Trusting AI: Analyzing Major Funding Deals
In Machines we Trust
In Machines we Trust
4.3 • 6 Ratings
🗓️ 4 May 2026
⏱️ 20 minutes
🧾️ Download transcript
Summary
Chapters
00:00 Introduction to AI Deals
01:59 Greg Brockman's AI Insights
04:19 Launch of Humane's AI System
07:20 Morgan Stanley's Spending Forecast
12:41 OpenAI and Anthropic's Strategies
16:38 Conclusion and Future Predictions
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Transcript
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| 0:00.0 | Open AI and Anthropic, the two biggest AI companies in the entire world. |
| 0:04.4 | They both signed a multi-billion dollar private equity deals, and they did it on the exact same day. |
| 0:08.9 | The structure of how those deals happened is different, though. |
| 0:12.0 | So I think that's going to be really interesting when it comes to what's going on with AI and enterprise. |
| 0:16.6 | Also, Greg Brockman says that AI went from writing 20% to 80% of all OpenAI's code in one month. |
| 0:24.1 | Saudi Arabia's Humane just launched on AWS, and it is calling it the first enterprise-grade agentic AI operating system. |
| 0:31.5 | And Morgan Stanley just bumped the 26 hyperscaler forecast to $805 billion. |
| 0:39.3 | The first thing I want to break down, though, is Greg Brockman's. |
| 0:42.3 | He went on a podcast recently and he had all these wild quotes, including talking about AI. |
| 0:47.3 | He said, quote, even over the course of December, we went from these agentic coding tools, writing 20% of your code to writing 80% of your code. |
| 0:55.5 | This is a 4x jump in one single month. |
| 0:58.5 | And he also said that OpenAI is 70 to 80% of the way to AGI. |
| 1:04.2 | He also agrees with Sam and Demise over at Google DeepMind and says that we're maybe two |
| 1:09.8 | breakthroughs away. |
| 1:11.0 | Now, of course, this wasn't everybody that agreed with him over on ex-Yan Lekun, |
| 1:15.6 | predictably has been dunking on the AGI claim. |
| 1:18.7 | He's been basically doing this all week. |
| 1:20.2 | You also have Andre Carpathie, who was a lot more, I guess you could say like measured, |
| 1:24.2 | but basically the thing that I've heard him talk a lot about is he says |
| 1:27.8 | that I'm sure some of these coding writing percentages are like huge, right, going from 20 to 80 |
| 1:33.7 | percent. But what he said is if you measure tokens emitted versus what is so, and that's kind of |
| 1:41.3 | where you're getting this 20 to 80 percent jump, but he says the difference is and a harder question is what fraction of all of these tokens, all of this and that's kind of where you're getting this 20 to 80% jump but he says the difference is |
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