Investing in Quantum and Physical AI

Key Concepts:

• Quantum Computing: Utilizing quantum-mechanical phenomena to perform computations.
• Qubits: The basic unit of information in quantum computing.
• Physical AI: Integrating AI with sensors and robotics to create smart devices that interact with the physical world.
• Observability: The ability to monitor and understand the state of a system or environment.
• Predictability: The ability to forecast future events or conditions based on current data and trends.
• IoT (Internet of Things): A network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data.
• Foundational Models: Large AI models that can be adapted for various tasks.

Quantum Computing Opportunities

• Investment Thesis: The speaker is a long-term, early-stage investor seeking companies with the potential to reach valuations of $10-30 billion. Quantum computing is identified as a promising area for such growth, considered the next wave of innovation after AI.
• Timeline: While quantum computing has been in development for 30 years, experts believe significant advancements towards scaled quantum computers will occur within the next decade.
• Impact: Scaled quantum computers are expected to revolutionize industries like financial services and pharmaceuticals.
• Hardware Development: The primary goal in quantum computing is achieving 10,000 to 100,000 scaled qubits, with multiple hardware approaches being pursued.
• Business Models:
  • Rental: Currently, quantum computers are rented out at prices ranging from $10,000 to $50,000 per hour.
  • IP Revenue Sharing: A potential business model involves taking a revenue stream from the intellectual property (IP) and technology developed using quantum computers.
  • Analogy to Pharmaceuticals: The speaker suggests that the first entity to build a functional quantum computer could have a similar impact to a major pharmaceutical company like Pfizer, due to the potential for drug discovery and development.
• IBM's Role: IBM aims to have its quantum computers deployed and achieving real-world results by 2029.

Physical AI and Infrastructure

• Definition: Physical AI involves using foundational AI models to interact with sensors and robotics, creating smart devices that enhance our physical world.
• Focus: The speaker's venture fund is thesis-driven, focusing on the intersection of observability and predictability in the environment and infrastructure.
• Shift from Reactive to Predictive: The goal is to move from a reactive approach (fixing problems after they occur) to a predictive approach in managing infrastructure like water, pipelines, electricity, and roads.

Portfolio Companies and Examples

• Bright AI:
  • Technology: Develops stickers with sensors that can be attached to infrastructure like utility poles and water pipelines.
  • Functionality: These stickers provide real-time observability data, such as the angle of a utility pole, enabling proactive maintenance.
  • Impact: Prevents failures like utility poles falling on electrical wires.
  • Water Leak Detection: Bright AI's sensors can detect leaks in water pipelines, addressing the issue of losing 6 billion gallons of treated water daily.
• TC Labs:
  • Goal: Aims to save one gigaton of carbon each year.
  • Approach: Uses AI to improve the efficiency and carbon footprint of existing energy infrastructure, such as oil refineries.
  • Context: Addresses the increasing energy demands driven by AI.
• True Swift:
  • Focus: Provides data sets from sensors in forests.
  • Purpose: Enables early detection of forest fires and major storms.
  • Benefit: Helps prevent power outages and other disruptions caused by natural disasters.

Conclusion

The speaker is optimistic about the potential of both quantum computing and physical AI. Quantum computing promises to revolutionize various industries through enhanced computational capabilities, while physical AI aims to improve infrastructure management by enabling predictive maintenance and resource optimization. The portfolio companies highlighted demonstrate the practical applications of physical AI in addressing critical challenges related to infrastructure, energy efficiency, and environmental monitoring. The key takeaway is the shift towards proactive and predictive solutions powered by AI and sensor technology.