GenAI capabilities are in a state of constant acceleration, but without true memory, it also is starting from scratch with each use. In this episode of Pure Signal, you’ll hear why context is the next critical unlock in AI and what it means for both businesses trying to stay ahead and consumers craving personalization. 

Opening up with a breakdown of how current models are operating, Vincent, Kevin, and Jason weigh how these platforms will need to evolve in order to be fully customized at the user level in a safe and scalable way. They argue that while the most obvious benefit exists on the consumer side with increased user loyalty, executives and businesses would also be able to leverage this unlock to streamline many of their operations.

Is it technically feasible to carry context from app to app? Will vendors allow it, or fight to own it? And what are the strategic risks of letting someone else control your AI memory layer?

Whether you’re designing new products, leading AI integration, or shaping data architecture, this episode offers a timely look at what it takes to build differentiated experiences in a world of commoditized intelligence.

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Quotes

"What’s fascinating is that we’re revisiting the same challenges we’ve seen throughout 200 years of computing. General vs. Special Purpose. Memory vs. No Memory. It’s always been the same problem. AI today looks like early mainframes or punch cards in some ways. We’re going to need another evolution to figure out how memory and personalization really work.” – Kevin Erickson

"The way we've designed systems for the last 20 years is to be stateless. The AI models are no different. You either put memory into the model, which is basically not scalable—or you provide it as input every time. That’s why durable, long-term memory is such a hard architecture problem to solve." – Jason Goth

"We're going to move from a world where your data travels with you. That's the game-changer. I shouldn't have to reintroduce myself to every system I use. The intelligence isn't just in the model, it's in what it remembers about me and how seamlessly it can apply that context." – Vincent Yates

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Time Stamps

00:00 Intro

01:00 The value of being remembered

05:35 Will AI models be sought out for stored context?

14:05 Can each platform be fully customized per user?

19:30 Solving future problems with current technology

25:25 Increasing loyalty with added context

30:10 Where will customers see the impact

36:35 Are potential risks worth worrying over?

43:20 It all comes back to differentiation

47:40 Wrapping up

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Links 

Connect with the hosts on LinkedIn!

• Vincent Yates

• Jason Goth

• Kevin Erickson

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