rising power of creativity in 2023 has been the subject of several articles we’ve recently published, including:

• Elevate B2B Marketing Podcast: Creativity & Inclusivity in B2B Marketing with Ty Heath
• What B2B Marketers Need to Know from LinkedIn’s New Benchmark Report
• 4 B2B Marketing Lessons from Disney’s The Little Mermaid
• Equilibrium: 10 Tips to Balance Creativity and Process in B2B Content Marketing
• Solvable Strategy: 4 B2B Marketing Take-Aways from Board Games

Use AI & Creativity To Elevate B2B Marketing

Generative AI and creativity may initially appear as two altogether different endeavors, however as our take-aways from Cannes have shown, both offer compelling justifications for B2B marketers to use, especially when each is factored into the other’s strategy.

The future of B2B marketing is poised to feature a uniquely human touch optimized with AI for creative storytelling.

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“The future of B2B marketing is poised to feature a uniquely human touch optimized with AI for creative storytelling.” — Lane R. Ellis @lanerellis
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We hope that the Cannes insight we’ve shared here will help you in your own efforts to elevate B2B marketing throughout 2023 and beyond.

To learn more about B2B marketing imagined by humans and optimized by machines, be sure to catch our CEO Lee Odden presenting during B2B Ignite London on Thursday, June 29, 2023 at 2:00 p.m., with a presentation entitled, “The New Kingdom of Content in 2023 and How to Wear the Crown.” Get the full details — including Lee’s list of eight must-see sessions during the event — in “The New Kingdom of Content for B2B Marketing – TopRank at B2B Ignite London.”

More than ever before, creating award-winning B2B marketing that elevates, gives voice to talent, and humanizes with authenticity takes considerable time and effort, which is why more brands are choosing to work with a top digital marketing agency such as TopRank Marketing. Reach out to learn how we can help, as we’ve done for over 20 years for businesses ranging from LinkedIn, Dell and 3M to Adobe, Oracle, monday.com and many others.

* LinkedIn is a TopRank Marketing client.

The post AI & Creativity: Key B2B Marketing Insights From The 2023 Cannes Creative B2B Lions appeared first on B2B Marketing Blog - TopRank®.

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Unveiling The Future Of AI

Unveiling The Future Of AI written by John Jantsch read more at Duct Tape Marketing

Marketing Podcast with Kenneth Wenger

In this episode of the Duct Tape Marketing Podcast, I interview Kenneth Wenger. He is an author, a research scholar at Toronto Metropolitan University, and CTO of Squint AI Inc. His research interests lie at the intersection of humans and machines, ensuring that we build a future based on the responsible use of technology.

His newest book, Is the Algorithm Plotting Against Us?: A Layperson’s Guide to the Concepts, Math, and Pitfalls of AI. Kenneth explains the complexity of AI, demonstrating its potential and exposing its shortfalls. He empowers readers to answer the question: What exactly is AI?

Key Takeaway:

While significant progress has been made in AI, we are still at the early stages of it’s development. However, the current AI models are primarily performing simple statistical tasks rather than exhibiting deep intelligence.The future of AI lies in developing models that can understand context and differentiate between right and wrong answers.

Kenneth also emphasizes on the pitfalls of relying on AI, particularly in the lack of understanding behind the model’s decision-making process and the potential for biased outcomes. The trustworthiness and accountability of these machines are crucial to develop, especially in safety-critical domains where human lives could be at stake like in medicine or laws. Overall, while AI has made substantial strides, there is still a long way to go in unlocking its true potential and addressing the associated challenges.

Questions I ask Kenneth Wenger:

• [02:32] The title of your book is the algorithm plotting against this is a bit of a provocative question. So why ask this question?
• [03:45] Where do you think we really are in the continuum of the evolution of AI?
• [07:58] Do you see a day where AI machines will start asking questions back to people?
• [07:20] Can you name a particular instance in your career where you felt like “This is going to work, this is like what I should be doing”?
• [09:25] You have both layperson and math in the title of the book, could you give us sort of the layperson’s version of how it does that?
• [15:30] What are the real and obvious pitfalls of relying on AI?
• [19:49] As people start relying on these machines to make decisions that are supposed to be informed a lot of times, predictions could be wrong right?

More About Kenneth Wenger:

• Get your copy of Is the Algorithm Plotting Against Us?: A Layperson’s Guide to the Concepts, Math, and Pitfalls of AI.
• Connect with Kenneth.

More About The Agency Certification Intensive Training:

• Learn more about the Agency Certification Intensive Training here

Take The Marketing Assessment:

• Marketingassessment.co

Like this show? Click on over and give us a review on iTunes, please!

Duct Tape Transcript

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John Jantsch (00:00): Hey, did you know that HubSpot's annual inbound conference is coming up? That's right. It'll be in Boston from September 5th through the eighth. Every year inbound brings together leaders across business, sales, marketing, customer success, operations, and more. You'll be able to discover all the latest must know trends and tactics that you can actually put into place to scale your business in a sustainable way. You can learn from industry experts and be inspired by incredible spotlight talent. This year, the likes of Reese Witherspoon, Derek Jeter, Guy Raz, are all going to make appearances. Visit inbound.com and get your ticket today. You won't be sorry. This programming is guaranteed to inspire and recharge. That's right. Go to inbound.com to get your ticket today.

