The Next Era of Computing | Extropic

Summary

The speaker, a physicist with a deep interest in theoretical physics and information theory, shares his journey of eight years leading to a breakthrough in computing. He discusses the evolution from quantum computing to a new paradigm that utilizes noise in thermodynamics to perform AI as a physical process. This approach is more energy-efficient and faster than current hardware, as it leverages the natural computation methods akin to how our brains work. The speaker introduces the concept of 'thermodynamic computing' and explains how it uses Josephson junctions, a key component in superconducting chips, to achieve superconductivity and exploit the Josephson effect. He envisions this technology as a significant step towards expanding the scope and scale of intelligence throughout the universe, enabling us to solve complex problems and ultimately reach for the stars.

Takeaways

• 🚀 The speaker's journey began 8 years ago with the concept that has now materialized into a new paradigm of computing, which they believe will change the world.
• 🌌 The speaker has always been interested in understanding the universe to build technologies with a maximal impact on scaling civilization to the stars.
• 🧠 The idea of viewing the universe as a simulation and embedding AI into the physics of the world came naturally from a background in theoretical physics and information theory.
• ⚙️ The challenge in quantum computing was noise, which is also a problem in low-power digital computers, but the new devices use this noise as an asset.
• 🌟 The speaker was inspired by the power of machine learning and the concept of a physical system performing machine learning as a physical process.
• 📊 Digital computers use bits to represent values, but the new paradigm is a different way of programming, closer to how nature and our brains compute.
• 🔌 As circuits get smaller, voltage noise becomes a problem for classical computation in CPUs, but the new thermodynamic computing aims to use this noise to drive computation.
• 💡 The new chips don't use transistors and instead use continuous variables and fuzzy values, which can be thought of as a point cloud shaped by data.
• 🔧 The process of machine learning is likened to a physical process where a parameterized physical device optimizes itself to accomplish a given task.
• 🌟 The speaker refers to the differentiable programming mindset, where gradient descent is considered a better programmer, as Software 2.0.
• 🏭 The speaker is in Sherbrook, Canada, at a fabrication facility where they manufacture a key component called Josephson junctions for superconducting chips.
• ❄️ The chips are cooled to 10 millikelvin to achieve superconductivity, which is necessary for exploiting the Josephson effect.
• 🔩 The technology is seen as a big step towards more energy-efficient and faster computers, which could fundamentally change how AI algorithms are run.
• 🌠 The ultimate goal is the expansion of intelligence throughout the universe, and the technology being developed is a significant step in that direction.

Q & A

What was the initial inspiration for the development of this new computing paradigm?

The idea for this new computing paradigm came to the speaker about 8 years ago, stemming from an interest in understanding the universe and building technologies with maximal impact on scaling civilization to the stars.

How does the speaker's background in theoretical physics and information theory influence their approach to AI?

The speaker's background led them to view the universe as a large simulation and naturally embed AI into the physics of the world, which is a different approach from traditional digital computation.

What is the main challenge faced in quantum computing that this new technology aims to address?

Noise is identified as a significant issue in quantum computing, which also becomes a problem when trying to create low-power digital computers. The new technology uses this noise as an asset rather than a liability.

How does the speaker describe the process of machine learning with a physical system?

The speaker describes it as a powerful concept where a physical system performs machine learning as a part of physics, which they initially tried to discredit but found to be compelling and feasible.

What is the fundamental difference between digital computers and the new thermodynamic computing approach?

Digital computers represent values in bits, while the new approach uses continuous variables and fuzzy values over a continuous variable, which is closer to how nature computes and how our brains compute.

How does the concept of 'differentiable programming' or 'software 2.0' fit into the speaker's vision for AI?

Differentiable programming, as termed by Andre Karpathy, is central to the speaker's vision where gradient descent is considered a better programmer than humans, optimizing the physical device parameters to accomplish tasks.

What are Josephson junctions, and why are they important to the new computing technology?

Josephson junctions are a key component in superconducting chips, acting like transistors for superconductivity. They are crucial for exploiting the Josephson effect and enabling AI as a physical process.

Why is superconductivity essential for the operation of these new chips?

Superconductivity is necessary to achieve the desired effects, such as low dissipation and exploiting the Josephson effect, which allows for the programmable physics of electrons in the metals.

What is the significance of the speaker's work in Sherbrook, Canada?

The speaker's work in Sherbrook involves the manufacturing of the first chips, which are superconducting and serve as a proof of concept for the thermodynamic computing paradigm, potentially revolutionizing the field.

What are the next steps for the development and adoption of this new computing technology?

The next steps include demonstrating similar principles in silicon, open sourcing the software, and encouraging global collaboration to program simulated and eventually real thermodynamic computers.

How does the speaker view the ultimate goal of their technology in the context of humanity's future?

The speaker sees the technology as a significant step towards expanding the scope and scale of intelligence throughout the universe, enabling humanity to solve complex problems and advance towards the stars.

What is the speaker's perspective on the importance of energy efficiency in the development of AI?

The speaker emphasizes that creating more energy-efficient computers that operate faster by fundamentally running AI algorithms differently is a game-changer, allowing for the application of intelligence to solve a wide range of problems.