Podcast Summary: How I Invest with David Weisburd | E175: Elon Musk: 10 Billion Humanoid Robots by 2040? w/NEA Partner Aaron Jacobson

Introduction

In episode E175 of How I Invest with David Weisburd, host David Weisburd engages in an insightful discussion with Aaron Jacobson, a Partner at NEA (New Enterprise Associates). The episode delves into the ambitious prediction made by Elon Musk regarding the proliferation of humanoid robots and explores the multifaceted challenges and opportunities within the realms of robotics, artificial intelligence (AI), and cybersecurity.

1. Elon Musk’s Prediction on Humanoid Robots

David Weisburd (A) initiates the conversation by referencing Elon Musk's bold prediction that by 2040, there will be over 10 billion humanoid robots on Earth. Aaron Jacobson (B) responds with a mix of admiration and skepticism.

Aaron Jacobson [00:15]: "Huge fan of all the companies that he's built, as well as him being a technologist and futurist. But I really view Elon’s predictions, like all of them, they're super inspirational, but they're optimistic."

Jacobson acknowledges Musk's visionary stance but contends that such predictions are overly optimistic, citing the protracted timeline required for technological advancements and supply chain scaling.

2. Challenges in Building General-Purpose Humanoids

Jacobson outlines the primary hurdles in developing versatile humanoid robots:

a. Robustness and Reliability

Modern robots excel at specialized tasks but falter with minor changes in their environment or tasks.

Aaron Jacobson [01:26]: "Robots are historically very good at very narrow, very specific tasks. But as soon as you adjust one small thing in the task... it fails."

b. Data Requirements and Model Architectures

Unlike language models, robotics requires vast and diverse datasets to navigate the physical world effectively. Current AI models, particularly transformers, are inefficient for robotics due to their high data and compute demands.

Aaron Jacobson [03:30]: "The quantity is not going to be the only thing that matters. Quality is going to be important too, as well as the diversity of data."

c. Supply Chain and Scaling Production

Producing billions of humanoids necessitates massive investments in components like motors and other essential parts, posing significant logistical and financial challenges.

3. Industrial vs. Consumer Applications for Humanoid Robots

A: Jacobson contrasts the feasibility of deploying humanoids in industrial settings versus consumer homes.

Aaron Jacobson [04:28]: "We are going to see humanoids very much in industrial applications, because these are very narrow applications... there's much more economic viability."

In industrial environments, robots can operate within controlled setups, enhancing reliability and reducing security concerns. Conversely, consumer applications face significant safety and practicality hurdles.

4. Technological Breakthroughs Needed for Scaling Humanoids

Jacobson identifies critical advancements required to realize large-scale humanoid deployment:

• Data Collection Efficiency: Developing cost-effective methods for gathering extensive video and physical data, possibly through teleoperations.

• Model Architecture Innovations: Creating more efficient AI architectures beyond transformers to handle the complexity of the physical world.

• World Modeling: Enhancing AI's ability to build internal models of the world akin to human cognitive processes.

Aaron Jacobson [07:03]: "If we found an architecture that was a hundred times, a thousand times more innovative, then I think that would really go a long way because it would start to function like the human brain."

5. AI Models: Closed vs. Open Models and Value Capture

The discussion shifts to the landscape of AI models, distinguishing between closed and open models.

Closed Models: Proprietary models accessed via specific platforms or APIs, with a few dominant players likely to capture substantial value.

Open Models: Models like Meta’s LLaMA that are accessible for customization and integration, enabling a broader ecosystem of value generation.

Aaron Jacobson [10:04]: "There's value capture in both of these at different layers... the value starts to accrue in really the infrastructure surrounding the model."

6. Facebook’s Strategy with LLaMA

Jacobson analyzes Facebook's (Meta's) strategy in releasing the LLaMA engine as an open model, emphasizing its dual role in leveling the competitive landscape and enhancing brand value.

Aaron Jacobson [12:31]: "For me, it's a few things. One, it's a bit of an equalizer in the model ecosystem... Two, it's also a brand. It hugely impacts Facebook brand."