(01:03): Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch. My guest today is Kenneth Wenger. He's an author, research scholar at Toronto Metropolitan University and CTO of Squint AI Inc. His research interests lie in the intersection of humans and machines, ensuring that we build a future based on the responsible use of technology. We're gonna talk about his book today Is the Algorithm Plotting Against Us?: A Layperson's Guide to the Concepts, Math, and Pitfalls of AI. So, Ken, welcome to the show.

Kenneth Wenger (01:40): Hi, John. Thank you very much. Thank you for having me.

John Jantsch (01:42): So, so we are gonna talk about the book, but I, I'm just curious, what, what does Squint AI do?

Kenneth Wenger (01:47): That's a great question. So, squint ai, um, is a company that we created to, um, do some research and develop a platform that enables us to, um,

(02:00): Do, do AI in a more responsible, uh, way. Okay. Okay. So, uh, I'm sure we're gonna get into this, but I touch upon it, uh, in the book in many cases as well, where we talk about, uh, ai, ethical use of ai, some of the downfalls of ai. And so what we're doing with Squint is we're trying to figure out, you know, how do we try to create a, an environment that enables us to use AI in a way that lets us understand when these algorithms are not performing at their best, when they're making mistakes and so on. Yeah,

John Jantsch (02:30): Yeah. So, so the title of your book is The Algorithm Plotting Against, this is a bit of a provocative question. I mean, obviously I'm sure there are people out there that are saying no

Kenneth Wenger (02:49): Well, because I, I actually feel like that's a question that's being asked by many different people with actually with different meaning. Right? So it, it's almost the same as the question of is AI posing an existential threat? I, I, it's a question that means different things to different people. Right. So I wanted to get into that in the book and try to do two things. First, offer people the tools to be able to understand that question for themselves, right. And first figure out how, where they stand in that debate, and then second, um, you know, also provide my opinion along the way.

John Jantsch (03:21): Yeah, yeah. And I probably didn't ask that question as elegantly as I'd like to. I actually think it's great that you ask the question, because ultimately what we're trying to do is let people come to their own decisions rather than saying, this is true of ai, or this is not true of AI

Kenneth Wenger (03:36): That's right. That's right. And, and, and again, especially because it's a nuanced problem. Yeah. And it means different things to different people.

John Jantsch (03:44): So this is a really hard question, but I'm gonna ask you, you know, where are we really in the continuum of, of AI? I mean, people who have been on this topic for many years realize it's been built into many things that we use every day and take for granted, obviously we ChatGPT brought on a whole nother spectrum of people that now, you know, at least have a talking vocabulary of what it is. But I remember, you know, I've been, I've been, I've had my own business 30 years. I mean, we didn't have the web

Kenneth Wenger (04:32): You know, that's a great question because I think we are actually very early on. Yeah. I think that, you know, we, we've made remarkable progress in a very short period of time, but I think it's still, we're at the very early stages. You know, if you think of ai where we are right now, we were a decade ago, we've made some progress. But I think the, fundamentally, at a scientific level, we've only started to scratch the surface. I'll give you some examples. So initially, you know, the first models, they were great at really giving us some proof that this new way of posing questions, you know, the, uh, neural networks essentially. Yeah, yeah. Right. They're very complex equations. Uh, if you use GPUs to, to run these complex equations, then we can actually solve pretty complex problems. That's something we realized around 2012 and then after around 2017, so between 2012 and 2017, progress was very linear.

(05:28): You know, new models were created, the new ideas were proposed, but things scaled and progressed very linearly. But after 2017, with the introduction of the model that's called the Transformer, which is the base architecture behind chat, g, pt, and all these large language models, we had another kind of realization. That's when we realized that if you take those models and you scale them up and you scale them up in, in terms of the size of the model and the size of the data set that we used to train them, they get exponentially better. Okay. And that's when we got to the point where we are today, where we realized that just by scaling them, again, we haven't done anything fundamentally different since 2017. All we've done is increase the size of the model, increase the size of the dataset, and they're getting exponentially better.

John Jantsch (06:14): So, so multiplication rather than addition?

Kenneth Wenger (06:18): Well, yes, exactly. Yeah. So, so it isn't, the progress has been exponential, not only in linear trajectory. Yeah. But I think, but again, the fact that we haven't changed much fundamentally in these models, that's going to taper off very soon. It's my expectation. And now where are we on the timeline? Which was your original question. I think if you think about what the models are doing today, they're doing very element. They're doing very simple statistics, essentially. Mm-hmm.

John Jantsch (07:39): Absolutely. I mean, I totally agree with you on artificial intelligence. I've actually been calling it ia. I think it's more of informed automation.

Kenneth Wenger (08:06): Yeah. So the, the, the simple answer is yes. I, I definitely do. And I think that's part of what, what achieving a higher level intelligence would be like. It's when they're not just doing your bidding, it's not just a tool. Yeah, yeah. Uh, but they, they kind of have their own purpose that they're trying to achieve. And so that's when you would see things like questions essentially, uh, arise from the system, right? Is when they, they have a, a, a goal they wanna get at, which is, you know, and, and then they figure out a plan to get to that goal. That's when you can see emergence of things like questions to you. I don't think we're there yet, but yeah, I think it's certainly possible.

