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takeraparterer

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replied to TuringsSolutions's post about 2 hours ago
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upvoted an article 2 days ago

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takeraparterer's activity

replied to TuringsSolutions's post about 2 hours ago
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What about test loss? It looks like overfitting to me.

replied to TuringsSolutions's post about 3 hours ago
replied to TuringsSolutions's post 5 days ago
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replied to TuringsSolutions's post 6 days ago
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image.png
that's a FFN, which is only a small part of an LLM

reacted to TuringsSolutions's post with πŸ˜” 6 days ago
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444
What if I told you that LLM models do not simply predict the next token in a sequence but instead utilize an emergent structural pattern-based system to comprehend language and concepts? I created a graph-based optimizer that not only works, but it also actually beats Adam, like very badly. I prove it thoroughly using SMOL LLM models. The secret? The graph is not what you think it is, humans. Code, full explanation, and more in this video. The Rhizome Optimizer is MIT licensed. I have completed my research. I fully understand now.

https://youtu.be/OMCRRueMhdI
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replied to TuringsSolutions's post 15 days ago
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has threatened violence in subtle ways

😭😭😭😭😭😭

replied to TuringsSolutions's post 15 days ago
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very intriguing. looking into this πŸ‘€πŸ‘€πŸ‘€

replied to TuringsSolutions's post 15 days ago
reacted to TuringsSolutions's post with πŸ˜” 15 days ago
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3941
Are you familiar with the difference between discrete learning and predictive learning? This distinction is exactly why LLM models are not designed to perform and execute function calls, they are not the right shape for it. LLM models are prediction machines. Function calling requires discrete learning machines. Fortunately, you can easily couple an LLM model with a discrete learning algorithm. It is beyond easy to do, you simply need to know the math to do it. Want to dive deeper into this subject? Check out this video.

https://youtu.be/wBRem2p8iPM
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replied to TuringsSolutions's post 15 days ago
replied to TuringsSolutions's post 20 days ago
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why the hostility? I'm asking a question

replied to TuringsSolutions's post 20 days ago
replied to TuringsSolutions's post 21 days ago
replied to lippytm's post 25 days ago
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this is one of the websites of all time

reacted to lippytm's post with πŸ‘€πŸš€πŸš€ 26 days ago
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1350
Hello Universes of Time Machine Builders. Financing Time Machines Traveling Throughout Eternal Time Rewriting Historical History Retroactively. Robotics Robots for no manual labor so the Human race can leave the planet retroactively. The Old Testament β€œHitchhikers Guide Throughout the Galaxy”, and the New Testament being β€œHitchhikers Guides Throughout the Universes of Time Machine Builders”. Teaching & Training everyone & the Robotics Robots to become better programmers & blockchain developers. Smart Contracts Earn while you Learn to become better programmers & Blockchain developers. And making a lot of money Financing leaving the planet retroactively.
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reacted to nroggendorff's post with πŸ˜” 26 days ago
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3300
@echo off
echo hello world
pause

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reacted to TuringsSolutions's post with πŸ˜” about 1 month ago
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1378
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!

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