Optimized AI Workloads on Anyscale with RayTurbo
Discover how Ray optimizes AI workloads across diverse computing environments in this 40-minute conference talk. Explore Ray's evolution from a 2016 research project to a widely adopted framework used by leading AI organizations. Learn about Anyscale's A…
Introduction to Model Deployment with Ray Serve
Learn to deploy ML models using Ray Serve. Explore Ray Core APIs, create scalable architectures, and integrate with MLflow and FastAPI. Gain hands-on experience in distributed computing and model deployment.
Anyscale's Governance Suite for Scalable AI Platforms - Ray Summit 2024
Explore Anyscale's Governance Suite for AI platforms, addressing security, controls, and productivity challenges in the era of Generative AI. Gain insights into sustainable AI practices for modern enterprises.
Roblox's Journey to Supporting Multimodality on vLLM - Ray Summit 2024
Explore Roblox's integration of multimodal language models into vLLM, uncovering technical challenges and insights for developers seeking to enhance their LLM deployments with advanced AI capabilities.
Faster Model Serving with Ray and Anyscale - Ray Summit 2024
Explore Ray Serve's capabilities for distributed model serving and deployment, focusing on Anyscale's solutions for large-scale AI models and the challenges of building AI applications in the era of generative AI.
Scaling Inference Deployments with NVIDIA Triton Inference Server and Ray Serve
Explore the integration of Ray Serve and NVIDIA Triton Inference Server for enhanced ML model performance and scalability. Learn to optimize inference deployments using advanced tools and a new Python API.
Handshake's Approach to Content Tagging with vLLM and Anyscale
Explore Handshake's journey in implementing vLLM-based content tagging using Anyscale, enhancing job feed performance and addressing growing LLM requirements through innovative internal tools and methodologies.
Accelerated LLM Inference with Anyscale - Ray Summit 2024
Dive into Anyscale's latest LLM enterprise features and open-source contributions. Explore advancements in vLLM, including FP8 support and speculative decoding, doubling throughput and latency efficiency for improved inference performance.
Anyscale's Vision and Ray AI Compute Engine - Future of AI Scaling
Discover Anyscale's vision for AI scaling with Ray, the AI Compute Engine. Explore cutting-edge solutions tackling AI workload management challenges, from compiled graphs to advanced governance suites.
Transforming the Physical World with AI - Samsara's Journey in Fleet Management Technology
Explore how Samsara leverages Ray and Anyscale to revolutionize AI in fleet management. Discover the impact of AI across their entire pipeline, from training to deployment, and its transformative effects on physical operations.
From Data Engineering to MLOps: Building a Scalable ML Platform - Reverb's Evolution
Discover how Reverb transformed their data engineering team into MLOps, exploring scalable ML platform development, developer experience optimization, and effective monitoring strategies using Ray and Anyscale.
GenAI for Enterprises - Practical Considerations From Pilot to Scale
Explore practical considerations for implementing GenAI in enterprises, from pilot to scale. Address challenges and learn successful approaches for large-scale AI deployment.
Real-Time Vectorization for Transactional Workloads with MongoDB Atlas and Anyscale
Explore real-time vectorization for transactional workloads using MongoDB Atlas and Anyscale, liberating data and enabling innovation with advanced models at scale.
Running ML Workloads with AWS Purpose-Built ML Accelerators and Ray
Discover AWS Trainium and Inferentia ML accelerators for high-performance, cost-effective Generative AI in the cloud. Explore native support for these accelerators in Ray.
Production RL and Decision-Making with RLlib
Learn to implement production-ready reinforcement learning and decision-making systems using RLlib, exploring real-world applications, challenges, and best practices.
Managed Cloud Infrastructure for LLMs
Explore solutions for LLM infrastructure challenges, including cost reduction, GPU availability, scalability, and cloud resource management. Learn to accelerate AI development and deployment.
OneDigital ML Platform: Unleashing the Power of Machine Learning at Scale
Explore OneDigital's journey in building a scalable ML platform using Ray and Anyscale. Learn about architecture, strategies, and retail use cases for advanced ML models.
Scaling AI Health Assistants: Challenges and Solutions
Explore challenges and solutions in scaling AI health assistants, focusing on model management, state persistence, and system reliability. Learn key principles for building scalable AI products using Ray.
Lessons From Fine-Tuning Llama-2
Explore insights from fine-tuning Llama-2 for specialized applications. Learn setup, infrastructure, and efficiency techniques to outperform GPT-4 in specific scenarios using Anyscale and Ray.
Developing and Serving RAG-Based LLM Applications in Production
Learn to develop, evaluate, and scale RAG-based LLM applications for production, including advanced topics like hybrid routing to bridge the gap between open-source and closed LLMs.
Scalable Evaluation and Serving of Open Source LLMs
Explore challenges and solutions for serving open-source LLMs in production, focusing on scalable evaluation and deployment strategies.