John Jantsch (08:40): But that's the sci-fi version too, right? I mean, where people start saying, you know, the movies, it's like, no, no, Ken, you don't get to know that information yet. I'll decide when you can know that

Kenneth Wenger (08:52): Well, you're right. I mean, the question, the way you asked the question was more like, is it, is it possible in principle? I think absolutely. Yes. Yeah. Do we want that? I mean, I, I don't know. I guess that's part of, yeah, it depends on what use case we're thinking about. Uh, but from a first principle's perspective Yeah, it is, it is certainly possible. Yeah. Not to get a model to

John Jantsch (09:13): Do that. So I, I do think there are scores and scores of people, they're only understanding of AI is I go to this place where it has a box and I type in a question and it spits out an answer. Since you have both layperson and math in the title, could you give us sort of the layperson's version of how it does that?

Kenneth Wenger (09:33): Yeah, absolutely. So, well, at least I'll try, lemme put it that way,

(10:31): So basically for any word in a, in a, in a prompt or in a corpus of text, they calculate the probability that word belongs in that sequence. Right? And then they choose the, the next word with the highest probability of being correct there. Okay? Now, that is a very simple model in the following sense. If you think about how we communicate, right? You know, we're having a conversation right now. I think when you ask me a question, I, I pause and I think about what I'm about to say, right? So I have a model of the world, and I have a purpose in that conversation. I come up with the idea of what I want to respond, and then I use my ability to produce words and to sound them out to communicate that with you. Right? It might be possible that I have a system in my brain that works very similar to a large language model, in the sense that as soon as I start saying words, the next word that I'm about to say is one that is most likely to be correct, given the words that I just said.

(11:32): It's very possible. That's true. However, what's different is that at least I already have a plan of what I'm about to say in some latent space. I have already encoded in some form. What I want to get across, how I say it, that the ability to pro to produce those words might be very similar to a language model. But the difference is that a large language model is trying to figure out what it's going to say as well as coming up with those words at the same time. Mm-hmm.

John Jantsch (12:20): I, I, I have certainly seen some output that is pretty interesting along those lines. But, you know, as I heard you talk about that, I mean, in a lot of of ways that's what we're doing is we're querying a database of what we've been taught, are the, the words that we know in addition to the concepts that we've studied, uh, and are able to articulate. I mean, in some ways we're querying that to me, prompting or me asking you a question as well, I mean, it works similar. Would you say

Kenneth Wenger (12:47): The aspect of prompting a question and then answering it, it's similar, but what is different is the, the concept that you're trying to describe. So, again, when you ask me a question, I think about it, and I come up with, so I, again, I have a world model that works so far for me to get me through life, right? And that world model lets me understand different concepts in different ways. And when I'm about to answer your question, I think about it, I formulate a response, and then I figure out a way to communicate that with you. Okay? That step is missing from what these language models are doing, right? They're getting a prompt, but there is no step in which they are formulating a response with some goal, right? Right? Yes. Some purpose. They are essentially getting a text, and they're trying to generate a sequence of words that are being figured out as they're being produced, right? There's no ultimate plan. So that, that's a very fundamental difference.

John Jantsch (13:54): And now, let's hear a word from our sponsor, marketing Made Simple. It's a podcast hosted by Dr. J j Peterson and is brought to you by the HubSpot Podcast Network, the audio destination for business professionals marketing made simple, brings you practical tips to make your marketing easy and more importantly, make it work. And in a recent episode, JJ and April chat with StoryBrand certified guides and agency owners about how to use ChatGPT for marketing purposes. We all know how important that is today. Listen to marketing Made Simple. Wherever you get your podcasts.

(14:30): Hey, marketing agency owners, you know, I can teach you the keys to doubling your business in just 90 days, or your money back. Sound interesting. All you have to do is license our three-step process that's gonna allow you to make your competitors irrelevant, charge a premium for your services and scale perhaps without adding overhead. And here's the best part. You can license this entire system for your agency by simply participating in an upcoming agency certification intensive look, why create the wheel? Use a set of tools that took us over 20 years to create. And you can have 'em today, check it out at dtm.world/certification. That's DTM world slash certification.

(15:18): I do wanna come to like what the future holds, but I want to dwell on a couple things that you dive into in the book. What are the, you know, other than sort of the fear that the media spreads

Kenneth Wenger (15:38): I think the biggest issue, and one of the, I mean the, the, the real motivator for me when I started writing the book is that it is a powerful tool for two reasons. It's very easy to use, seemingly, right? Yeah. You can spend a weekend learning python, you can write a few lines, and you can transform, you can analyze, you can parse data that you couldn't before just by using a library. So you don't really have to understand what you're doing, and you can get some result that looks useful, okay? Mm-hmm.

(16:42): In a, in, in a way that can affect other people. For example, you know, let's say you work in a financial institution and, and, and, and you come up with a model to figure out, uh, who you should, who you should give some credit, get, you know, approved for, for credit for a credit line, and who you shouldn't. Now, right now, banks have their own models, but sure, if you take the AI out of it, traditionally those models are thought through by statisticians, and they may get things wrong once in a while, but at least they have a big picture of what it means to, you know, analyze data, biasing the data, right? What are the repercussions of bias in the data? How do you get rid of all these things are things that a good statistician should be trained to do. But now, if you remove the statisticians, because anybody can use a model to analyze data and get some prediction, then what happens is you end up denying and approving credit lines for people who, with you, you know, with repercussions that could be, you know, driven by very negative bias in the data, right?

(17:44): Like, it could affect a certain section of the population, uh, negatively. Maybe there's some that can't get a credit line anymore just because they live in a particular neighborhood mm-hmm.

