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In Machines we Trust

AI App Crisis, OpenAI Does Math, Big Nvidia Deal

In Machines we Trust

In Machines we Trust

Technology

4.36 Ratings

🗓️ 11 March 2026

⏱️ 18 minutes

🧾️ Download transcript

Summary

In this episode, we explore the challenges AI-powered apps face with long-term user retention, analyze ChatGPT's new interactive visual explanations for math and science, and discuss Thinking Machine Labs' massive computing deal with Nvidia.


Chapters
00:00 Introduction & Birthday Shoutout
01:36 AI App Retention Struggles
12:04 ChatGPT's Interactive Visuals
14:21 Thinking Machine Labs x Nvidia Deal
16:49 Industry Trends and Future


Links
See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Transcript

Click on a timestamp to play from that location

0:00.0

Welcome to the podcast. I'm your host, Jaden Schaefer. Guys, today is my 30th birthday, but I had to record a podcast because there's some crazy stuff happening.

0:08.4

Number one, there's a bunch of research and data coming that is showing AI powered apps are really struggling with long-term retention.

0:16.5

Also, chat GPT can now create interactive visuals that are going to help you understand math and science, which Google was kind of doing something similar.

0:23.0

It's going to be really cool to see chat GPT do this.

0:25.6

And third, thinking machine labs has just created a massive compute deal within video, which is pretty exciting for a company that has such a legendary background and has raised so much money.

0:37.1

So we're going to get all of these stories today. But before we do, I have to say a huge shout out in the last couple of days. I've asked people for my birthday. If you could leave a rating and review if you haven't already. I want to read the most recent review that someone dropped. This is from eating crab yesterday. He said, just wanted to say thank you for the

0:54.8

podcast. I don't have very much time in my day being a full-time student and working full-time, but I have a huge passion for AI, being able to keep up with your podcast, helps me keep in the loop. I appreciate it. Keep it up and happy birthday. A huge shout out to eating crab. Thank you so much for the review. Guys, today is my birthday. I'm turning 30 before I go through a midlife crisis.

1:12.3

If you guys could do me a massive favor, much for the review. Guys, today is my birthday. I'm turning 30 before I go through a midlife crisis.

1:12.3

If you guys could do me a massive favor for today, and please leave a rating review if you

1:17.8

haven't already. It would be the greatest birthday present of all time. I will be eternally grateful

1:22.6

over on Apple or Spotify or wherever you get your podcast. I know it's usually annoying, but today's my

1:27.4

birthday. So if you've ever appreciated that podcast in the past or today, it would be greatly

1:32.1

appreciated to drop a review. All right, let's get into the episode today. So the thing that I think

1:36.0

is really interesting is kind of this idea right now that all of the AI powered apps are really

1:42.0

struggling to keep long-term, you know, people engage long-term retention

1:47.1

on the apps. And I think there's a couple problems with this as someone that has built AI

1:51.0

powered apps in the past and as someone that is, you know, actively working in an AI startup,

1:56.5

AI box and a company. I can understand where a lot of this challenge is, and that is, I think,

2:00.6

with AI coming out and the power, you know power of AI being so incredible, I think we definitely had a really big wave, especially at, in the last couple of years, where there was a lot of concepts of, you know, what AI could do and would be able to do. And a lot of people, I think, overhyped or oversold their

2:17.6

apps. And I think that's going to be the primary driver of low retention. In addition, I do think that, like, right now, I try probably 10 times as much software as I have over the last, you know, five, 10 years working in the industry. And so I think right now we just try so much more and then we kind of settle on what works best. I think if you're a developer and you're creating a tool with

2:37.0

AI in it, you have one shot really for someone to go try your tool and for it to wow them and for them to be impressed and be like, okay, I will keep this as part of my long term tool belt of the tools I use. If they try it and it flops, there's a bunch of tools from big companies that I've tried in the past. They flopped and I haven't gone back. I think one of those examples would be something like runway for video. This is a platform that I tried a lot in the early days. It wasn't that great. And I mean, you have to give them a huge kudos for being first, but I never really got back to that platform and then Suno came out in a lot of these other video generations. You have Higgs field, which has a whole bunch of models on there. And I tend to just use more of those types of tools today than going back to some of the OG video tools. I think this is kind of a trend you'll see with a lot of, I know it's kind of like a random story from my experience, but I think you're going to see that a lot. So there was a recent report that came out of Revenue Cat and they showed that the

3:28.0

subscription. lot of, I know it's kind of like a random story from my experience, but I think you're going to see that a lot. So there was a recent report that came out of Revenue Cat, and they showed that

...

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