Conversation with Elon Musk and Satya Nadella at Microsoft Build 2025. - Elon Musk Thinking

Summary5 min read

Podcast Summary: Elon Musk Thinking – Conversation with Elon Musk and Satya Nadella at Microsoft Build 2025

Hosted by Astronaut Man | Release Date: May 20, 2025

In this engaging episode of Elon Musk Thinking, host Astronaut Man sits down with Elon Musk and Satya Nadella at Microsoft Build 2025. The conversation delves into Musk’s early programming days, the development and vision behind the AI model Grok, AI safety, and the integration of advanced AI across Musk’s diverse enterprises, including Tesla and SpaceX. This summary captures the essence of their discussion, highlighting key points, notable quotes, and the overarching insights shared during the episode.

1. Elon Musk’s Early Programming Days

The podcast opens with Astronaut Man reminiscing about Musk’s beginnings in the tech world, highlighting his roots as a Windows developer and a PC gamer. Musk shares his formative experiences in software development:

Elon Musk [00:17]: “I actually started before Windows with DOS. I had one of the early IBM PCs with MS-DOS and I think I had like 128k in the beginning and then it doubled to 256k, which felt like a lot. So I programmed video games in DOS and then later in Windows. Remember Windows 3.1?”

This segment underscores Musk’s deep-seated passion for programming and his hands-on experience with early computer systems, setting the stage for his future endeavors in technology and innovation.

2. Introducing Grok and First Principles in AI

Astronaut Man transitions the conversation to Musk’s work on Grok, an advanced AI model poised for release:

Elon Musk [01:20]: “With Grok, especially with Grok 3.5 that is about to be released, it's trying to reason from first principles, so apply kind of the tools of physics to thinking.”

Musk elaborates on Grok 3.5’s foundational approach, emphasizing the importance of basing AI reasoning on fundamental physics principles:

Elon Musk [01:35]: “If you violate conservation of energy or momentum, you're either going to get a Nobel Prize or you're wrong. And you're certainly wrong.”

This approach aims to ensure that AI reasoning aligns with verifiable truths, reducing errors and enhancing the model’s reliability.

3. AI Safety and Community Feedback

A significant portion of the discussion revolves around AI safety and the ethical considerations essential for responsible AI development:

Elon Musk [02:45]: “The old maxim that honesty is the best policy. It really is for safety. But we do make mistakes, but we aspire to correct them very quickly.”

Musk highlights the importance of transparency and rapid error correction in AI systems to ensure safety and reliability. He also stresses the value of developer feedback in refining Grok:

Elon Musk [02:50]: “We are very much looking forward to feedback from the developers, developing a community to say like, what do you need? Where are we wrong? How can we make it better?”

This collaborative approach underscores Musk’s commitment to building AI systems that are both effective and ethically sound.

4. Grounding AI in Physical Reality

The conversation delves into the necessity of grounding AI models in physical reality to ensure intelligent and accurate predictions:

Elon Musk [04:10]: “For any given AI, grounding it against reality—physics is the law... To really be intelligent, it's got to make predictions that are in line with reality.”

He emphasizes that adherence to physical laws is fundamental for AI applications in autonomous vehicles and robotics:

Elon Musk [04:20]: “With the car needs to drive safely and correctly. The humanoid robot Optimus needs to perform the task that it's being asked to perform.”

This grounding ensures that AI systems function reliably in real-world scenarios, enhancing their practical utility and safety.

5. AI Applications Across Tesla, SpaceX, and Beyond

Musk discusses the deployment of Grok across his companies, enhancing operations and customer service:

Elon Musk [05:00]: “Grok is already doing quite a good job at SpaceX and Tesla, and we look forward to offering that to other companies.”

He highlights how AI improves customer interactions by maintaining patience and friendliness, even under stress:

Elon Musk [05:35]: “The AI is infinitely patient and friendly, and you can yell at it and it's still going to be very nice.”

This application not only improves user experience but also streamlines issue resolution processes, making customer service more efficient and pleasant.

6. Orchestrating Multiple AI Models and Future Integration

The discussion touches on the orchestration of multiple AI models to create sophisticated applications:

Elon Musk [04:10]: “It's not even about any one model. It's about orchestrating multiple models, multiple agents...”

He envisions the convergence of language models with vision and action capabilities, aiming for more holistic and capable AI systems:

Elon Musk [06:01]: “Over time we will have this coming together of language models with vision, with action, but to your point, being really grounded on a real world model.”

This integration aims to enhance AI’s ability to interact seamlessly with its environment, making it more versatile and effective across various applications.

7. Conclusion and Call for Developer Engagement

As the conversation wraps up, Musk reiterates the importance of developer input in refining AI models:

Elon Musk [06:31]: “We're looking for feedback from you, the developer audience. Tell us what you want and we'll make it happen.”

Host Astronaut Man expresses excitement about deploying Grok to the developer community, fostering innovation and collaboration. This call to action emphasizes the collaborative spirit necessary for advancing AI technology responsibly and effectively.

Notable Quotes

On First Principles in AI:

“With Grok, especially with Grok 3.5 that is about to be released, it's trying to reason from first principles, so apply kind of the tools of physics to thinking.”
— Elon Musk [01:20]
On AI Safety:

“The old maxim that honesty is the best policy. It really is for safety... but we aspire to correct [mistakes] very quickly.”
— Elon Musk [02:45]
On Grounding AI:

“For any given AI, grounding it against reality—physics is the law... To really be intelligent, it's got to make predictions that are in line with reality.”
— Elon Musk [04:10]
On Developer Feedback:

“Tell us what you want and we'll make it happen.”
— Elon Musk [06:31]

Final Thoughts

This episode of Elon Musk Thinking offers a comprehensive look into Elon Musk’s approach to AI development, highlighting his emphasis on first principles, safety, and practical applications across his companies. Musk’s commitment to transparency and collaboration with the developer community underscores a forward-thinking vision for AI that prioritizes both innovation and ethical responsibility. Listeners gain valuable insights into how advanced AI models like Grok are being designed to integrate seamlessly with real-world applications, ensuring both utility and safety.