John Jantsch (17:57): But wasn't that a factor previously? I mean, certainly neighborhoods are considered

Kenneth Wenger (18:06): Yeah, absolutely. So like I said, we always had a problem with bias, right? In the data, right? But traditionally, you would hope, so two things would happen. First, you would hope that whoever comes up with a model, just because it's a complex problem, they have to have some satis statistical training. Yeah. Right? And a, an ethical statistician would have to consider how to deal with the bias in the data, right? So that's number one. Number two, the problem that we have right now is that, first of all, you don't need to have that set decision. You can just use the model without understanding what's happening, right? Right. And then what's worse is that with these models, we can't actually understand how the, or it's very difficult traditionally to understand how the model arrived or prediction. So if you get denied either a credit line or as, as I talk about in the book bail, for example, in, in a court case, uh, it's very difficult to, to argue, well, why me? Why, why was I denied this thing? And then if you go through the process of auditing it again with the traditional approach where you have a decision, you can always ask, so how did you model this? Uh, why was this person denied this particular case in a, in an audit? Mm-hmm.

John Jantsch (19:21): So I, I mean, so so what you're saying, one of the initial problems is that people are relying on the output, the data. I mean, even, you know, I use it in a very simple way. I run a marketing company and we use it a lot of times to give us copy ideas, give us head headline ideas, you know, for things. So I don't really feel like there's any real danger in there other than maybe sounding like everybody else

Kenneth Wenger (19:57): Yes. And, and there's very, so the answer is yes. Now, there's two reasons for that. And by the way, let me just go back to say that there are use cases where, of course you have to think about this as, as a spectrum, right? Like yeah, yeah. There are cases where the repercussions of getting something wrong is worse than other cases, right? So as you say, if you're trying to generate some copy and you know, if it's nonsensical, then you just go ahead and change it. And at the end of the day, you're probably gonna review it anyway. So, so that is a lower, probably a lower cost. The cost of a mistake there will be lower than in, in the case of, you know, using a model in a, in a judicial process, for example. Right? Right. Right. Now, with respect to the fact that these models sometimes get, make mistakes, the reason for that is that the way these models actually work is that they, and, and the part that can be deceiving is that they tend to work really well for areas in the data that that is, that they understand really well.

(20:56): So, so if you think of, of a dataset, right? So they're trained using a dataset for most of the data in that dataset, they're gonna be able to model it really well. And so that's why you get models that perform, let's say, 90% accurate on a particular data set. The problem is that for the 10% where they're not able to model really well, the mistakes there are remarkable and in a way that a human would not be able to make those mistakes. Yeah. So what happens in those cases that, first of all, when we're training these models that we get, we say, well, you know, we get 10% error rate in this particular dataset. The one issue is that when you take that into production, you don't know that the incidences rate of those errors are gonna be the same in the real world, right?

(21:40): You may end up, uh, being in a situation where you get those data points that lead to errors at a much higher rate than you did in your data set. Just one problem. The second problem is that if, if you are in a, if your use case, if your production, you know, application, it's such where a mistake could be costed, like let's say in a medical use case or in self-driving, when you have to go back and explain why you got something wrong, why the model got something wrong, and it is just so bizarrely different from what a human would get wrong. That's one of the fundamental reasons why we don't have these systems being deployed across safety critical domains today. And by the way, that's one of the fundamental reasons why we created splint, is to tackle specifically those problems, is to figure out how can we create a set of models or a system that's able to understand specifically when models are getting things right and when they're getting things wrong at runtime. Because I really think it's, it's one of the fundamental reasons why we haven't advanced as much as we should have at this point. It's cuz when models work really well, uh, when they're able to model the data, well then they work great. But for the cases where they can't model that section of the data, the mistakes are just unbelievable, right? It's things that humans would never make those kinds of

John Jantsch (23:00): Mistake. Yeah, yeah, yeah. And, and obviously, you know, that's certainly gonna, that has to be solved before anybody's gonna trust sending, you know, a man spacecraft, you know, guided by AI or something, right? I mean, when you know human life is at risk, you know, you've gotta have trust. And so if you can't trust that decision making, that's certainly gonna keep people from employing the, the technology, I suppose.

Kenneth Wenger (23:24): Right? Or using them, for example, to help in, as I was saying, in medical domains, for example, cancer diagnosis, right? If you want a model to be able to detect certain types of cancer, given let's say biopsy scans, you wanna be able to trust the model. Now anything, any model essentially, you know, it's going to make mistakes. Nothing is ever perfect, but you want two things to happen. First, you wanna be able to minimize the types of mistakes that the model can make, and you need to have some indication that the quality of the prediction of the model isn't great. You don't wanna have that. Yeah. And second, once a mistake happens, you have to be able to defend that the reason the mistake happened is because the, the quality of the data was such that, you know, even a human couldn't do better. Yeah. We can't have models make mistakes that a human doctor would look at and say, well, this is clearly Yeah, incorrect.

John Jantsch (24:15): Yeah. Yeah. Absolutely. Well, Ken, I wanna take, uh, I wanna thank you for taking a moment to stop by the Duct Tape Marketing Podcast. You wanna tell people where they can find, connect with you if you'd like, and then obviously where they can pick up a copy of Is the Algorithm Plotting against Us?

Kenneth Wenger (24:29): Absolutely. Thank you very much, first of all for having me. It was a great conversation. So yeah, you can reach me on LinkedIn and for the cop for a copy of the book and get it both from, uh, Amazon as well as from our publisher website, the, it's called the working fires.org.

