ZenML 0.80.0 transforms tenant structures into workspace/project hierarchies with advanced RBAC for Pro users, while enhancing tagging, resource filtering, and dashboard design. Open-source improvements include Kubernetes security upgrades, SkyPilot integration, and significantly faster CLI operations. Both Pro and OSS users benefit from dramatic performance optimizations, GitLab improvements, and enhanced build tracking.
Streamline your machine learning platform with ZenML. Learn how ZenML's 1-click cloud stack deployments simplify setting up MLOps pipelines on AWS, GCP, and Azure.
OpenAI's Batch API allows you to submit queries for 50% of what you'd normally pay. Not all their models work with the service, but in many use cases this will save you lots of money on your LLM inference, just so long as you're not building a chatbot!
On the difficulties in precisely defining a machine learning pipeline, exploring how code changes, versioning, and naming conventions complicate the concept in MLOps frameworks like ZenML.
Exploring the evolution of MLOps practices in organizations, from manual processes to automated systems, covering aspects like data science workflows, experiment tracking, code management, and model monitoring.
Today, we're back to LLM land (Not too far from Lalaland). Not only do we have a new LoRA + Accelerate-powered finetuning pipeline for you, we're also hosting a RAG themed webinar.
Context windows in large language models are getting super big, which makes you wonder if Retrieval-Augmented Generation (RAG) systems will still be useful. But even with unlimited context windows, RAG systems are likely here to stay because they're simple, efficient, flexible, and easy to understand.
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