Speak at Ray Summit!

Christina@cszhu.dev · last yr.

have you ever wanted to speak at an AI conference? :) 📢 The CfP for Ray Summit 2025 San Francisco is open, and we'd love to have you submit a talk on anything and everything ML + AI + distributed computing! first time speakers are welcome 🫶 www.anyscale.com/blog/ray-sum...

DeepSeek released smallpond, a big data processing framework built on top of Ray. - Smallpond targets high performance data processing. - It provides a high-level dataframe API - Targets petabyte-level scaling The challenges around training data prep only grow when you include multimodal data.

Amazon published this only 4 months ago, but it feels like an eternity. It's one of the most impressive large-scale data processing migration efforts. Rare to see companies truly achieving order of magnitude cost improvements (while simultaneously increasing scale). aws.amazon.com/blogs/openso...

Amazon’s Exabyte-Scale Migration from Apache Spark to Ray on Amazon EC2 | Amazon Web Services

Large-scale, distributed compute framework migrations are not for the faint of heart. There are backwards-compatibility constraints to maintain, performance expectations to meet, scalability limits to...

aws.amazon.com

Talked with John Schulman last year about the ChatGPT backstory and scaling laws 😍 John co-founded OpenAI and created ChatGPT. www.youtube.com/watch?v=6Ctv...

ChatGPT Creator John Schulman on OpenAI | Ray Summit 2023

YouTube video by Anyscale

youtube.com

A good overview of the fundamentals of how to extend context windows for LLMs (if you care about RAG, you probably care about context lengths).

Fine-tuning LLMs for longer context and better RAG systems

Based on the popular “Needle In a Haystack” benchmark and RAG, we share our process of creating a problem-specific fine-tuning dataset to extend the context of models to build better RAG systems.

anyscale.com