John Jantsch (24:42): Awesome. Well, again, thanks for solving by great conversation. Hopefully, we'll maybe we'll run into you one of these days out there on the road.

Kenneth Wenger (24:49): Thank you.

John Jantsch (24:49): Hey, and one final thing before you go. You know how I talk about marketing strategy, strategy before tactics? Well, sometimes it can be hard to understand where you stand in that, what needs to be done with regard to creating a marketing strategy. So we created a free tool for you. It's called the Marketing Strategy Assessment. You can find it @marketingassessment.co, not.com, dot co. Check out our free marketing assessment and learn where you are with your strategy today. That's just marketing assessment.co. I'd love to chat with you about the results that you get.

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Embracing Your Entrepreneurial Superpower Being Unemployable

Embracing Your Entrepreneurial Superpower Being Unemployable written by John Jantsch read more at Duct Tape Marketing

Marketing Podcast with Alysia Silberg

In this episode of the Duct Tape Marketing Podcast, I interview Alysia Silberg. She is a leading venture capitalist in Silicon Valley, where she mentors tech startups and helps them go public. She is the CEO & General Partner of the investment firm Street Global.

Her online radio show: Global Fireside Chats, brings together global industry titans to share insights on our fast-changing world. Furthermore, Alysia is a UN Women Empower Women Global Champion and an international board director with sovereign wealth fund experience. 

Her first book, Unemployable: How I Hired Myself details her life story and guide to financial freedom. It’s a guide that helps to change your mindset from “I can’t” to “I can”. 

Key Takeaway:

Alysia changes the narrative of being “unemployable” and relates it to entrepreneurship and finding one’s superpower in business. Being unemployable is something to be proud of, as it often reflects the mindset and qualities of an entrepreneur, that can lead to innovation and generate changes. She emphasizes the importance of owning one’s uniqueness, taking risks, embracing curiosity, and seizing the opportunities presented by the digital revolution.

The current business environment, which Alysia describes as a “modern-day renaissance”, it’s a time for innovation and new opportunities. It’s important to leverage the power of AI and digital tools to start and grow a business and develop each person’s superpower.

Questions I ask Alysia Silberg:

• [01:52] Tell me a little bit about the artwork from the book cover.
• [03:07] Your book launch party was at a roller rink. How did that come about?
• [04:13] Why is the book called Unemployable?
• [07:20] Can you name a particular instance in your career where you felt like “This is going to work, this is like what I should be doing”?
• [08:58] You talk about superpowers and finding your superpower. Does your superpower have a name?
• [10:00] Back in South Africa you got shot, what did that story mean to your journey?
• [11:53] Is there anything about what’s going on right now in the current business environment that you think makes us a strong time?
• [15:25] What’s the first step you tell people to acquire the mindset you talk about?
• [18:23] What are your thoughts on the idea that there are proven business models and you don’t have to like to create a whole new thing from zero?
• [19:41] Based on where you see where we are today, what’s work going to look like in 10 years?

More About Alysia Silberg:

• Get your copy of Unemployable: How I Hired Myself
• Connect with Alysia and follow her on Instagram

More About The Agency Certification Intensive Training:

• Learn more about the Agency Certification Intensive Training here

Take The Marketing Assessment:

• Marketingassessment.co

Like this show? Click on over and give us a review on iTunes, please!

Duct Tape Transcript

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John Jantsch (00:00): Hey, did you know that HubSpot's annual inbound conference is coming up? That's right. It'll be in Boston from September 5th through the eighth. Every year inbound brings together leaders across business, sales, marketing, customer success, operations, and more. You'll be able to discover all the latest must know trends and tactics that you can actually put into place to scale your business in a sustainable way. You can learn from industry experts and be inspired by incredible spotlight talent. This year. The likes of Reese Witherspoon, Derek Jeter, Guy Raz are all going to make appearances. Visit inbound.com and get your ticket today. You won't be sorry. This programming is guaranteed to inspire and recharge. That's right. Go to inbound.com to get your ticket today.

(01:03): Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch. My guest today is Alysia Silberg. She's a leading venture capitalist in Silicone Valley where she mentors tech startups and helps them go public. She is the CEO and general partner of the investment firm, street Global. Her online radio show, global Fireside Chats brings together global industry tightens to share insights on our fast changing world. She is a UN Women Empower Women Global Champion, and an international board director with Sovereign Wealth Fund experience. We're gonna talk about her first book, Unemployable: how I Hired Myself. So Alysia, welcome to the show.

Alysia Silberg (01:47): Hi John. Very excited to be joining you. Thanks for having me.

John Jantsch (01:50): So listeners can't see this, although you'll see, you can see it in the show notes, the video of folks obviously will see it, but I, you have a picture of the artwork from the cover behind you there in the in frame and I just, I wanted to start there because I just absolutely love it. So tell me a little bit about, I mean I frankly it's a work of art.

Alysia Silberg (02:08): Thank you. Um, very excited to hear you say that. So you talk about being unemployable, you talk about the future of ai. I know these are themes we'll be chatting about today, but I had five designers trying to come up with what it meant to be unemployable and no one could convey that in imagery. And one of my founders who has an ed tech startup focusing on AI in Minneapolis, he said, let me sit down and let me take the book and let me put it in open AI's design platform and let's see what happens. And the, this is what the AI came up with. It's the essence of a founder's journey and it's interpreting it, you know, that drive and ambition, you know, like that all of its embodied it that in this situation happens to be my image. But I'm, I'm very excited that we created that connection with the AI and it turned out the way it did.

