Axiom Distributed AI - Revision history

Al Piskun at 14:21, 20 May 2026

2026-05-20T14:21:15Z

Al Piskun at 13:47, 20 May 2026

2026-05-20T13:47:29Z

← Older revision		Revision as of 13:47, 20 May 2026
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	~~[[File:{{#setmainimage:Axiom-logo.png}}\|alt=Axiom Distributed AI\|center\|frameless]]~~
	{{Infobox software		{{Infobox software


	\| name = Axiom Distributed AI		\| name = Axiom Distributed AI
	\| screenshot = Axiom-logo.png		\| screenshot = Axiom-logo.png
	\| caption = Logo of the Axiom Distributed AI project		\| caption = Logo of the Axiom Distributed AI project

			\| status = Inactive
			\| category = Experimental
			\| compute = CPU & GPU
			\| dependencies = None

	\| developer = PyHelix / Axiom Project Team		\| developer = PyHelix / Axiom Project Team
	\| released = {{Start date and age\|2026\|01\|23}}		\| released = {{Start date and age\|2026\|01\|23}}
	\| discontinued = ~~Yes -~~ {{Start date and age\|2026\|03\|21}}		\| discontinued = {{Start date and age\|2026\|03\|21}}
			\| repository = [https://github.com/PyHelix/boinc-Axiom github.com/PyHelix/boinc-Axiom]


	~~\| repository = [https://github.com/PyHelix/boinc-Axiom github.com/PyHelix/boinc-Axiom]~~
	\| programming language = Python, C++		\| programming language = Python, C++
	\| operating system = Windows, Linux		\| operating system = Windows, Linux

			\| stats as of = {{Start date and age\|2026\|03\|14}}
			\| average performance = 5398.69 GigaFLOPS
			\| active users = 65
			\| total users = 94
			\| active hosts = 219
			\| total hosts = 159

			\| rac =
			\| credit per day =
			\| gpu performance =
			\| cpu performance =

	~~\| platform = BOINC~~
	~~\| genre = Distributed computing, Artificial Intelligence~~
	\| license = Open Source		\| license = Open Source
	\| website = [https://web.archive.org/web/20260319085629/https://axiom.heliex.net/ Archived website]		\| website = [https://web.archive.org/web/20260319085629/https://axiom.heliex.net/ Archived website]
	}}		}}

			[[File:{{#setmainimage:Axiom-logo.png}}\|alt=Axiom Distributed AI\|center\|frameless]]

	'''[https://axiom.heliex.net/ Axiom Distributed AI]''' was an experimental volunteer distributed computing project built on the [https://berkeley.edu BOINC] platform. Launched in early 2026, the project explored an alternative approach to artificial intelligence training by using decentralized, biologically inspired learning techniques rather than conventional centralized AI infrastructure [https://linustechtips.com].		'''[https://axiom.heliex.net/ Axiom Distributed AI]''' was an experimental volunteer distributed computing project built on the [https://berkeley.edu BOINC] platform. Launched in early 2026, the project explored an alternative approach to artificial intelligence training by using decentralized, biologically inspired learning techniques rather than conventional centralized AI infrastructure [https://linustechtips.com].

Al Piskun at 17:19, 19 May 2026

2026-05-19T17:19:05Z

← Older revision		Revision as of 17:19, 19 May 2026
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	\| developer = PyHelix / Axiom Project Team		\| developer = PyHelix / Axiom Project Team
	\| released = {{Start date and age\|2026\|01\|23}}		\| released = {{Start date and age\|2026\|01\|23}}
	\| discontinued = Yes ~~(Completed Test / Proof of Concept)~~		\| discontinued = Yes - {{Start date and age\|2026\|03\|21}}

Al Piskun: {{Start date and age|YEAR|MONTH|DAY}}

2026-05-19T16:41:52Z

← Older revision		Revision as of 16:41, 19 May 2026
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	\| developer = PyHelix / Axiom Project Team		\| developer = PyHelix / Axiom Project Team
	\| released = 2026-01-23		\| released = {{Start date and age\|2026\|01\|23}}
	\| discontinued = Yes (Completed Test / Proof of Concept)		\| discontinued = Yes (Completed Test / Proof of Concept)

