Build a Better AI Homelab with Flyte

​Turn your AI homelab into a powerful AI experimentation and development platform with Flyte 2!

​I've spent the past year using Flyte to build and experiment with AI workloads on my NVIDIA DGX Spark, and now with Apple Silicon support, you can bring the same capabilities to your Mac or other local GPU hardware.

​In this hands-on session, I'll share real examples covering LLM fine-tuning, computer vision and VLMs, model serving, robotics simulation, image and video generation, AI agents, and more.

​We'll explore how Flyte makes local AI development easier with:

• ​Experiment tracking and reproducibility for training, evaluation, and inference

• ​GPU and environment management for local AI workloads

• ​Model serving with flexible scaling

• ​Flyte Reports for visualizing robotics simulations, comparing generated images and videos, and tracking model performance

• ​Durable execution with caching, retries, and failure recovery

• ​Remote UI for monitoring and managing experiments from anywhere

​Whether you're running an NVIDIA DGX Spark, an Apple Silicon Mac, or your own GPU server, see how Flyte brings powerful MLOps and AI orchestration capabilities to your homelab.

​Bring your own hardware. Flyte makes it better.