John Jantsch (02:55): Yeah, it's kind of a, a block, almost like a Japanese block print illustration. It's really fabulous. Okay, another totally unrelated

Alysia Silberg (03:11): Well, we're gonna be, you know, the book is about finding your superpower and you know, superpowers are often unexpected and we discovered them in the weirdest of ways. And for me, they happened to be, I went to a pair of pink roller skates at five years old. I went to them more than anything on earth and I couldn't afford them. No one in my family could afford them. And I had to figure out how I could get these pink roller skates and I built a business and you'll read all about it in the book. Crazy wild Only founders understand what it means to, to want something so badly. And I never wore those roller estates ever. I treasured them cuz they reminded me of what's possible. The dreamer, you know, anything is possible. And so the idea of having a a roller skating party for the book was the only thing I could do to honor each of our journeys. For me it's roller skates. For you it was probably something else, but once a founder, always a founder and it was just, it's the way it's meant to be

John Jantsch (04:05): Kind of sounds like a load of fun too. So there's that

Alysia Silberg (04:26): Absolutely. So I was trained as an actuary and I went for a career aptitude test at a bank. And I was like, you know, on my way thinking I joined, you know, a big bank and I was told I, I was unemployable in that attitude test and I was devastated. I was like, what do I do now? And I took it as an insult and at the time it was, you know, it wasn't a compliment and it took me decades to own that. And what I do today now is I'm a researcher and I'm an investor. Like those are the things that make me the entrepreneur that I am. Right. And it was very tough choosing the title. I did a ton of research because everyone kept saying, but you're not unemployable. How can you say you're unemployable? And I'm like, well actually I am.

(05:07): And it's okay. It's something to be proud of. The most important creators in history were basically unemployable to create innovation and change in these things. You've gotta be able to just live in a different way to many people and take risks. But there's a lot of bravery around their title And I, I hope and honors the founder's journey. So for everyone out there that feels the unemployable, as I say, I've learned to own it and be the queen of unemployable

John Jantsch (05:39):

Alysia Silberg (06:12): Absolutely. I think I suffered from huge imposter syndrome and the ironic part was it was that bank who didn't want me and because of my imposter syndrome I decided no one wanted me. So when job offer offers came, I was like whoa, I don't feel I belong here because there's something wrong with me. Versus I'm a born and bred founder and this is what I do. Like you, you've been running a company for a very long time and I think definitely, I think many people and I think that's what I hope to get out of the book where each person has something unique and instead of hiding from it and saying I have to con conform to what everybody expects me to do, rather say, okay, AI is bringing all this change. People are gonna lose their jobs, things are gonna be very different. Let me own my superpower, let me bold a business. And even if I do feel a bit like an imposter even now, I still feel like an imposter. I still have to work on it a lot. It's okay. You will find customers that will support you just the way you are and you can bold something really cool as you have done

John Jantsch (07:12): So. So you have started, have you lost track of how many companies over the years? Number doesn't matter

Alysia Silberg (07:18): Too many,

John Jantsch (07:18): Many. But uh, I'm wondering if you could in hindsight, as we always do,

Alysia Silberg (07:43): For sure. I think it was the company that we built that brought us to the US in the first place where I just, it was connecting the dots and we were solving a problem for our customer. So it was a very early voice analytics pro uh, platform, which is helping salespeople sell better. Long before sales enablement became like this very ubiquitous thing. And it was just, there was so much intensity coming at us from the market where they wanted something better that wasn't available. That even though everyone in South Africa said to us, you're mad, what are you doing going to America for a sales app? The idea that there was a probability of greater than let's say 10%, that we would bold something extremely valuable. That was enough of, I don't know, just a spark of you know, like I'm gonna do this no matter what and even whatever happens, I'm doing this and I'm gonna make it work. But absolutely that one was just clear and I think I used that to look at startups today where when I can see something that's gonna happen, you wanna be on that journey cuz it's so exciting.

John Jantsch (08:44): Yeah. And then it, and I mean this in a positive way then it becomes like a drug, right? You recognize it the next sentence like I want that high again. Right,

Alysia Silberg (08:51): Absolutely. Absolutely. It's addictive.

John Jantsch (08:57): So, so you talk a lot in this book about superpowers and finding your superpower. I'm curious, does your superpower have a name?

Alysia Silberg (09:05): I'm obsessed with pattern recognition and I think growing up people saw me as a freak. Like it was very tough growing up cuz I was so different to everyone around me, like in South Africa and absolutely I'm not and I think that's why I work so well with the AI because it's so much better than pattern rec, pattern recognition than me. And faster is absolutely

John Jantsch (09:38): It's interesting, I've for years, you know, have told people that my superpower is curiosity and I think that's probably very related to you know, pattern recognition. A lot of times, you know, I will read a book about architecture and you know, get my best ideas even though I have nothing to do with architecture

Alysia Silberg (10:18): Absolutely and I think it was a pivotal moment in the sense that I saw an environment that just made no sense to me. And I was very young and I saw the people around me where they chose to live in an environment that they believed made sense to them because they were fearful of going and as you say, being curious enough to try something that was better, even though it was very scary for me, I had no choice from that moment onwards. I knew I was gonna come to America and it never mattered what went wrong, what obstacle, what was thrown in my way. Like as you read the book, you'll see the number of times where I had visa troubles and it was like I never gave up on the American dream where you say curiosity, the idea that you can live in a place where the sky is the limit for founders and you can bolt till your heart's content and there's so much support available and you'll always find an investor, you'll always find customers, you'll always find team members. I didn't grow up in that environment and so that moment that happened, even though it was the most terrifying thing to ever happen in my life, I still have the scar to this day and I could have had it removed, but I chose to have it because it's a reminder of where I came from and to feel a sense of gratitude of where I am and that just never take for granted the luckiness to actually be here.