7. Cybersecurity: Current Landscape and Growth

Transitioning to cybersecurity, Jacobson provides a comprehensive overview of its rapid growth driven by increasing threats and evolving technological landscapes.

a. Increase in Breaches and Ransomware

The frequency and severity of cyberattacks, including ransomware and data breaches, are escalating.

Aaron Jacobson [14:04]: "Global ransomware attacks went up in 2024 by 11%. There was over 5,000 incidents."

b. Architectural Shifts Driving Growth

Emerging technologies like mobile applications, cloud computing, and AI introduce new security challenges, necessitating sophisticated cybersecurity solutions.

Aaron Jacobson [14:04]: "Now we've got our employees want to run agents to automate a lot of the workflows... how are we going to secure all those agents?"

8. Penetration Testing in Cybersecurity

Jacobson elaborates on the importance of penetration testing (pen testing) as a proactive measure to identify and mitigate vulnerabilities.

Aaron Jacobson [16:15]: "Cybersecurity pen testing is the best practice where you test your network and your IT infrastructure from the outside in."

9. Future of Cybersecurity

Jacobson forecasts a grim near-term outlook with escalating cyber threats but remains optimistic about long-term solutions driven by AI advancements.

Aaron Jacobson [17:29]: "It's going to get a lot worse and scarier before it gets a lot better... AI is going to fundamentally solve the biggest challenge in cyber, which is the lack of talent."

10. Role of Insurance in Cybersecurity

Cyber insurance plays a crucial role in promoting best practices and mitigating financial risks associated with cyberattacks.

Aaron Jacobson [19:31]: "Insurance encourages companies to embrace best practices because the whole point of insurance is to gather as much information about an organization and their cybersecurity processes to understand risk."

11. Preventive Measures for Individuals and Companies

Emphasizing foundational cybersecurity practices, Jacobson advises on implementing multi-factor authentication (MFA) and least privilege access to reduce vulnerability.

Aaron Jacobson [20:39]: "It's all about the basics. Let's get back to the basics. Multi factor authentication, least privilege access."

12. Speaker B's Background at Catalyst and NEA

Jacobson shares insights from his tenure at Frank Quattrone's Catalyst, highlighting the importance of founder characteristics in building successful startups.

Aaron Jacobson [24:47]: "Frank taught me about a lot about what to look for in a founder to ultimately build a successful company."

13. Evolution of Venture Industry

Discussing the future of venture capital, Jacobson anticipates an expansion of investment stages and strategies to accommodate scaling startups.

Aaron Jacobson [26:04]: "There are synergies in terms of being able to invest at multiple stages... it's why we're a multi stage investment firm."

14. How to Follow Speaker B on Social Media

For listeners interested in connecting with Aaron Jacobson, he is active on platforms like X (formerly Twitter) under the handle @AaronAJ and on LinkedIn. He encourages founders to reach out via email at a.jacobson@nea.com.

Aaron Jacobson [26:47]: "Always love meeting founders and talking about the future of cyber, AI and robotics."

Conclusion

Episode E175 offers a deep dive into the intersecting worlds of robotics, AI, and cybersecurity, underscored by expert perspectives from NEA's Aaron Jacobson. The discussion balances optimism with realism, highlighting both the transformative potential and the significant challenges inherent in these rapidly evolving fields.

Notable Quotes with Timestamps

• 00:15 – On Elon Musk’s Optimistic Predictions: “But I really view Elon’s predictions... they’re super inspirational, but they're optimistic.”

• 01:26 – On Robotics' Task-Specific Limitations: “Robots are historically very good at very narrow, very specific tasks. But...it fails.”

• 07:03 – On the Need for Innovative Model Architectures: “If we found an architecture that was a hundred times, a thousand times more innovative... it would start to function like the human brain.”

• 10:04 – On Value Capture in Closed vs. Open AI Models: “There's value capture in both of these at different layers...infrastructure surrounding the model.”

• 17:29 – On the Future of Cybersecurity: “AI is going to fundamentally solve the biggest challenge in cyber, which is the lack of talent.”

• 20:39 – On Preventive Cybersecurity Measures: “It's all about the basics. Let's get back to the basics. Multi factor authentication, least privilege access.”

This comprehensive summary encapsulates the critical discussions and insights shared during the podcast, providing readers with a thorough understanding of the topics covered without needing to listen to the full episode.