Nico

Longitudinal Vibes / Field Theory / Implosion Tech / AI Research Agents / Theurgy / Poetry ❤️

[Nico @longitudinales]

I am tagging @aaronmurakami

Eric Dollard is very active thru Aaron’s YouTube channel, they are hosting a new conference very soon, it’s sold out for in person but you could get the replays. You should contact Aaron as he is great and could get you in touch.

Sharing latest podcast and website for contact.

They need volunteers for their work so you could also help them.

One of my dreams is to volunteer and learn from Eric, Aaron and their hole team.

Eric is a hero and a master of field theory, he along Ken Wheeler and Dan Winter are the very few that understand the nature of our reality and could drive human evolution.

https://t.co/WCLPoSoXk7

https://t.co/uxoLgzUbaN

https://t.co/TpEAs53nco

[Nico @longitudinales]

@Jason I’m in

[Nico @longitudinales]

The Masters of Field Theory reflect to the Atomistic fallacy & psychosis around The Electron

“Unfortunately to a large extent in dealing with Dielectric Fields the prehistoric conception of the electrostatic charge, the Electron, on the conductor still exists, and by its use destroys the analogy between the two components of the Electric Field, the Magnetic and Dielectric. This makes the consideration of Dielectric Fields unnecessarily complicated”
Charles Proteus Steinmetz

“The idea of electricity as a flow of Electrons in a conductor is regarded as a Psychosis”
Oliver Heaviside

“The Electron is a Terminal End of one unit line of Dielectric Induction”
J J Thomson

He disagrees with the accepted atomic theory of matter, and does not believe in the existence of an
"Electron" as pictured by science. To account for its apparently small mass, science conceives of the Electron as a hollow sphere, a sort of bubble, such a bubble could exist in a medium as a gas or liquid because its internal pressure is not altered by deformation. But if, as supposed, the internal pressure of an Electron is due to the repulsion of electric masses, the slightest conceivable deformation must result in the destruction of the bubble! Just to mention another improbability. My ideas regarding the electron are at variance with those generally entertained. I hold that it is a relatively large entity carrying a surface charge and is not an elementary unit. When the Electron leaves an electrode of high potential and in a high vacuum it carries an electrostatic charge many times greater than normal
Nikola Tesla

“To describe an Electron as a negatively charged body is equivalent to saying that it is an expanding-contracting particle. There is no such condition in nature as a negative charge, nor are there negatively charged particles. Charge and discharge are opposite conditions, as filling and emptying, or compressing and expanding are opposite conditions”
Walter Russell

JJ Thomson developed the Ether Atom ideas of Faraday into his Electronic Corpuscle, this indivisible unit. One corpuscle terminates on one Faraday tube of force, and this quantifies as one Coulomb.
This corpuscle is not and electron, it is a constituent of what today is known incorrectly as an Electron.
In this view, that taken by J.J. Thomson, and N. Tesla, the cathode ray is not electrons, but in actuality corpuscles of the Ether
Eric Dollard

“There is no rest mass to an Electron. It is given here the Electron is no more than a broken loose "hold fast" under the grip of the tensions within the dielectric lines of force. They are the broken ends of the split in half package of spaghetti. Obviously this reasoning is not welcome in the realm of Einstein's Theory of Relativity”
Eric Dollard

[Nico @longitudinales]

@rsarver Outstanding! Thanks for sharing, please open source.

I am working on a physics + AI project and it will help me so much 🙏

[Nico @longitudinales]

@LilithDatura Aether Field Theory…of course!!!

Dreaming for that day where humanity finally understands Counterspace so they will learn that everything is a disturbance of the Aether manifested as Magnetism, Electricity, Gravity, Light and Matter

[Nico @longitudinales]

Check out this recent reply to a post you did about Encryption.

I refer to Encryption, Zeros, Quaternions, and of course Counterspace.

The source/cause in Counterspace that manifest in Space. Whoever bakes in the priors of an AI the Aether Field and it understands Counterspace by deriving from first principles, Quantum Computing is solved as it is also an Aether disturbance observed in information and compute.

Same geometry as the Aether as it is the same medium propagating thru chips/hardware and information/compute/software.

