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Abekek Notes@abekek_notes P.797
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GPT-4 Will Be 500x Smaller Than People Think

Классный пост на тему каким будет GPT-4. Заметил много постов с инфографикой показывающей относительные размеры модели GPT-4 в сравнении с GPT-3 – полный треш по словам этого поста.

What GPT-4 Might Look Like:

To properly fit a model with 100T parameters, open OpenAl needs a dataset of roughly 700T tokens.
Given 1M GPUs and using the calculus from above, it would still take roughly 2650 years to train the model.

So, here is what GPT-4 could look like:
• Similar size to GPT-3, but trained optimally on 10x more data
• Multi-modal outputting text, images, and sound
• Output conditioned on document chunks from a memory bank that the model has access to during prediction
Doubled context size allows longer predictions before the model starts going off the rails

Regardless of the exact design, it will be a solid step forward. However, it will not be the 100T token human-brain-like AGI that people make it out to be.

https://www.reddit.com/r/learnmachinelearning/comments/10fw2df/gpt4_will_be_500x_smaller_than_people_think_here/
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GPT-4 Will Be 500x Smaller Than People Think

Классный пост на тему каким будет GPT-4. Заметил много постов с инфографикой показывающей относительные размеры модели GPT-4 в сравнении с GPT-3 – полный треш по словам этого поста.

What GPT-4 Might Look Like:

To properly fit a model with 100T parameters, open OpenAl needs a dataset of roughly 700T tokens.
Given 1M GPUs and using the calculus from above, it would still take roughly 2650 years to train the model.

So, here is what GPT-4 could look like:
• Similar size to GPT-3, but trained optimally on 10x more data
• Multi-modal outputting text, images, and sound
• Output conditioned on document chunks from a memory bank that the model has access to during prediction
Doubled context size allows longer predictions before the model starts going off the rails

Regardless of the exact design, it will be a solid step forward. However, it will not be the 100T token human-brain-like AGI that people make it out to be.

https://www.reddit.com/r/learnmachinelearning/comments/10fw2df/gpt4_will_be_500x_smaller_than_people_think_here/

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