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You are here		www.primeintellect.ai State-of-the-art in Decentralized Training
\|	\|	anyscale-staging.herokuapp.com Components of an Open Source AI Compute Tech Stack	13.3 parsecs away Travel
\|	\|	Powered by Ray, Anyscale empowers AI builders to run and scale all ML and AI workloads on any cloud and on-prem.	13.3 parsecs away Travel
\|	\|	blog.paperspace.com Accelerating Large Language Models: The H100 GPU's Role in Advanced AI Development	12.6 parsecs away Travel
\|	\|	Explore the revolutionary capabilities of the H100 GPU, which plays a crucial role in shaping the future of AI.	12.6 parsecs away Travel
\|	\|	www.anyscale.com How ByteDance Scales Offline Inference with Multi-Modal LLMs	12.1 parsecs away Travel
\|	\|	ByteDance, the company behind Tiktok, leverages multi-modal models to enable many applications, such as text-based image retrieval or object detection.	12.1 parsecs away Travel
\|	\|	www.ethanrosenthal.com Time Series for scikit-learn People (Part II): Autoregressive Forecasting Pipelines \| Ethan Rosenthal	81.8 parsecs away Travel
\|		In this post, I will walk through how to use my new library skits for building scikit-learn pipelines to fit, predict, and forecast time series data. We will pick up from the last post where we talked about how to turn a one-dimensional time series array into a design matrix that works with the standard scikit-learn API. At the end of that post, I mentioned that we had started building an ARIMA model.	81.8 parsecs away Travel