John Jantsch (11:44): Is there anything about this moment in time that makes it like, now is when you should jump now is when you should do your, you know, whatever you've been thinking about doing there? Anything about what's going on right now, you know, in in the current business environment that you think makes us a strong time?

Alysia Silberg (11:59): Absolutely. I think, you know, I'm a student of the Renaissance. I've studied it in depth and we are living at the most exciting time in history. You know, many people are very frightened, you know, economically, politically, there's a lot happening. But this is a time of great excitement and I think there are many people who fear the AI revolution and yes, there will be a lot of change in terms of jobs and in terms of all these things that will change, but ultimately they will change for the better. But I think going back to superpowers, why I felt it was so important to get the book into as many people's hands as possible is I know what it's like to have no money. I know what it's like to be frightened. I know what it's like to have to be poor and like all those things I've experienced those things and you don't wanna be sitting in your job thinking, what's gonna happen to me?

(12:46): What's gonna happen to my kids? Versus thinking, okay, this may happen to me, but instead of sitting waiting for it, I'm gonna take my life into my own hands. I have something of value that I can offer the world. How do I leverage the power of, let's say the internet? There are 3 billion people online. So com, the combination of your superpower and the power of the internet, you can easily start a business on the side and you can grow it. It's, and the fact that you don't need to know how to code anymore, the fact that you don't need to know how to do all these things because the AI is so easy, it's anyone can use it now it's a matter of, you said it, curiosity coming from a place of like, okay, I'm gonna learn this. This isn't difficult. Like it's there and it's there for the taking. And I think the longer people wait purely because it's new and a little bit scary for many people, the more you get left behind versus saying, okay, we are living through a modern day renaissance and it's coming out of the us let me participate, let me do it. And in yours, time at the speed things are going, you'll never, ever look back that much I can assure you of.

John Jantsch (13:50): And now let's hear a word from our sponsor, marketing Made Simple. It's a podcast hosted by Dr. JJ Peterson and is brought to you by the HubSpot Podcast Network. The audio destination for business professionals marketing made simple brings you practical tips to make your marketing easy and more importantly make it work. And in a recent episode, JJ and April chat with StoryBrand certified guides and agency owners about how to use ChatGPT for marketing purposes. We all know how important that is today. Listen to marketing Made Simple. Wherever you get your podcasts.

(14:27): Hey marketing agency owners, you know, I can teach you the keys to doubling your business in just 90 days or your money back. Sound interesting. All you have to do is license our three-step process that's gonna allow you to make your competitors irrelevant, charge a premium for your services and scale perhaps without adding overhead. And here's the best part. You can license this entire system for your agency by simply participating in an upcoming agency certification intensive look, why create the wheel? Use a set of tools that took us over 20 years to create. And you can have 'em today, check it out at dtm.world/certification. That's dtm.world/certification.

(15:11): I guarantee you, when this book comes out and you're out speaking to uh, groups or speaking to individuals, somebody's gonna come up to you and say, okay, your talk was brilliant, I'm so inspired. But like, what's the first step?

Alysia Silberg (15:27): Absolutely. I've tried to take what I've learned over the last decade with AI and simplify it in a way that empowers anyone, right? I'm obsessed with being a teacher and I hope, you know, I believe in radical open-mindedness. I hope that what I've done is going to help many people. So I have a daily AI use data that's free and it's got different sections to it. One of the sections I love the most is tools. And there's all these different tools there and when people start reading it, they'll be like, she's insane. She expects me to understand this stuff and bear with me. As I say, I've taught statistics, finance, financial, maths, go and look at the tools every day, just read about the tools and in the beginning it'll be like it's a bit new and it's a bit scary and there's videos included, there's all kinds of things.

(16:10): And give yourself, let's say seven days, then 10 days just reading it. And by the end of that you'll start noticing, Hey, this is not that difficult. Okay, I wanted to build a website instead of going the usual route of all the difficulties of building a website, it's actually an AI tool that I can use for free or next for free. And I can get an AI tool to build that website for me. And as you watch it build itself and you're like giving it the parts that it needs to build it, you'll see it's actually incredibly fun. It's, you have no idea how much fun AI's like, it's like a form of magic like I use for text messages for, you know, you're tired, you're worn down, you've had a busy day, you're trying to convey something, but you just, you're like, my brain is saturated and the fact that this machine can take what you're trying to say and just make those micro adjustments so that you're conveying the right thing, but your tone where you don't wanna come across as worn down and tired and all these things you wanna be, I'm happy and I'm happy to be talking to and it can do that for you.

