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Anurag Bhagsain
@abhagsain
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Learner, Builder | Stan, Swing π§ Indie Hacker at heart π¨βπ» - https://t.co/KrubZa9okg - https://t.co/CeqiLH9QR8 - https://t.co/prsddki2t9
Himachal Pradesh
Joined March 2014
RT @kevinrwhitley: Working on an ultra-fast, ultra-tiny JS rate limiter. Currently 0(1) efficiency (read: as fast as it gets) and only ~16β¦
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@jerryjliu0 Can you guys make the pricing a little bit easier to understand? π
(Someone who wants to integrate LlamaParse into their AI product but doesn't want an unexpected bill or go bankrupt πββοΈ)
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@janwilmake 2yrs ago, I implemented the counter thing in KV and ignored DO (thanks to the name) but knew that KV is like cache, so we can use it π« Recently, I needed to implement a real-time thing, and that's when I started looking into DO
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I was going to watch Pushpa 2 on Netflix this weekend, but I guess it can wait
New 3h31m video on YouTube: "Deep Dive into LLMs like ChatGPT" This is a general audience deep dive into the Large Language Model (LLM) AI technology that powers ChatGPT and related products. It is covers the full training stack of how the models are developed, along with mental models of how to think about their "psychology", and how to get the best use them in practical applications. We cover all the major stages: 1. pretraining: data, tokenization, Transformer neural network I/O and internals, inference, GPT-2 training example, Llama 3.1 base inference examples 2. supervised finetuning: conversations data, "LLM Psychology": hallucinations, tool use, knowledge/working memory, knowledge of self, models need tokens to think, spelling, jagged intelligence 3. reinforcement learning: practice makes perfect, DeepSeek-R1, AlphaGo, RLHF. I designed this video for the "general audience" track of my videos, which I believe are accessible to most people, even without technical background. It should give you an intuitive understanding of the full training pipeline of LLMs like ChatGPT, with many examples along the way, and maybe some ways of thinking around current capabilities, where we are, and what's coming. (Also, I have one "Intro to LLMs" video already from ~year ago, but that is just a re-recording of a random talk, so I wanted to loop around and do a lot more comprehensive version of this topic. They can still be combined, as the talk goes a lot deeper into other topics, e.g. LLM OS and LLM Security) Hope it's fun & useful!
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RT @karpathy: New 3h31m video on YouTube: "Deep Dive into LLMs like ChatGPT" This is a general audience deep dive into the Large Languageβ¦
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