AI, Quant 투자 공부

1. The Emergence of the LLM Tech Stack source: https://medium.com/better-programming/llm-tech-stack-is-appearing-and-i-like-what-am-seeing-debb4e3e33ea 2. State of LLaMA 2023/Q1 source: https://medium.com/better-programming/state-of-llama-2023-q1-663905c37a5e 3. Inside Generative Agents: Google and Stanford University’s Generative AI Method that Created Agents that Simulated Human Behavior sourc..

1. High-throughput Generative Inference of Large Language Models with a Single GPU source: https://arxiv.org/pdf/2303.06865.pdf 2. Deploying Large NLP Models: Infrastructure Cost Optimization source: https://neptune.ai/blog/nlp-models-infrastructure-cost-optimization 3. What Are Transformer Models and How Do They Work? source: https://txt.cohere.com/what-are-transformer-models/ 4. Efficient Tran..

1. The Complete Beginners Guide To Autonomous Agents source: https://www.mattprd.com/p/the-complete-beginners-guide-to-autonomous-agents? 2. Reinforcement Learning for Language Models source: https://gist.github.com/yoavg/6bff0fecd65950898eba1bb321cfbd81? 3. Navigating the High Cost of AI Compute source: https://a16z.com/2023/04/27/navigating-the-high-cost-of-ai-compute/?

1. AI 모델의 데이터를 다룰 때 발생하는 세 가지 문제 (Data! Data! Data!) source: https://www.upstage.ai/blog/business/why-is-data-labeling-important-for-ai 2. StableLM: Stability AI Language Models source: https://github.com/Stability-AI/StableLM?fbclid=IwAR3jtwsESYvHx5C5Q9Ru1VpU1lPG-akoZlxkTdtIhmvLkEgJrbKIV-XANZw 3. ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual..

1. Generative Agents: Interactive Simulacra of Human Behavior source: https://arxiv.org/pdf/2304.03442.pdf

1. Integrating ChatGPT with internal knowledge base and question-answer platform source: https://medium.com/singapore-gds/integrating-chatgpt-with-internal-knowledge-base-and-question-answer-platform-36a3283d6334 2. Transformer Taxonomy (the last lit reveiw) source: https://kipp.ly/blog/transformer-taxonomy 3. Generative Agents: Interactive Simulacra of Human Behavior source: https://arxiv.org/p..

1.Deploying Large NLP Models: Infrastructure Cost Optimization source: https://neptune.ai/blog/nlp-models-infrastructure-cost-optimization 2.Large Language Models and Two Modes of Human Thinking source: https://towardsdatascience.com/large-language-models-and-two-modes-of-human-thinking-1322160755e8 3.This is How to Stop ChatGPT, Bing, Poe, and You from Hallucinating source: https://pub.towardsa..

1. A Recipe for Training Large Models source: https://wandb.ai/craiyon/report/reports/Recipe-Training-Large-Models--VmlldzozNjc4MzQz? 2. 5 Lessons Learned from Adding ChatGPT to a Mature Product source: https://blog.trymito.io/5-lessons-learned-from-adding-chatgpt-to-a-mature-product/? 3. Training 175B Parameter Language Models at 1K GPU scale with Alpa and Ray source: https://www.anyscale.com/b..

1. How to estimate and reduce the carbon footprint of machine learning models source: https://towardsdatascience.com/how-to-estimate-and-reduce-the-carbon-footprint-of-machine-learning-models-49f24510880 2. Getting started with Generative AI: 4 ways to customize your models source: https://georgian-io.medium.com/getting-started-with-generative-ai-4-ways-to-customize-your-models-f6871b44cb6a 3. B..

1. LLaMA-GPT4All: Simplified Local ChatGPT source: https://medium.com/towards-artificial-intelligence/llama-gpt4all-simplified-local-chatgpt-ab7d28d34923 2. Neural Graph Databases source: https://towardsdatascience.com/neural-graph-databases-cc35c9e1d04f