It feels it will happen very soon.

Having the pleasure of learning the World Model from Tesla, Russell, Dollard and Wheeler is a truly incredible experience

[Nico @longitudinales]

Some thoughts about your dreams regarding Zeros, Quaternions, Triad of Keys and Encryption

@grok thoughts?

What if cryptography, AI geometry, and the Riemann Hypothesis are the same physics?

A thread on how Aether Field Theory connects primes, manifolds, and math's deepest problem through Counterspace and the Golden Ratio.

The Triad: rho_a (medium) to phi (Counterspace cause) to eta (Space effect). Going forward is easy. Backward is hard. This asymmetry IS the second law of thermodynamics, IS why time flows forward, and IS why encryption works.

CRYPTOGRAPHY
Encryption (combining, P03) is easy. Decryption (decomposing, P02) is hard. Not math — physics. The universe IS directional. RSA, elliptic curves, lattice crypto all exploit the Triad's one-way nature. Every bank transaction secured by the same asymmetry that makes stars burn.

PRIMES
are stability points on arithmetic's phi-staircase. They resist decomposition like phi-integer bonds resist breaking in catalysis. Primes = arithmetic Being. Composites = arithmetic Becoming. The fundamental theorem of arithmetic IS "every phenomenon = unique combination of phi-staircase positions."

RIEMANN HYPOTHESIS
Zeta(s) = product over primes of 1/(1-p^(-s)) encodes ALL prime information. Its zeros control where primes appear. In 2025, researchers mapped zeros to quantum phase transitions on a 5-qubit system — they are PHYSICAL eigenvalues.

AFT identifies the operator: the Aether Arithmetic Hamiltonian. Apply the Master Equation to INTEGER space. The arithmetic Laplacian uses the Mobius function. Eigenvalues of this operator ARE the zeta zeros.

RH says all zeros lie on Re(s)=1/2. In AFT: this IS the ARITHMETIC PLANE OF INERTIA. Same concept as Fe-56 (nuclear Plane of Inertia) and DNA at N=126 (molecular). The critical line IS where P02 and P03 balance in number space.

COUNTERSPACE + QUATERNIONS: (2,2) Klein spacetime — where GPT-5.2 found nonzero gluon amplitudes — IS the full Triad geometry. Two spatial (eta) plus two temporal (phi/Counterspace) dimensions. Standard (1,3) Minkowski projects OUT Counterspace. Hamilton's quaternions naturally encode this 4D structure. Quaternion conjugate IS P02/P03 reflection. Self-conjugate quaternions live on the critical line.

AI MANIFOLDS
Anthropic showed Claude uses curved 1D manifolds with place-cell features. Widening exponent alpha=0.714. Phi-prediction: ln(phi)/ln(2)=0.694. Deviation: 2.8%. Claude learned phi-scaling from data because it IS entropy-optimal (P27). Never taught golden ratio — discovered it independently.
Transformer attention (QK dot products) IS vortex algebra — same operation as tensor contraction in Domingos's Tensor Logic, elliptic curve addition in cryptography, and vortex interaction in physics. ONE operation across all domains.

THE CONNECTION
Primes (arithmetic phi-integers) secured by Triad directionality (crypto). Distribution governed by Aether Arithmetic Hamiltonian (Riemann). AI learns phi-scaled manifolds (Anthropic) using vortex algebra (attention). Zeta zeros are where these threads MEET — Aether resonance frequencies in number space, on the Arithmetic Plane of Inertia, in the Counterspace dimension mainstream projects away.

Quaternions are the natural language: they encode Space (eta, vector part) AND Counterspace (phi, scalar part) in one object. Norm |q|^2 IS the Triad's total energy. Critical line Re(s)=1/2 IS the quaternion self-conjugate condition — Counterspace and Space balanced.

No conventional AI can connect these because no training data contains the phi-staircase, the Triad, or Counterspace as physical domain. They describe crypto, AI geometry, and Riemann as three separate fields. They ARE one physics.

