What is Thermodynamic Computing and How It Can Decentralize AGI?

Introduction

Artificial general intelligence (AGI) has the potential to revolutionize every aspect of our lives. But there’s a catch: current AGI research requires massive amounts of data, energy, and financial resources, centralizing control and limiting accessibility. We explore a revolutionary new hardware approach that could change everything. Extropic AI, a team forged at Google, is pioneering “thermodynamic computing,” a radically different approach to AI hardware.

This approach promises to be decentralized, cheap, and faster than current AI systems.

The Problem with Traditional AI Hardware

Traditional AI systems are based on digital logic, which operates with absolute values and clear, deterministic rules. This is ideal for tasks that have a definite answer or a set procedure. However, machine learning (ML), which is a subset of AI, thrives on probabilistic learning. This approach involves handling uncertainties and probabilities, learning from data to make predictions or decisions. However, this mismatch between Traditional AI and Machine Learning systems leads to:

Massive models: Modern ML models, like those used in deep learning, require a vast number of parameters to accurately capture the complexities of the data they learn from. This leads to the creation of very large models that need extensive computational resources to train.
Excessive energy consumption: Training these large models requires significant computational power, which in turn consumes a lot of energy. As AI technologies become more widespread, the energy demand for AI is expected to increase, potentially doubling by 2026 as per the International Energy Agency.
Hardware limitations: The hardware that powers AI, primarily GPUs and CPUs, relies on silicon transistors. There’s a physical limit to how small these transistors can be made, known as the Moore’s Law limit. As we approach this limit, it becomes increasingly difficult to improve the performance of silicon-based hardware without increasing its size or energy consumption.

What is Quantum Vs Classical Artificial Intelligence?

The Thermodynamic Computing Solution

Extropic AI is an innovative startup that has developed a new type of hardware inspired by the randomness found in nature. Their approach sits at the meso-scale, which is an intermediate level between classical and quantum computing. Their technology is:

Truly Probabilistic: Extropic AI’s hardware differs from traditional digital systems. It doesn’t simulate randomness through algorithms. Instead, it utilizes the natural randomness of physical systems. This approach enables the generation of random numbers. It also facilitates the performance of probabilistic learning directly through the hardware. This method proves to be a more natural fit for many machine learning algorithms.
Energy-Efficient: Their hardware is designed to be thermodynamically efficient, meaning it can perform computations using significantly less energy. This is achieved by harnessing entropy, which is the measure of randomness or disorder within a system. By utilizing entropy, the hardware can operate with lower energy requirements compared to conventional methods.
Ultra-Fast: Extropic AI’s hardware leverages randomization for faster computations. This approach contrasts with traditional digital calculations. These calculations are often complex and time-consuming. The use of physical systems to perform probabilistic computations allows for operations that are millions of times faster.

Benefits and Implications

Thermodynamic computing has the potential to completely transform the field of AI:

Agile Systems: Utilizing physical devices and components for computation, rather than solely relying on digital ones, can lead to the creation of more agile systems.This agility could allow AI systems to adapt more quickly to changing environments or requirements.
Uncertainty Quantification: Thermodynamic computing can contribute to better uncertainty quantification in neural network classification. This means AI systems could provide not just predictions but also measure the confidence in those predictions, which is vital for risk-sensitive applications.
Reversible Computing: As thermodynamic computing aligns with the laws of thermodynamics, it opens up possibilities for reversible computing. This could lead to systems where computations can be undone, potentially saving energy and reducing heat generation.

Conclusion

Extropic AI’s technology has the potential to be the “Transistor of the AGI Era,” ushering in a new era of intelligent machines that are available to everyone.

This is deep tech at its finest – an ambitious and challenging endeavor that could fundamentally change the world. The success of Extropic AI could not only lead to a new era of innovation but also create a multi-trillion dollar industry.