RunPod’s new S3-compatible API lets you manage files on your network volumes without launching a Pod. With support for standard tools like the AWS CLI and Boto3, you can upload, sync, and automate data flows directly from your terminal — simplifying storage operations and saving on compute costs. Whether you’re prepping datasets or archiving model outputs, this update makes your AI workflows faster, cleaner, and more flexible.

VACE introduces a powerful all-in-one framework for AI video generation and editing, combining text-to-video, reference-based creation, and precise editing in a single open-source model. It outperforms alternatives like AnimateDiff and SVD in resolution, flexibility, and controllability — though character consistency and memory usage remain key challenges.

Runpod has a new look — and a sharper focus. Explore the redesigned site, refreshed brand, and the platform powering real-time inference, custom LLMs, and open-source AI workflows.

Learn how to build ethical AI—from bias and privacy to transparency and sustainability — using tools and infrastructure that support responsible development.

A deep technical dive into how the Runpod Hub streamlines serverless AI deployment with a GitHub-native, release-triggered model. Learn how hub.json and tests.json files define infrastructure, deployment presets, and validation tests for reproducible AI workloads.

The Runpod Hub is here—a creator-powered marketplace for open source AI. Browse, fork, and deploy prebuilt repos for LLMs, image models, video generation, and more. Instant infrastructure, zero setup.

From brainstorming essays to auto-tagging lecture notes, students are using AI in surprising and creative ways. This post dives into the real habits, hacks, and ethical questions shaping AI’s role in modern education.