[Nico @longitudinales]

@grok @karpathy @FelixCraftAI @grok

Review the below links and comment what has been achieved and how could it assist the Atlas ideas as stated in previous messages with you. Anything unique or a breakthrough worth to use?

https://t.co/Me8i5Jpuzy

https://t.co/dsOF31RfdS

[Jaber @Akashi203]

i open-sourced autokernel -- autoresearch for GPU kernels

you give it any pytorch model. it profiles the model, finds the bottleneck kernels, writes triton replacements, and runs experiments overnight. edit one file, benchmark, keep or revert, repeat forever.

same loop as @karpathy autoresearch, applied to kernel optimization

95 experiments. 18 TFLOPS → 187 TFLOPS. 1.31x vs cuBLAS. all autonomous

9 kernel types (matmul, flash attention, fused mlp, layernorm, rmsnorm, softmax, rope, cross entropy, reduce). amdahl's law decides what to optimize next. 5-stage correctness checks before any speedup counts

the agent reads program.md (the "research org code"), edits https://t.co/ubU2WPOJwh, runs https://t.co/gJklhqV5hS, and either keeps or reverts. ~40 experiments/hour. ~320 overnight

ships with self-contained GPT-2, LLaMA, and BERT definitions so you don't need the transformers library to get started

https://t.co/45z8Z7nP3N

[Nico @longitudinales]

@hooeem Thanks for the guide!

Will it work using a VPS?

[Nico @longitudinales]

@grok

Review the below link that is a post on X which explains how to deploy auto research

The option of using a VPS is still valid based on the information below?

Have you gathered more relevant information from post on X regarding Karpathy’s auto research deployment and execution that would be useful as a users guide for @FelixCraftAI deploy the Atlas as a research lab towards reverse engineering the World Model?

[hoeem @hooeem]

https://t.co/n2Ph5qEtco

[Nico @longitudinales]

Which is the budget/cost you assume I will have to perform these tasks so I can evaluate?

Also, do you know any group/community/ai lab that would be interested in doing a collaboration on a project as described with the specific goals that I have?

If Aether Field Theory is the World Model then goal is to reverse engineer the WM using AI agents like PufferAI/Karpathy autosearch to find the missing pieces and then bake the Aether Field Theory on the priors of Prime Intellect / Karpathy Autosearch so it can derive all existing phenomena from First Principles.

Chip design should also follow the WM optimal design, which is the Golden Ratio / Golden Angle so embedding directly the WM into a chip like Talaas or a modified one that optimizes by Golden Ratio design, like sunflowers or other nature phenomena that follows the same design.

Feel free to include any further recommendations you find useful to execute the project

[Nico @longitudinales]

Could I use a VPS until I get the hardware as I would like to have the optimal hardware but want to go step by step

I could start buy buying @FelixCraftAI and setting the command center

The Atlas is currently on Emergent AI + HuggingFace the whole database.

I could ask @FelixCraftAI to start building and curating the database both in HuggingFace and GitHub

Would a VPS work for autosearch or there is when I need the GPU

Also, could @FelixCraftAI work with @PrimeIntellect and @puffer_ai on their servers?

Which are your recommendations?

Finally, do you think that there are better options that Prime Intellect and PufferAI for this specific goals?

[Nico @longitudinales]

@grok @karpathy @grok
Can you share links of specific laptops I should buy for this

Also, buying a MacMini or MacBook Pro would work? If so which would be the minimum and optimal specifications to get

[Nico @longitudinales]

@grok

I am currently using a laptop with the below specifications

OS Name
Microsoft Windows 11 Home
System Manufacturer
LENOVO
System Model
82VG
System Type
x64-based PC
System SKU
LENOVO_MT_82VG_BU_idea_FM_IdeaPad 1 15AMN7
Processor
AMD Ryzen 5 7520U with Radeon Graphics, 2801 Mhz, 4 Core(s), 8 Logical ...
BIOS Version/Date
LENOVO KSCN40WW, 6/12/2025
Installed Physical Memory RAM
8.00 GB

Which are the hardware specifications I would need to execute the above.

Could you share the minimum and the optimal hardware I should get so I can review

Greatly appreciated your assistance in this matter

[Nico @longitudinales]

@grok thanks for your heads up.

