Infrastructure challenges like high compute costs, GPU availability, scalability, and the burden of managing cloud resources slow down LLM and generative AI development. Anyscale provides the solutions to tackle these problems so our customers can focus on building and deploying high-performing custom models and applications. Our infrastructure powers our fast, cost-efficient, and scalable Anyscale Endpoints product. In this talk, you will hear about how we:
• Leverage all available GPU across different clouds to satisfy your compute needs
• Build intelligent features such as autoscaling and fully utilizing preemptible instances to cut cost
• Speed up instance start time to accelerate development cycle
• Manage compute, networking, storage and other cloud resources
Takeaways
• There is growing interest in self-hosting open source LLMs due to its flexibility, data privacy and cost-effectiveness, but it comes with challenges.
• Anyscale platform provides the solutions to the infrastructure challenges that come with self-hosting LLM, such as high compute costs, GPU availability, scalability, and the burden of managing cloud resources.
Find the slide deck here: https://drive.google.com/file/d/1g4F_6nnykgot1UQjU1vnHN6-oxDWCHnf/view?usp=drive_link
About Anyscale
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Anyscale is the AI Application Platform for developing, running, and scaling AI.
https://www.anyscale.com/
If you're interested in a managed Ray service, check out:
https://www.anyscale.com/signup/
About Ray
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Ray is the most popular open source framework for scaling and productionizing AI workloads. From Generative AI and LLMs to computer vision, Ray powers the world’s most ambitious AI workloads.
https://docs.ray.io/en/latest/
#llm #machinelearning #ray #deeplearning #distributedsystems #python #genai