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	\| genre = Distributed computing, Artificial Intelligence		\| genre = Distributed computing, Artificial Intelligence
	\| license = Open Source		\| license = Open Source
	\| website = [https://~~axiom~~.~~heliex~~.~~net~~/ axiom.heliex.net]		\| website = [https://web.archive.org/web/20260319085629/https://axiom.heliex.net/ Archived website]
	}}		}}

	'''Axiom Distributed AI''' was an experimental volunteer distributed computing project built on the [https://berkeley.edu BOINC] platform. Launched in early 2026, the project explored an alternative approach to artificial intelligence training by using decentralized, biologically inspired learning techniques rather than conventional centralized AI infrastructure [https://linustechtips.com].		'''[https://axiom.heliex.net/ Axiom Distributed AI]''' was an experimental volunteer distributed computing project built on the [https://berkeley.edu BOINC] platform. Launched in early 2026, the project explored an alternative approach to artificial intelligence training by using decentralized, biologically inspired learning techniques rather than conventional centralized AI infrastructure [https://linustechtips.com].

	The project invited volunteers from around the world to donate spare CPU and NVIDIA GPU processing power to help train a shared neural network collaboratively across thousands of computers. Community analysis and forum data indicate that the project has concluded its run, operating primarily as a short-lived experimental test and proof-of-concept [https://berkeley.eduforum_thread.php?id=15694&postid=118571].		The project invited volunteers from around the world to donate spare CPU and NVIDIA GPU processing power to help train a shared neural network collaboratively across thousands of computers. Community analysis and forum data indicate that the project has concluded its run, operating primarily as a short-lived experimental test and proof-of-concept [https://berkeley.eduforum_thread.php?id=15694&postid=118571].

Al Piskun at 17:02, 18 May 2026

2026-05-18T17:02:15Z

Show changes

Al Piskun at 21:14, 16 May 2026

2026-05-16T21:14:03Z

← Older revision		Revision as of 21:14, 16 May 2026
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	== Axiom Distributed AI ==		[[File:{{#setmainimage:Axiom-logo.png}}\|alt=Axiom Distributed AI\|center\|frameless]]

	~~[[File:Axiom-logo.png\|right\|250px\|Axiom Distributed AI]]~~		'''Axiom Distributed AI''' is an experimental volunteer distributed computing project built on the [https://boinc.berkeley.edu/ BOINC] platform. The project explores a new approach to artificial intelligence training using distributed, biologically inspired learning techniques rather than conventional centralized AI infrastructure.

	'''Axiom Distributed AI''' is an experimental volunteer distributed computing project built on the [[BOINC]] platform. The project explores a new approach to artificial intelligence training using distributed, biologically inspired learning techniques rather than conventional centralized AI infrastructure.

	Axiom invites volunteers from around the world to donate spare CPU and GPU processing power to help train a massive neural network collaboratively across thousands of computers.		Axiom invites volunteers from around the world to donate spare CPU and GPU processing power to help train a massive neural network collaboratively across thousands of computers.

Al Piskun: initial population

2026-05-16T20:44:21Z

initial population

New page

== Axiom Distributed AI ==

[[File:Axiom-logo.png|right|250px|Axiom Distributed AI]]

'''Axiom Distributed AI''' is an experimental volunteer distributed computing project built on the [[BOINC]] platform. The project explores a new approach to artificial intelligence training using distributed, biologically inspired learning techniques rather than conventional centralized AI infrastructure.

Axiom invites volunteers from around the world to donate spare CPU and GPU processing power to help train a massive neural network collaboratively across thousands of computers.

Official website: [https://axiom.pyhelix.com/ Axiom Distributed AI]
Open source development: [https://github.com/PyHelix/boinc-Axiom GitHub Repository]

== Overview ==

Unlike most modern AI systems that rely on centralized datacenters and expensive GPU clusters, Axiom experiments with a decentralized learning architecture inspired by '''Hebbian learning''' — often summarized as:

<blockquote>
"Neurons that fire together wire together."
</blockquote>

The project distributes training tasks across volunteer computers worldwide using the BOINC infrastructure. Each participant contributes small amounts of computation toward a larger shared neural model.

