Algorithmic Simplicity

Educational Youtube channel focusing on computer science.

[Algorithmic Simplicity @AlgorithmicSimp]

@dhtikna I'm working on the next one right now.

[Algorithmic Simplicity @AlgorithmicSimp]

@theheavensite @kurko @_yusufknl I am working on it right now.

[Algorithmic Simplicity @AlgorithmicSimp]

Fascinating read! I am honoured to see my video mentioned along side so many other great educators.

[William Taysom @wtaysom]

Wrote a letter/novella of three years of AI thoughts https://t.co/LOl2l04N4K presents a cross between science fiction and victorian "science" demonstration with the real, surreal, magically real, and magical all braided together with little comic skill and full earnestness.

[Algorithmic Simplicity @AlgorithmicSimp]

@KeviKiru Hello! Yes I am still around, just been busy with non-Youtube things. I am hoping to return soon though!

[Algorithmic Simplicity @AlgorithmicSimp]

Finally finished my explainer on why LLMs can in fact learn world models, and why larger neural nets generalize better than smaller ones (against all theoretical predictions) https://t.co/1vNisrgaMf

[Algorithmic Simplicity @AlgorithmicSimp]

@pedroth9 Great article! I wish I know about it when I was scripting my video, it would have made it a lot easier haha. I knew this derivation was too simple to not have been discovered before, but I couldn't find it anywhere. Hopefully it becomes more popular.

[Algorithmic Simplicity @AlgorithmicSimp]

I released my #SoMEpi entry: the simplest way to derive Taylor's polynomial. I haven't seen this derivation presented anywhere else before, and I think it's really neat, so I made it a video on it. After this I am back to machine learning content (Solomonoff induction next!)

[Algorithmic Simplicity @AlgorithmicSimp]

Link here: https://t.co/GVKiR3uw5a

[Algorithmic Simplicity @AlgorithmicSimp]

@GregBlue123 I am releasing a video for SoMEpi very shortly, but it's not machine learning focused. Next machine learning video won't be for some time.

[Algorithmic Simplicity @AlgorithmicSimp]

My latest explainer video on Mamba is out! Mamba is an exciting new neural net architecture that has the potential to replace transformers. Come learn how Mamba works from the basics. And don't worry, no state space theory required!

[🐚xtotem @0xtotem]

I get this question a lot, so here are some neat channels to learn more about ML and stay up to date:

Edu - https://t.co/tDOkvYrePJ by @AlgorithmicSimp
News - https://t.co/peaXStYWuM by @AiFlux
Goat - https://t.co/iQ3o108Ikx by @karpathy
Tutorials - https://t.co/RWs3dd1FdX

[Algorithmic Simplicity @AlgorithmicSimp]

@a_karvonen Thanks for the tip!

[Algorithmic Simplicity @AlgorithmicSimp]

My latest video on Mamba is out: https://t.co/kfk2PYGfhC

Come learn how Mamba outperforms transformers, no state space model theory needed!

[Algorithmic Simplicity @AlgorithmicSimp]

Video here: https://t.co/iIIPiO2NbI

[j j @mistymntncop]

@AvimanyuRoy3 I like @AlgorithmicSimp's video on the topic
https://t.co/bLXuhe8FQP

[Algorithmic Simplicity @AlgorithmicSimp]

@praveenkumar_92 For example, CNNs are usually justified by saying that they make the model translation invariant, but locally connected nets are NOT translation invariant, they only reduce the input dimension, and they perform just as well (e.g. https://t.co/FPPsNwFoWY).

[Algorithmic Simplicity @AlgorithmicSimp]

Just released a new video on how generative AI models work! Deep dive on auto-regression and diffusion and their advantages/disadvantages https://t.co/DV3Gizo8jY

[Algorithmic Simplicity @AlgorithmicSimp]

@praveenkumar_92 I was teaching the ML course at my university. I thought the lecture slides from previous years did a really poor job of justifying why these methods work, so I tried to make better ones. The actual process was a combination of reading lots of papers and experimenting myself.

[Adam Karvonen @a_karvonen]

Highly recommend @AlgorithmicSimp 's videos. He always provides a perspective that is more interesting/ unique than most other explanations.

[j j @mistymntncop]

Really appreciate @AlgorithmicSimp's ability to explain the big picture of how NN model's work. Other explanation's miss the forest for the trees.
https://t.co/bLXuhe8FQP