We are thrilled to announce the latest developments in our NeuraPilot project. We are excited to share that we have successfully implemented and are currently testing two of the three crucial components of self-driving technology:
1. Decision Making: Completed.
2. Vehicle Control: Completed.
3. Environment Detection: Work-in-progress.
To showcase the remarkable capabilities of NeuraPilot, we have created a captivating first-person view 3D and 360 videos. The simulation features twenty cars, each operating as a separate neural network. Remarkably, these neural networks consist of only fifty neurons, making efficient use of resources. The neural networks are trained from scratch, without any pre-training.
What sets our approach apart and enables our cars to learn quickly and effectively is our utilization of a small set of relevant invariants obtained through careful consideration of symmetries. For further information and details, please refer to our publication at https://arxiv.org/abs/2301.10077.
1. Decision Making: Completed.
2. Vehicle Control: Completed.
3. Environment Detection: Work-in-progress.
To showcase the remarkable capabilities of NeuraPilot, we have created a captivating first-person view 3D and 360 videos. The simulation features twenty cars, each operating as a separate neural network. Remarkably, these neural networks consist of only fifty neurons, making efficient use of resources. The neural networks are trained from scratch, without any pre-training.
What sets our approach apart and enables our cars to learn quickly and effectively is our utilization of a small set of relevant invariants obtained through careful consideration of symmetries. For further information and details, please refer to our publication at https://arxiv.org/abs/2301.10077.
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We are delighted to present NeuraTutor, the cutting-edge educational platform revolutionizing the way we learn.
Matching: Enjoy tailored learning with our advanced AI tutor matching.
Assistance: Instant help from our 24/7 AI assistant.
Notifications: Stay updated on tutor/student matches and chat messages.
Accessibility: Seamlessly access NeuraTutor via web or mobile apps.
Join the NeuraTutor community today and unlock a world of educational possibilities!
Download the NeuraTutor app now from the App Store https://apps.apple.com/us/app/neuratutor/id6447997772 or Google Play https://play.google.com/store/apps/details?id=com.neuratutor.anc
Matching: Enjoy tailored learning with our advanced AI tutor matching.
Assistance: Instant help from our 24/7 AI assistant.
Notifications: Stay updated on tutor/student matches and chat messages.
Accessibility: Seamlessly access NeuraTutor via web or mobile apps.
Join the NeuraTutor community today and unlock a world of educational possibilities!
Download the NeuraTutor app now from the App Store https://apps.apple.com/us/app/neuratutor/id6447997772 or Google Play https://play.google.com/store/apps/details?id=com.neuratutor.anc
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Forwarded from The World as a Neural Network
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
https://artificialneuralcomputing.com/wann
Artificial Neural Computing
at the intersection of Physics, Biology and Machine Learning
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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
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
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Why do complex systems tend to exhibit critical behavior? The dataset-learning duality might be the answer. https://arxiv.org/abs/2405.17391
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🎉 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)
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)
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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
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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
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
Artificial Neural Computing
at the intersection of Physics, Biology and Machine Learning
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Forwarded from ML Journal Club
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!
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!
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Forwarded from ML Journal Club
Which Large Language Models do you use most often?
Final Results
65%
ChatGPT
42%
DeepSeek
17%
Claude
9%
Gemini
6%
Llama
7%
Qwen
4%
Mistral
1%
Gork
8%
None
Forwarded from The World as a Neural Network
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.
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Forwarded from The World as a Neural Network
“We apply the physics–learning duality to molecular systems ...” coming to arxiv near you this Tuesday https://youtu.be/7cfjS4mHbfQ
YouTube
Physics-Learning duality
Physics-based and learning-based simulations of water molecules from the paper "Molecular Learning Dynamics" by Yaroslav Gusev and Vitaly Vanchurin. https://arxiv.org/abs/2504.10560
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Forwarded from The World as a Neural Network
“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
And here, we show that all atoms are agents, all agents are learning — all things are learning.
https://arxiv.org/abs/2504.10560
arXiv.org
Molecular Learning Dynamics
We apply the physics-learning duality to molecular systems by complementing the physical description of interacting particles with a dual learning description, where each particle is modeled as an...
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Forwarded from The World as a Neural Network
Perhaps it's time for physicists to explore machine learning algorithms, biologists to learn differential geometry, and machine learning scientists to study quantum mechanics.
https://arxiv.org/abs/2504.14728
https://arxiv.org/abs/2504.14728
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🌟 We Are Now Accepting Applications for the Internship Program 🌟
Do you have extensive knowledge in mathematics, physics, and machine learning? Are you passionate about exploring learning systems at the deepest level—whether they are natural or artificial?
We are looking for motivated interns to join our research team working at the intersection of physics, biology, and machine learning. Our work is driven by the idea that the world itself may function as a neural network, and we aim to uncover the fundamental principles that govern these complex systems.
This internship offers a unique opportunity to contribute to cutting-edge theoretical and computational research, bridging ideas from multiple disciplines to deepen our understanding of the universe through neural physics.
🔗 Apply now: https://artificialneuralcomputing.com/internship
🔬 Discover our research: https://artificialneuralcomputing.com/research
Join us in pushing the boundaries of science, technology, and our understanding of reality.
Do you have extensive knowledge in mathematics, physics, and machine learning? Are you passionate about exploring learning systems at the deepest level—whether they are natural or artificial?
We are looking for motivated interns to join our research team working at the intersection of physics, biology, and machine learning. Our work is driven by the idea that the world itself may function as a neural network, and we aim to uncover the fundamental principles that govern these complex systems.
This internship offers a unique opportunity to contribute to cutting-edge theoretical and computational research, bridging ideas from multiple disciplines to deepen our understanding of the universe through neural physics.
🔗 Apply now: https://artificialneuralcomputing.com/internship
🔬 Discover our research: https://artificialneuralcomputing.com/research
Join us in pushing the boundaries of science, technology, and our understanding of reality.
Artificial Neural Computing
at the intersection of Physics, Biology and Machine Learning
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Our growing product line now features the LADS library, Neurah platform, and NeuraStock — alongside NeuraPilot, NeuraTutor, and NeuraPrint. See https://artificialneuralcomputing.com/products
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Join the Neurah Project
📢 We invite scholars from diverse disciplines to submit proposals exploring fundamental questions across the interconnected domains of human knowledge.
🧠 The Neurah project seeks to foster collaboration and catalyze breakthroughs in theory and application through contributions in physics, biology, chemistry, mathematics, computer science, neuroscience, psychology, philosophy, economics, political science, sociology, art, and education.
🤝 By bringing together diverse perspectives, we aim to advance new ideas and frameworks with the potential to transform research and education across fields.
🔗 Learn more and apply at http://Neurah.com
📢 We invite scholars from diverse disciplines to submit proposals exploring fundamental questions across the interconnected domains of human knowledge.
🧠 The Neurah project seeks to foster collaboration and catalyze breakthroughs in theory and application through contributions in physics, biology, chemistry, mathematics, computer science, neuroscience, psychology, philosophy, economics, political science, sociology, art, and education.
🤝 By bringing together diverse perspectives, we aim to advance new ideas and frameworks with the potential to transform research and education across fields.
🔗 Learn more and apply at http://Neurah.com
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