Semanlink - YouTube AND Transformers

nicknochnack/LangchainDocuments: Leveraging Your Own Documents in a Langchain Pipeline

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2023-05-14 About

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- Intelligence has emerged: why? how?
- Let's study this with *controlled experiments* and *toy models*
- Clean and clear insights that peer slightly behind the magic curtain

emergence; rise of scale. Phase transition: fct(compute time for training: nb of params, dataset size)

(12:25) Transformers: the jump when compared to traditional NN: instead on oparating on single input X, operates on a set of inputs. (cf. training to say whether an image contains 2 elements of the same kind). **The aptitude to compare elements in the input sequence enables analogies** - the essence of reasoning.(Classical NN treats one high dimensional vector, tranformers hanlde sets of vectors. Attention layer replaces learned filters W of classical NN by the other elements in the sequence. Attention module compares part of input against other part of input. "Relative machines rather than absolute". Sets are a very powerful level of abstraction)

emergence
> The truth is that nobody has a clue what is going on"
>
> "**Something unknown is doing we don't know what**" (A. Eddington)

being inspired by physics' methodology: controled experiments and toy mathematical models

2023-03-28 About

Mat Kelcey : The map interpretation of attention - YouTube

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2022-10-24 About

Perspectives on knowledge acquisition & mobilization with neural net - Hugo Larochelle - CoLLAs 2022 - YouTube

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2022-09-17 About

Unveiling Transformers with LEGO - YouTube

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2022-06-30 About