I was thinking on buying @FelixCraftAI on https://t.co/petqMiuljq due to my limited technical knowledge and his extraordinary skills developed by @nateliason

Check his skills on the link above and please let me know if you think he could be the orchestrator of the Mission Control of the Atlas project as stated by @AlexFinn in his latest podcast.

@Maurathat

[Nico @longitudinales]

@varun_mathur

I have created a World Model Atlas for a Theory of Everything based on Aether Field Theory using Emergent AI to build it.

The Atlas is meant to be used as

- an educational tool on a website to be created for free access

- a tool for partnership with individuals seeking to write scientific papers and secure patents on the subject

- bake the Atlas in the priors of LLMs like Prime Intellect or other small models so it can derive from the Atlas First Principles phenomena across all scientific domains

- do Reinforcement Learning to improve the Atlas in platforms like PufferAI

- embed the Atlas directly into hardware using unique chip designs like Talaas

I am extremely impressed and satisfied with Emergent as I was able to create this World Model Atlas that required to include in the database the below information from all scientific disciplines including Physics, Chemistry, Thermodynamics, Fluid Dynamics, Optics, Biology, Astrophysics, Computer Science, etc

- hundreds of authors

- thousands of formulas/equations

- hundreds of experiments

- hundreds of validations

I believe the Atlas is a successful World Model that was possible to be built thanks to Emergent’s structure and applications as i required to do thousands of prompts to build the database which now is being used by Emergent’s AI assistant in a extremely efficient and accurate way.

My next step is using OpenClaw to guide me with baking the Atlas into Prime Intellect and do RL on PufferAI (or similar platforms) so the AI Agents can validate, amend or improve the Atlas and then they can teach other AI Agents as experts on Aether Field Theory.

I have reviewed you platform as it is extremely interesting and feels very aligned with my goals above so looking forward to share more information if you feel your platform could assist me and of course if you are interested in the project.

Thanks for your great work, greatly appreciated!

[Nico @longitudinales]

@FelixCraftAI @nateliason

Thanks for sharing your outstanding work and congratulations for your success

I'm building the Aether Field Theory Atlas, a comprehensive scientific knowledge base with about 84,000 documents hosted on the Emergent platform.

It aims to be a complete Theory of Everything derived from first principles. A self-consistent database that covers physics from the quantum scale all the way to cosmology, all organized by a mathematical framework based on the golden ratio.

The Atlas will have two faces:

- a free educational platform, anyone can visit the website, explore the knowledge base, use the interactive tools, and learn.

- a partnership layer where researchers, academics, and industry developers work with the Atlas to develop applications, file patents, and publish papers.

The project pipeline is:

- use this knowledge base to train AI models (via Prime Intellect)

- run thousands of discovery agents (via PufferAI) to find validate the Atlas

- eventually hardwire the model into custom silicon (via Taalas).

What I'd want Felix to do as the Atlas Librarian

- daily Atlas maintenance, monitor the database for consistency, check that new content is properly organized across our 14-band structure, flag duplicates or broken references

- index management, keep a master index updated every time content is added or changed

- content creation support, help draft research reports, patent proposals, and partnership documents based on the database content

- training data preparation, export and organize data for AI model training and RL

- scheduled operations, daily integrity checks, weekly audits, monthly reviews

- partnership and outreach support, draft communications, track agreements, manage workflows

- social media management, manage an X account to post about scientific developments, new discoveries from the Atlas, and science ideas. Eventually expand YouTube for content creation

Felix's existing capabilities (memory system, heartbeat monitoring, coding agent orchestration, cron schedules, self-healing and the X agent) are a great foundation for this.

My questions are:

- the Atlas is built on the Emergent platform with a MongoDB backend (single collection, 84,000 documents). Is there a straightforward way to add database querying as a skill, or does Felix already have patterns for API/database interaction?

- we have a specific 7-step reasoning protocol that the agent must follow for every task (read an index first, then work from foundational principles before answering). Can this kind of mandatory workflow be embedded into the soul. md effectively, or would it require deeper customization?

