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Richard A Aragon

TuringsSolutions

https://www.turingssolutions.com

AI & ML interests

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Articles

The Myth of Running Out of Data: Why Infinite Math Makes AI Training Limitless

Aug 8

• 1

Simulating Monte Carlo Algorithms With Gaussian Probability

Jul 29

• 1

Utilizing Gaussian Probability Space to Simulate Monte Carlo Algorithms with Particle Swarm Optimization

Jul 27

Navigating Complexity with Elegance: The P-FAF Approach to Fractal Word Embeddings

Feb 22

Humor Understanding Multi-task Optimization & Ranking

Feb 9

• 1

Probabilistic Fractal Activation Function (P-FAF) and Its Advantages Over Traditional Word Vectorization

Feb 8

• 5

Organizations

Posts 24

Post

I built a Hyper Dimensional Computing (HDC) Encoder and Decoder and I also built out all of the code needed to replace the Encoder and Decoder of a Llama model with this HDC model, then train the Llama model on the HDC Encoder/Decoder. All MIT licensed. Here is a video where I break it all down. I can answer any questions about this project or help anyone out where I can. I am not a super developer or anything and I don't have access to enough compute to train this on a large dataset: https://youtu.be/4VsZpGaPK4g

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1047

Ever wondered how neural networks actually work under the hood?

In my latest video, I break down the core mathematical concepts behind neural networks in a way that's easy for IT professionals to understand. We'll explore:

- Neurons as logic gates
- Weighted sums and activation functions
- Gradient descent and backpropagation

No complex equations or jargon, just clear explanations and helpful visuals!

➡️ Watch now and unlock the mysteries of neural networks: https://youtu.be/L5_I1ZHoGnM

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