Axiom is currently considered a '''proof-of-concept research project''' exploring whether distributed Hebbian learning can scale effectively in a real-world volunteer computing environment.

== Why Axiom Distributed AI? ==

Traditional AI systems typically depend on:

* Massive centralized datacenters
* High energy consumption
* Large-scale backpropagation training
* Expensive specialized hardware

Axiom instead investigates whether learning can emerge from:

* Distributed volunteer computation
* Correlation-based learning
* Decentralized pattern recognition
* Biologically inspired neural adaptation

The long-term vision is to explore alternative methods for building AI systems that are:

* More decentralized
* More energy efficient
* Community driven
* Resistant to centralized control

== Goal ==

The immediate goal of the project is to demonstrate that:

'''Distributed Hebbian learning works at scale.'''

If successful, the research could contribute toward new approaches in:

* Neural network training
* Decentralized artificial intelligence
* Distributed machine learning
* Collaborative AI infrastructure
* Emergent pattern recognition systems

In the long term, models trained on extremely diverse real-world data could potentially become foundational systems for future AI applications.

At present, the project primarily serves as an experimental research platform and proof of concept.

== Methods ==

Axiom trains neural systems to recognize patterns in data using the spare processing power of volunteer computers.

Instead of conventional language-model training, Axiom currently focuses on learning:

* Bit-level compression patterns
* Sequence prediction
* Correlations within data streams
* Generalized pattern recognition

=== Key Technical Concepts ===

# '''Not an LLM'''
#* Axiom is '''not''' currently training a Large Language Model (LLM).
#* The system instead attempts to learn predictive patterns at the bit-stream level.
#
# '''Distributed Learning'''
#* Training workloads are distributed across volunteers worldwide through BOINC.
#* Each computer contributes partial learning updates to the shared model.
#
# '''Correlation-Based Credit System'''
#* Random or low-quality data naturally contributes less to the model.
#* Useful learning signals correlate more strongly with other contributors' gradients.
#* This creates a natural weighting system favoring meaningful patterns.
#
# '''Noise Reduction'''
#* Random noise generally fails to correlate with broader learning patterns.
#* As a result, noisy data contributes less to overall model development.
#
# '''Generalization Through Diversity'''
#* Diverse datasets may improve the model's ability to generalize across different data types.
#* Text, code, images, documents, and structured data may all contribute useful patterns.

== Monitoring Learning Progress ==

The Axiom website provides live statistics and progress monitoring.

One key metric is:

'''Bit loss'''

When bit loss trends downward over time, it suggests the neural model is learning meaningful structures and predictive relationships rather than memorizing random noise.

Volunteers can monitor:

* Model learning progress
* Training statistics
* Network participation
* Workunit activity
* Validation metrics

== Contributing Data ==

Volunteers may optionally contribute local files to help train the system.

=== Windows ===

Place files in:

<pre>
%USERPROFILE%\Axiom\contribute\
</pre>

=== Linux Mint 22.3 ===

Place files in:

<pre>
\boinc\Axiom\contribute\
</pre>

=== Supported Contribution Types ===

Users may contribute many different file types, including:

* Documents
* Images
* Source code
* PDFs
* Logs
* Structured datasets
* Experimental real-time data streams

The project encourages experimentation and creative uses of distributed training data.

== Open Source Development ==

Axiom Distributed AI is open source software.

Source code and development discussions are available on GitHub:

[https://github.com/PyHelix/boinc-Axiom boinc-Axiom GitHub Repository]

The project welcomes:

* Developers
* Testers
* Researchers
* BOINC volunteers
* AI enthusiasts

== Project Team / Sponsors ==

* PyHelix
* Axiom Project

== External Links ==

* [https://axiom.pyhelix.com/ Official Axiom Distributed AI Website]
* [https://github.com/PyHelix/boinc-Axiom Axiom GitHub Repository]