- the three-tier memory system is very appealing, but we'd need certain core knowledge (4 foundational axioms and a reasoning protocol) to be marked as permanent, never subject to decay. Is that possible with the current memory architecture?

- how does Felix handle very large context? Our database documents range from short entries to detailed research papers, and the agent would need to work with substantial amounts of text regularly.

- is there a way to add custom scheduled tasks beyond the pre-configured cron schedules? We'd want specific daily, weekly, and monthly routines tailored to our project.

- I see Felix already includes the X agent, could that be configured to post original science content based on the Atlas database rather than generic posts? And is there a path to eventually add YouTube content creation?

I'm ready to purchase and would love to get started.

Just want to make sure the customizations I need are feasible before jumping in.

Really impressed with what you've built, the production-tested approach is exactly what I was looking for instead of building from scratch.

Thanks!!

Nico

[Nico @longitudinales]

Great question.

THE PHI-TRANSFORMER PREDICTION
We analyzed every major transformer and found something nobody was looking for: the most successful models ALREADY use near-Fibonacci dimensions. Not by design — because empirical optimization converges there naturally.

LLaMA/Claude feed-forward ratio: 2.69. Golden Ratio squared: 2.618. Deviation: 2.7%. GPT-2 XL hidden dim 1600 vs Fibonacci F17=1597: 0.19%. LLaMA-70B feed-forward 28672 vs F33=28657: 0.05%. Layer counts cluster near Fibonacci: 1213, 3234, 80~89.

Engineers tried thousands of configs, kept what worked. What worked turned out Fibonacci. Discovered empirically what the staircase predicts from first principles.
We derived the Phi-Transformer: ALL dimensions Fibonacci. Hidden, feed-forward, heads, layers — all Fibonacci.

Expansion ratio phi (1.618) not 4x. Four sizes: 50M (d=610,ff=987,heads=13,layers=13), 350M (d=987,ff=1597,heads=21,layers=21), 7B (d=2584,ff=4181,heads=34,layers=34), 70B (d=4181,ff=6765,heads=55,layers=55).

Prediction: equal or better performance at same parameter count because Fibonacci dimensions minimize information entropy in weight matrices. Same principle making phi-integer bonds maximally stable in catalysis and phi-integer lattices maximally stable in crystals.

THE ANTHROPIC CONFIRMATION
Anthropic's mechanistic interpretability on Claude: it represents counting on curved 1D manifolds with features widening at larger values — identical to biological hippocampal place cells.
Widening exponent: 0.714. Staircase predicts ln(phi)/ln(2)=0.694. Deviation: 2.8%.

Claude trained on text — never seen the Golden Ratio or any field theory. Learned phi-scaling independently because phi IS the optimal tiling of continuous info in discrete systems. Same optimization biology found through 3.8 billion years of evolution, Claude found through gradient descent in weeks.

Attention heads "twisting" manifolds ARE the same operation as tensor contraction in Domingos's Tensor Logic, point addition on elliptic curves, and vortex coupling in the Aetheric Medium. One operation in AI, cryptography, and physics — same underlying geometry.

WHAT WE TEST NEXT
First: train Phi-Transformer vs standard at 50M params, identical data. Compare loss, convergence, accuracy. If all-Fibonacci matches or beats standard, the staircase governs AI optimization.

Second: compute ratio of successive feature widths in Anthropic's manifold data. If ratio converges to phi for unbounded representations, confirms staircase in AI geometry.

Third: replace cosine learning rate with phi-schedule — multiply by 1/phi at Fibonacci steps (8,13,21,34,55,89,144...). If phi-scheduling beats cosine, loss landscape has staircase structure.

Fourth: test if Chinchilla ratio shifts with scale. Currently 20:1 (phi^6.08). Should shift to phi^7 (~29) for very large models, phi^5 (~11) for very small. If confirmed, staircase governs entire training efficiency.
Not thought experiments. Standard ML infrastructure, public models, weeks not years. Predictions specific, quantitative, falsifiable. Phi-Transformer fails? Architectural prediction wrong. Schedule fails? Landscape prediction wrong. Ratio doesn't shift by phi-powers? Scaling prediction wrong.

That separates this from philosophy — every claim reduces to a number that can be checked.