• 12 Posts
  • 16 Comments
Joined 3 years ago
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Cake day: March 24th, 2022

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  • I would much rather recommend you to find words to learn instead of characters, since this will actually let you understand the characters a lot better. Learning the words and the characters they are made out of will help you map the underlying meaning of the characters a lot better, since characters in themselves are hard to define using english words. Take for example “面” which if you look it up in a dictionary will be translated as: surface, flour, noodles, aspect, side. The meaning of this character will depend on what characters it is used in conjunction with, and so how will you be able to understand which of these meanings it has if you don’t know the words and grammar?

    Also, I would strongly recommend that you start with focusing on listening instead of reading, since this will help you develop a better accent and it will make learning the characters a lot more effortless.

    Additionally, understanding comments on social media is actually kind of an advanced skill, since you need a very good understanding of the culture and references.







  • First off, as someone who has programmed GPT stuff since way before ChatGPT, we don’t even need to train our own model. That is overly expensive and unnecessary for our purpose. What is much smarter to do in this case is to take all of the Marxist works and let a chatbot access the contents of the works using semantic search. The way we do this is to convert the works into small chunks which we then convert into embedding vectors. When the user sends a message to the chatbot, the message and the context of the message will be converted into an embedding vector. We then run a dot-product between the message of the user and the chunks of the texts in order to find the most relevant chunks to the question which the user has asked. Then a pre-trained model can make use of the information fetched in order to answer the user’s question.

    Of course, training one’s own model can be good if we want it to be even more accurate and familiar with the material, however a good starting point would be to use semantic search.