Entropic Intelligence Since 2017

Amtropy

An abstract entropy arising from computations of deep networks. A generative force defined on the deep layers — a discovery of how depth behaves and what can be computed.

Explore the Theory Get in Touch
Amtropic Machine — 99 Hidden Layers Training Visualization

What is Amtropy?

Amtropy denotes an abstract entropy that arises from computations of deep networks. It is entropic because amtropy is defined following thermodynamic rules — a metric observed consistently from well-formed networks.


It is a generative force defined on the deep layers of stacked RBMs, a behavior of patterns related with the confidence level of them. It helps to choose better models among many options, or it is a manifestation of emotion or sense of goal to be pursued by the agent.

S → 𝜙
Entropy ↔ Abstraction

Amtropic Machine

A kernel solution implementing Amtropy theory with supporting algorithms — built to be a building block of scalable, real-time systems.

Kernel Architecture

Implements Amtropy theory with BP, softmax, and thoughtful utilities in a plug-and-play style for real-time applications. ~100K lines of C code.

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Deep Layer Intelligence

Deeper layers improve accuracy beyond DBN architectures. Entropic monotonicity — entropy consistently decreases in higher layers, yielding greater abstraction (𝜙).

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Foundational Platform

Designed as the core tool to build foundational LLMs and other critical projects. Scalable systems constructed fast and running efficiently.

100K+
Lines of C Code
99
Hidden Layers
2016
Development Since
𝜙 · 𝜒
Abstraction & Volume

Entropic Monotonicity

Our discovery is that deeper layers improve accuracy, and a consistent metric in the depth of layers is the entropic monotonicity — entropy keeps decreasing in higher layers.

The inverse of amtropy is defined as the degree of "abstraction" symbolized as 𝜙. The volume metric (𝜒) also decreases along the depth. 99 hidden layers working together, consistently improving accuracy and abstraction.

The implications expand perspectives on modelling networks and open new applications based on the computation of emotions and desires as well as optimal generations.

Layer 1
H = 0.95
Layer 10
H = 0.82
Layer 25
H = 0.65
Layer 50
H = 0.42
Layer 75
H = 0.24
Layer 99
H = 0.08
Amtropy (S) — decreasing ↓
Abstraction (𝜙) — increasing ↑

Business Scope

Building scalable AI solutions and partnerships for real-world applications.

01

Modular AI Kernels

Providing the AM kernel solution to institutes who can benefit from modular AI kernels to solve real-time data streams.

02

Joint Research

Building joint researches of difficult problems with accountable partners. Collaborating on foundational AI challenges.

03

Financial Trading

A financial trading system running on AM kernels — successfully proven as an alpha version, opening valuable business opportunities in financial services.


Get in Touch

Ready to explore
the depth?

We welcome accountable partners who share our vision of understanding deep layers and building scalable AI solutions.

yshan@amtropy.com

Contact only if you are accountable.