What Will Our AI and Web Content Look Like to Future Generations?

What Will Our AI and Web Content Look Like to Future Generations?

Digital Marketer – Podcaster – Jason Barnard | Ep. 360 Send It Rising Internet Marketing

Kellen Kautzman suggests that because we are the first generation in human history to create such a volume of recorded content, we will be the first generation to be listened to at length by future generations. The content we create on TikTok, YouTube, Facebook and others will presumably survive and be available to study. Interesting. Add to that how they might perceive our current levels of AI and Machine Learning, and the conversation gets really interesting!

00:00 Future generations will witness today’s contents
00:25 Contents produced in social media platforms
00:41 The early days of AI
01:15 Knowledge Graph as encyclopedia for machines

Transcript from: What Will Our AI and Web Content Look Like to Future Generations?

I’ve said many times on the show that we are in the generation that sort of like the Adam and Eve generation where our future generations, thousands, tens of thousands of years later, we are the first generation of human history where they’re going to be able to listen to us at length. Because there’s going to be so much content that we produce. TikTok, YouTube, Facebook. Like my parents’ generation, anyone who’s alive today. That’s the point I’m making, content creators today, which is just so wild to me. And they’re going to listen to these conversations we had about the early days of AI. And it will be known as some word we haven’t even invented yet, like pre consciousness, pre enlightenment, like before the machines were enlightened. This is what they were talking about. Do you feel like we’re living in the Jurassic era in some ways?

Yeah, that’s really interesting perspective. I’m actually going to be giving a talk in New York and I’ve been invited to a Knowledge Graph conference where they talk about… A Knowledge Graph is basically building understanding that a machine can use. A guy called Dixon Jones talks about it as an encyclopedia for machines. But it’s actually quasi-human understanding by a machine.

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