AI, SEO, and the Future of Search
episode
Voices of Search // A Search Engine Optimization (SEO) & Content Marketing Podcast
57 min
2 speakers
8 chapters
transcribed 1 month ago
Transcript
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Transcript generated automatically by AI and may contain errors.
What is the post‑transformer landscape and how does it affect SEO strategy?
The Voices of Search Podcast is a proud member of the I Hear Everything Podcast Network. Looking to launch or scale your podcast? I Hear Everything delivers podcast production, growth, and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit IHear Everything.com. Welcome to the Voices of Search Podcast in IHear Everything presentation. introduction. In this podcast, we'll share the news, knowledge, and strategies you need to navigate the ever-changing world of SEO. Ready to expedite your company's organic growth efforts? Sit back, relax, and get ready for your daily dose of search engine optimization wisdom. Here's today's host of the Voices of Search podcast, Tyson Stockton.
My name's Tyson, and joining me today is Kristen Tinski, SVP of Creative and co-founder at Fractal. Welcome back to the podcast, Kristen.
Thanks for having me.
It's uh been a little while, but second time I've had you on the podcast. Um I believe if I remember correctly, the first time was probably back in I guess like 22 or 23. Um you were coming out with quite a bit of work as far as like some early kind of AI-led workflows. But I want to pick your brain a little bit more on kind of like how you see our industry. industry developing and before we started recording We're talking a little bit about like a post-transformer world. So what what does that mean to you and how would you describe what that looks like?
Yeah. So well, I guess I'll preface it by saying nobody knows exactly the truth here because these architectures are not completed and some of them may require breakthroughs that we haven't achieved yet. So the timelines are not entirely certain, but it's seeming like in the next maybe three to five years we'll have some of these breakthroughs that will allow for remediating some of the issues that transformers have and that will be what changes the search and marketing game, I think. So I guess you can start by by talking about transformers themselves and the issues that they have. So a transformer is basically like a giant matrix. You can think of it like a spreadsheet. It's um the weights are in each individual cell.
And every time that the training is done or each pass of training is done, every single weight is updated. So it's an incredibly um computationally dense. thing and for that reason it's also very uh it's a it's a huge energy suck, right? So like Talking about building massive data centers that are requiring even their own power plants. Um, the future of transformers in terms of scaling them is sort of hitting an upper limit. Um we know that they they scale in a quadratic way. So the more parameters you have and the more training you do, the more compute you need, um in in a in a really exponential way. So we're we're sort of hitting the upper limit and and I think that's that's really uh what's going to require us to to find this new paradigm.
And how how do you like And I agree with you. It's like we don't know exactly when, but I think it's like It's less of a question of whether or not this is the direction that we're heading in and more of like that win. So like if we remove kind of if it's next twelve months, thirty-six months, whatever. How would you describe kind of like How we would compete in that, like what implications does that have in how we're strategizing our efforts within search?
Yeah, so it When we get these new architectures, the primary thing that's going to be solved is continual learning. So right now, transformers need to be trained and then they can run inference and and you get an answer, but they're not learning as you're working with them. They were trained once and then they're doing inference. The next generation of models will be continual learners. So Uh they'll learn with you and they'll learn continually as you go. You won't have to retrain them continually at you know, like half a billion dollars or whatever it currently costs to train a frontier model. So when that happens, you'll also start to get hyper-personalized agents.
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Chapters
8 chapters
1
What is the post‑transformer landscape and how does it affect SEO strategy?
0:00–8:01
2
How will continual‑learning AI agents create hyper‑personalized search experiences?
8:01–16:11
3
Why will result variance increase and how should marketers measure success?
16:11–24:14
4
What new AI‑driven content‑creation workflow does Fractl use for data journalism?
24:14–33:02
5
Which development tools (Cursor, Claude, Opus, etc.) are most effective for building AI agents?
33:02–40:30
6
How will hyper‑personalized content reshape brand authority and the long‑tail?
40:30–49:02
7
What are the biggest misconceptions marketers have about AI‑generated search results?
49:02–56:38
8
What single piece of advice should marketers take away for future content strategy?
56:38–57:04