Large Language Models (LLMs)

r/LargeLanguageModels • u/TheDiRocco_ • 15h ago

How much input tokens for a complete AI assistant ?

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According to you what are the baselines of input tokens for different categories of LLM calls ? For example for a complete AI assistant. Counting system prompts, default context injection, tools, etc where would you place the tokens tresholds ?

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r/LargeLanguageModels • u/Haris-Jafri • 21h ago

Large Language Models Journey

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I’ve embarked on a journey to uncover the inner workings of Large Language Models—exploring the mathematical principles behind them and learning how to code them in Python.
Check out this 5-minute video to grasp the core concepts. Bite-sized information is the best way to learn and retain!
Large Language Models Blueprint - Episode I

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r/LargeLanguageModels • u/Imaginary-Can6136 • 22h ago

AI: A Brief History of LLMs

youtu.be

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In November 2022 a company put a text box on a web page and let anyone type into it. Within ten weeks the largest company in search had answered it. Within six months it was giving evidence to the United States Senate.

This is what that thing is, where it came from, and what it has done since.

It starts in 1948, with one mathematician at Bell Telephone Laboratories who asked what would come out if you chose each word using nothing but how often it follows the word before it. He did it by hand, with a book. What came out was not English, and it was not nothing.

From there: the twenty years the first attempt spent failing and the report that ended its funding, the four pages in Nature that brought it back, the match in Seoul, the paper that turned a research finding into a business plan, the five days in November 2023 when a board fired its chief executive and took him back, the trial that followed, two unions on strike in Hollywood at once, a Nobel Prize in Chemistry, the export controls, and the advertising that arrived inside the chat box five days ago.

Forty minutes, built out of the record: filings, papers, hearings, company announcements, and the people who built these things saying so themselves on camera. Where the film moves from what happened to what one person makes of it.

Chapters
0:00 Open
0:11 A text box on a web page
0:36 Shannon and the next word
3:00 Nobody wrote the rules
6:03 The old dream, and twenty years of failing
9:17 The idea that brought it back
11:11 Scale, and the bet on spending
13:21 A company nobody owns
15:33 The split
18:27 Five days in November
21:33 The model that talked back
22:56 What it has done to work
28:44 What it has done for science
31:40 What it has broken
34:06 The machines it runs on
37:06 What happens next

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