The birth of the internet is undoubtedly one of humanity’s greatest inventions. Claude Shannon’s information theory laid the theoretical foundation for the internet. Shannon defined information as something that reduces uncertainty, independent of its meaning. This view emphasizes the transmission and encoding of information, enabling the free flow of any kind of information across the internet, which created the information age we know today. However, as the internet has rapidly developed, we have gradually realized that information is not just a stream of meaningless bits—it also carries value, trust, and emotions. Norbert Wiener’s information theory focuses more on the role of information in human society, emphasizing that information is a crucial part of communication, with rich meaning and value.

How to transform Shannon’s information internet—devoid of meaning—into a Wiener-based internet, which embodies meaningful trust-value, is the challenge we face. Fortunately, the emergence of Bitcoin offers us a potential path.

Bitcoin is essentially a system based on Shannon’s information theory. Through the Proof-of-Work (PoW) mechanism, it converts disordered computational power into an ordered blockchain structure and turns meaningless information into meaningful data. The Unspent Transaction Output (UTXO) in Bitcoin is one such piece of meaningful information—it records the transaction history and ownership relationships of Bitcoin, thus becoming the foundation of trust.

Satoshi Nakamoto, in designing Bitcoin, cleverly utilized the UTXO structure along with the PoW mechanism, realizing the transformation from a meaningless information internet into one based on meaningful trust-value. The UTXO is similar to real-world currency, where every transaction must have a clear origin and destination, ensuring traceability and transparency. Meanwhile, the PoW mechanism ensures the uniqueness and immutability of UTXOs through competitive computational power, thus establishing the foundation of trust.

Satoshi’s design offers us a definitive direction: how to emerge from Shannon’s meaningless information internet into a meaningful trust-value internet based on Wiener’s information theory?

To achieve this, we can consider the following approaches:

1. ‍Using Blockchain to Structure Information: Convert information on the internet into a UTXO structure that carries clear meaning and value. This could include transforming digital assets, identity information, intellectual property, and more into UTXOs, which makes them traceable, verifiable, and tradable.‍
2. Consensus Mechanisms for Trust: Ensuring the uniqueness and immutability of UTXOs through PoW or other consensus mechanisms. Just like Gödel’s incompleteness theorem shows that any formal system has unprovable propositions, consensus mechanisms create a “relative truth” in a decentralized network, ensuring the reliability of information.‍
3. Creating an Open and Transparent Environment: Build a secure, transparent, and open network where people can freely exchange and utilize meaningful information. This mirrors Turing machines’ ability to simulate computation: in an open environment, information—like symbols on a Turing machine tape—can be freely processed, fostering the exchange of information and value.‍
4. Thermodynamic Work: By leveraging “thermodynamic work,” we can turn Shannon’s chaotic, meaningless information internet into an ordered, meaningful value network based on Wiener’s theory. Like life systems evolving from disorder to order, incentive mechanisms guide the network toward more valuable directions.‍
5. Self-Directed Modeling: Empower the network with intelligence to autonomously learn, evolve, and adapt to environmental changes. The network can adjust its structure and parameters based on user behaviors and transactions, optimizing resource allocation and improving efficiency. This reflects the McCulloch-Pitts neuron model’s concept of self-learning neural networks.‍
6. Perceptive Automata: Integrate perceptive capabilities into the network, enabling it to sense and interact with the physical world. For example, IoT devices can collect data from the environment and user behaviors, adjusting the network’s actions based on this perception. This brings the network beyond the virtual world, enabling interaction with the physical world and creating greater value.

Through these principles, BEVM(λ) aspires to build a meaningful trust-value internet that transcends Shannon’s theory. The aim is a network where information flows freely, value is securely exchanged, the network evolves autonomously, and the virtual and physical worlds are seamlessly integrated.

Inspired by McCulloch-Pitts Neuron Model

Part of the inspiration behind BEVM(λ)’s design comes from the 1943 paper “A Logical Calculus of Ideas Immanent in Nervous Activity” by Warren McCulloch and Walter Pitts, which proposed the McCulloch-Pitts neuron model. This model laid the foundation for neural network research and contained deep philosophical implications.

The model simplifies a neuron into a logical unit, comparing weighted inputs to a threshold and outputting either “excitation” or “inhibition.” This simplification captures the most basic features of neural activity and emphasizes the connections and interactions between neurons. McCulloch-Pitts’ concept of networked intelligence aligns with BEVM(λ)’s self-directed modeling principle.‍

Looking to the Future of BEVM(λ)‍

BEVM(λ) is not just a technological breakthrough; it also represents an expansion of the boundaries of human cognition. It seeks to answer a fundamental question: Can we build a smarter, more trustworthy, and more valuable network that goes beyond the limitations of the current internet?

The future of BEVM(λ) is full of limitless possibilities. It may reshape our understanding of information and value, ultimately guiding us into a more prosperous digital age.

Summary‍

BEVM(λ) is a project aimed at building a trust-value internet. Drawing inspiration from thinkers like Karp, Gödel, Turing, and Nakamoto, and using principles from the McCulloch-Pitts neuron model, BEVM(λ) outlines six core design principles: UTXO Structuring, Consensus-based Trust, Open & Transparent Environment, Thermodynamic Work, Self-Directed Modeling, and Perceptive Automata. BEVM(λ) strives to build a meaningful trust-value network on top of Shannon’s theory, ultimately creating a network where information flows freely, value exchanges securely, and virtual and physical worlds merge.