(17:07): It's these tiny things where you don't have to start at the most advanced stuff. You can start at the basics and just bold up and find other people that are interested. That's being huge for me. Where if you, you bold a peer group of people who are like, I'm really interested in it, why don't we talk about it? Why don't we, like one of my friends is doing like music and AI and he's spending all his time composing music and he's like, well can you send me your music? I'm like, if I'm embarrassed, he's like, I'm embarrassed to my music too. But I'm like, okay, let's share music and see where this goes. And we've got this whole AI music group that we're creating. So I think it's like, again, taking something you are really interested in and saying, can I have more fun with this? Can I do more with this? And then finding other people who can play with you. It's a lot about playing.

John Jantsch (17:49): Yeah. You know, I started my business before we had the internet, you know, as a marketer I tell that to groups sometimes and they're like, what? I don't, I don't get how right

Alysia Silberg (18:35): Absolutely. Like what you're doing, it would be a brilliant use case and I'd love to talk to you sometime offline where it's so much fun to take what you've created and say, okay, where are the biggest problems you as the creator with mastery have over your business? Where are those things that you really, you don't wanna be spending your time on those things, you wanna be spending your time on these other things? And how do we use the AI to give you that time back so that you can spend your time on the thing you love most within your business. And it's so easy. That's the part that blows the person's mind. Where mm-hmm

John Jantsch (19:32): Awesome. Let's do it. Uh, I want you to go beyond where we are today and you know, take the crystal ball for what it's worth,

Alysia Silberg (19:46): I'm a contrarian and so

(19:51): I think this, I think people are going to have, we're gonna have all these tools, they're gonna be working for us and I think everyone will have a lot more freedom. I think the machines will be doing all the stuff no one wants to do, which I think is really cool. I think we'll also go into a very creative period in history again like the renaissance where things that people just didn't have time to do, they will have time to do. A lot of people around me spend a lot of time thinking about universal basic income. These kinds of things are important to also think about in terms of, in terms of the future, you know, I've had an interesting experience on my own team where we started bringing in like digital workers in the team. So like adv, AI avatars. And it's been very interesting because you think about the team and the team is creating these avatars and my team was like, okay, what kind of demographic do we want?

(20:41): What age do we want the avatar to be? All these things that I'm interested to see, like they were literally designing these avatars where lands us up at the same time. I'm fascinated by what young people have to say about this. So I engage a sub even for the book especially, I engage a ton with people like in this 17, 18, 19, 20 year olds and they want a lot of in real life engagement. They want what we always had, as you said, you built your business before the internet, you knew what it was like to do everything in person and they crave that engagement. Mm-hmm

(21:38): And I have a feeling a lot of that will come back where, why do you have to spend all your time in front of a machine if you know I can hang out with you in person cuz I'm not stuck to my machine doing all my work. So I don't know how it will play out, but I think ultimately things will be better. But that comes down to regulation too, in terms of just, you know, managing the AI really, really well cuz it is so powerful and it learns so well no matter how curious we are.

John Jantsch (22:05): You know, it's interesting when you talk about, you know, being a student of the Renaissance, you know, prior to factories being created, you know, people didn't work like they do today. They didn't work nine to five or whatever it was, they spent, you know, great chunks of time just hanging out in salons and doing things. So I, you know, in some ways, you know, I think what you're, what is possible if we change the mindset of the factory, so to speak, you know, I think there is a possibility that this actually aids a return to a more, more human

Alysia Silberg (22:40): I I fully agree with you. I can like, I can sense how desperate people are like, you know, I, I spend a lot of time thinking about like mental health and those things and people crave that kind of world and there's no reason why we can't partner with the machines to give us that kind of life for everyone. Where people do have more time to, like, I'm really enjoying this conversation. If neither of us were working, we could be hanging out, having this conversation in our own salon with people like us and the creativity and the things that can come out of it. We've seen the last 500 years with defined by that time in history. We can define the next 500 euros by this time.

John Jantsch (23:20): Yeah. Alysia, we could talk a long time about this stuff, but we are out of time for today's episode. You wanna, I'd, I'd love for you to invite people to connect with you or find out however they, you would like to invite them and obviously pick up a copy of Unemployable.

Alysia Silberg (23:36): Absolutely. Uh, please, I've discounted unemployable to 99 cents on Amazon because I wanted to get into as many founders' hands as possible. So please go and buy the book and review it. And if you think it sucks, I'm radically open-minded. You can tell me it sucks and I'd love to know why. Cause you know, there's always a kernel of truth and all criticism and I'm a founder who loves to learn from their customers. So please buy the book. Let me know what you think. Connect with me on social media. I love hearing from other founders and creators and in the newsletters free, I'd love to share the newsletter so your founders and everyone in your community can subscribe. And again, if they've got questions, just email me back. I've got a team of people dedicated to it. So if they start, they feel is missing, they wanna learn more about, I'm very passionate about really changing the world when it comes to, you know, the changes taking place. And so I love hearing from people just like us.

John Jantsch (24:25): Awesome. Well again, thank you so much for taking a few minutes to stop by the podcast and hopefully we'll run into you one of these days out there on the road in real life.

Alysia Silberg (24:33): I would love it. Thank you very much for hosting me. I loved every minute of it.

John Jantsch (24:38): Hey, and one final thing before you go. You know how I talk about marketing strategy, strategy before tactics? Well, sometimes it can be hard to understand where you stand in that, what needs to be done with regard to creating a marketing strategy. So we created a free tool for you. It's called the Marketing Strategy Assessment. You can find it @marketingassessment.co, not.com.co. Check out our free marketing assessment and learn where you are with your strategy today. That's just marketing assessment.co. I'd love to chat with you about the results that you get.

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