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Ray in 2023 Robert Nishihara
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12x 50% 40% 10x 5x 30% Why Ray? faster cheaper cheaper cheaper faster cheaper
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As AI capabilities have grown, so have the challenges Scale Future readiness Cost These are the challenges Ray was built for
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Anyscale Endpoints - fine-tuning Llama-2-7B GPT-4 fine-tuned 86% 3% 78% Superior task-specific performance at 1/300th the cost of GPT-4!
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Spark SageMaker $0 $20 $40 $60 $3.5 $7.3 $57 AWS Cost to process 1M images $2.5 Batch inference - costs
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Anyscale Endpoints Cost efficient LLM inference Anyscale Endpoints Single GPU optimizations Multi-GPU modeling Inference server Autoscaling Multi-region, multi-cloud $1 / million tokens (Llama-2 70B)
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