Whether you’re a developer, tech enthusiast, or someone interested in the future of AI, this episode provides a rich and engaging exploration of the principles and practices shaping one of the most influential figures in technology today.

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Transcript12 lines

[00:01]
A
Thank you so much, Elon, for being here at Build. I know you started off as an intern at Microsoft. You were a Windows developer and of course you're a big PC gamer. Still, you want to just talk about even your early days with Windows and the kinds of things you built.
[00:17]
B
Yeah, well, actually started before windows with DOS. I had one of the early IBM PCs with Ms. DOS and I think I had like 128k in the beginning and then it doubled to 256k, which felt like a lot. So I, yeah, programmed video games in DOS and then later in Windows. Remember Windows 3.1?
[00:44]
A
Yeah, no, it's wonderful. I mean, even the last time I chatted with you, you were talking all about everything, the intricacies of Active Directory. And so it's fantastic to have you at our developer conference. Obviously the exciting thing for us is to be able to launch on Azure. I know you have a deep vision for what AI needs to be and that's what got you to get this built. It's a family of models that are both response and reasoning models and you have a very exciting roadmap. You want to just tell us a little bit about sort of your vision, the capability you're pushing on both capability and efficiency. So maybe you can just talk about a little bit of that.
[01:20]
B
Sure. So yeah, with Groq, especially with Grok 3.5 that is about to be released, it's trying to reason from first principles, so apply kind of the tools of physics to thinking. So if you're trying to get to fundamental truths, you boil things down to the axiomatic elements that are most likely to be correct, and then you reason up from there and then you can test your conclusions against those axiomatic elements. And in physics, if you violate conservation of energy or momentum, then you're either going to get a Nobel Prize or you're wrong. And you're all certainly wrong. Basically, that's really the focus of Grok 3.5 is sort of find the fundamentals of physics and applying physics tools across all lines of reasoning and to aspire to truth with minimal error. There's always going to be some mistakes that are made, but aim to get to truth with acknowledged error, but minimize that error over time. And I think that's actually extremely important for AI safety. So I've thought a lot for a long time about AI safety and my ultimate conclusion is the old maxim that honesty is the best policy. It really is for safety. But I do want to emphasize we have and will make mistakes, but we aspire to correct them very quickly. And we are very much looking forward to feedback from the developers, develop a community to say like, what do you need? Where are we wrong? How can we make it better? And to have Grok be something that the developer community is very excited to use and where they can feel that their feedback is being heard and GROK is improving and serving their needs.
[03:14]
A
Yeah, I know it's in some sense, you know, cracking the physics of intelligence is perhaps the real goal for us to be able to use AI at scale. And so it's so good to, you know, take that first principles approach that you and your team are taking. And also you're deploying this. I mean, one of the things about sort of what you do is you're doing, you know, unsupervised FSD on one side you're doing robotics. Of course there's Groq. So you're deploying Grok across all of your businesses from SpaceX to Tesla. Obviously at X, I would love to even, you know, one of the themes for this developer conference, Elon, is we're building pretty sophisticated AI apps.
[03:52]
B
Right.
[03:52]
A
It's not even about any one model. It's about orchestrating multiple models, multiple agents, just anything that you are seeing in the real world application side, even inside of your own companies. When you think about even a Tesla or a SpaceX where you put Grok and these other AI models you're building.
[04:10]
B
Yeah, it's incredibly important for AI model to be grounded in reality. Reality, I was saying, which is physics is the law and everything else is a recommendation, which is, I'm not suggesting people break the laws made by, you know, humans. You know, we should generally obey the laws of humans. But, but I've seen many people break human made laws, but I have not seen anyone break the laws of physics. So for, for any given AI, grounding it against reality and reality. For example, as you mentioned, with, with the car needs to drive safely and correctly. The humanoid robot Optimus needs to, you know, perform the task that it's being asked to perform. These are things that are very, very helpful for ensuring that the model is truthful and accurate because it has to adhere to laws of physics. So I think that's actually maybe somewhat overlooked or at least not talked about enough is that to really be intelligent it's got to make predictions that are in line with reality. In other words, physics, it's a really fundamental thing and being able to ground that with cars and robots is very important. We are seeing Grok be very helpful in things like customer service. And the AI is infinitely patient and friendly and you can yell at it and it's still going to be very nice.
[05:42]
A
That's good.
[05:43]
B
Yeah. And so. So I think in terms of improving the quality of customer service and sort of issue resolution, AI is already. GROK is already doing quite a good job that at SpaceX and Tesla, and we look forward to offering that to other companies.
[06:02]
A
No, that's fantastic. Really thrilled to get this journey started, getting that developer feedback and then looking forward to even how they deploy. There is these language models, I think over time we will have this coming together of language models with vision, with action, but to your point, being really grounded on a real world model. And that I think is ultimately the goal here. And so thank you so much, Elon, for briefly joining us today. And we're really excited about working with you and getting this into the developer's hands.
[06:32]
B
Thank you very much. And I can't emphasize enough that we're looking for feedback from you, the developer audience. Tell us what you want and we'll make it happen. Thank you.