What do self-driving cars have to do with particle physics? A lot, actually. (Details in our new paper on arXiv https://arxiv.org/abs/2301.10077. Also check out the simulation https://artificialneuralcomputing.com/cars)

We now have a YouTube channel where we post videos of lectures and journal club presentations on the theory of machine learning. Feel free to join:
https://www.youtube.com/@ArtificialNeuralComputing

The World as a Neural Network

Are you curious about how the world operates like a neural network? Do you want to explore the implications of this idea? Our group meetings provide a platform for thought-provoking discussions of interdisciplinary topics such as the interconnectedness of systems and the emergence of complex behavior from simple rules. With a diverse group of individuals our meetings provide a unique opportunity to expand your knowledge, engage in stimulating discussions, and network with like-minded individuals.

Don't miss out on this chance; join us every Friday at noon EST via Zoom https://us06web.zoom.us/j/82683235624?pwd=WE1EbENwZXc0WkFyODU1Uk85YkZFdz09

YouTube videos of previous meetings: https://youtube.com/playlist?list=PLnu7tVik2MzKHBeqKy5nGWh5Hs5Wn2SX2

Facebook group: https://www.facebook.com/groups/2930104110608299

Telegram channel: https://t.me/theworldasaneuralnetwork and chat: https://t.me/theworldasaneuralnetworkchat

NeuraPrint ver 1.0

We are thrilled to introduce NeuraPrint, our remarkable psychological tool meticulously designed to measure and explore the fundamental aspects of your free will. Immerse yourself in the enchantment as NeuraPrint utilizes a selection of relevant invariants to predict a "random" sequence generated by none other than you. But that's not all! We are currently developing an extraordinary feature to measure your level of consciousness. Prepare yourself for a mind-expanding adventure as we dive deep into the captivating realm of relevant invariants, analyzing their secrets to predict the sequence. Get ready for an awe-inspiring journey with NeuraPrint!

Download now from the App Store and Google Play.

We're excited to announce our new website dedicated to the World as a Neural Network group, featuring a comprehensive Frequently Asked Questions section. Explore the interconnected world with us!

https://artificialneuralcomputing.com/wann

We are accepting applications for our 2024 internship program. Extensive knowledge of mathematics, physics and machine learning is required.

Phase I (January 2024 - February 2024): Taking an online class on advanced topics in machine learning (e.g. statistical modeling, thermodynamic description, non-equilibrium dynamics, physics- and bio-inspired algorithms, etc.)

Phase II (March 2024 - April 2024): Working on a research project that involves modeling (biological, physical or machine) learning system using numerical methods (e.g. developing numerical simulations, statistical analysis of learning systems, etc.)

Phase III (May 2024 - June 2024): Working on a research project that involves modeling (biological, physical or machine) learning system using analytical methods (e.g. developing theory of learning, designing machine learning algorithms, etc.) 

If you have no experience, but a lot of knowledge we strongly encourage you to apply. If you have a lot of experience, but no knowledge we strongly discouraged you to apply.
https://artificialneuralcomputing.com/internship

Early Warning System for pandemics? Why not! https://arxiv.org/abs/2401.04444

Why do complex systems tend to exhibit critical behavior? The dataset-learning duality might be the answer. https://arxiv.org/abs/2405.17391

🎉 NeuraPrint 2.0 🎉

Explore your mind like never before with NeuraPrint 2.0 — now available on iOS and Android!

Measure your Free Will and Consciousness with this unique tool:

🎲 Free Will: Determined by the accuracy of predictions of a 'random' sequence generated by the user.
🧠Consciousness: Calculated from the non-linearity of the predictions.

Ready to dive into self-discovery?

📲 Get it on [iOS] (https://apps.apple.com/us/app/neuraprint/id6446124144)

📲 Get it on [Android] (https://play.google.com/store/apps/details?id=org.anc.neuraprintapp.neuraprintapp)

A study of the emergence of classical field theories from the activation and learning dynamics of neural networks—whether artificial, biological, or fundamental. https://arxiv.org/abs/2411.08138

We are now hiring in Artificial Neural Computing.

Extensive knowledge of mathematics, physics and machine learning is required. Responsibilities include developing theory of learning and machine learning algorithms, modeling physical and biological systems, designing computer architecture and hardware components.

If you have no experience, but a lot of knowledge we strongly encourage you to apply. If you have a lot of experience, but no knowledge we strongly discouraged you to apply.

https://artificialneuralcomputing.com/internship

Starting in the new year, we will resume weekly Machine Learning Journal Club meetings. Here are some details:

WHY: The main goal is to discuss theoretical papers and ideas in machine learning. As far as we know, no such journal clubs currently exist, so let's try to keep the emphasis on theory, not numerics.

WHERE: The meetings will be held over Zoom and are open to all researchers and developers. Feel free to invite anyone who might be interested to join our dedicated group on Telegram: @ANCJournalClub.

WHEN: Unless stated otherwise, all meetings will take place on Tuesdays at 11 am ET. Please add this to your calendar, set a reminder, or use whatever method works for you—but please try not to be late.

WHAT: We will only discuss theoretical papers that are either already published or at least posted on arXiv. If you find something interesting, feel free to post it in this group along with your thoughts on why you think it’s relevant and/or interesting.

WHO: The meetings will start on January 7th, and Vitaly Vanchurin will present his paper, "Emergent Field Theories from Neural Networks." However, presenting papers by others (or inviting authors of relevant papers to present) is strongly encouraged. If you’re interested, please let us know, and we will add you to the schedule.

HOW: The meetings should be very informal, and everyone should feel free to actively participate in the discussions, ask relevant questions, make comments, etc.

Happy (upcoming) New Year!

A journey from physics to machine learning and back to physics. Along the way, we unified classical algorithms such as SGD, RMSProp, and Adam, developed new algorithms with superior learning efficiency, and identified a mechanism for the emergence of curved geometry.

“We apply the physics–learning duality to molecular systems ...” coming to arxiv near you this Tuesday https://youtu.be/7cfjS4mHbfQ

“If, in some cataclysm, all of scientific knowledge were to be destroyed, and only one sentence passed on to the next generations of creatures, what statement would contain the most information in the fewest words? I believe it is the atomic hypothesis: that all things are made of atoms.” — Richard Feynman

And here, we show that all atoms are agents, all agents are learning — all things are learning.

https://arxiv.org/abs/2504.10560