DigestAI news desk

Cut through the AI noise.

Hardware & Compute1 min read

Adobe optimizes Photoshop, Premiere for NVIDIA’s RTX Spark platform

Adobe has rebuilt Photoshop, Premiere Pro, and Substance 3D Painter to run faster on NVIDIA’s RTX Spark platform. The company claims the apps are twice as fast for AI tasks and editing workflows, with real-time rendering and smoother performance for tasks like effects, color grading, and texturing. RTX Spark is NVIDIA’s new SoC designed for AI workloads on Windows laptops and small desktops,…

1 source

Key points

  • Adobe rebuilt Photoshop, Premiere Pro, and Substance 3D Painter for NVIDIA’s RTX Spark platform
  • Apps claim two times faster performance for AI tasks and editing workflows
  • RTX Spark targets creatives and developers, not enterprise users, with AI workloads

The updates aim to reduce latency and speed up heavy processes, such as applying effects in Photoshop or rendering in Premiere. Adobe’s VP Deepa Subramaniam emphasized the importance of performance for professionals like photographers, filmmakers, and designers, who rely on seamless workflows to focus on their creative output. The changes are part of Adobe’s broader push to leverage AI and hardware acceleration for creative tools.

Full story from engadget.com · by Mariella Moon · via Search: NVIDIAOpen source ↗

Adobe rebuilt Photoshop and Premiere for NVIDIA's RTX Spark platform

engadget.com · 14 October 2026

Loading the full article…

This text was published by engadget.com and written by Mariella Moon. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

Topics · follow one to build your own front page
AdobeNVIDIADeepa Subramaniam

The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

Comments

via GitHub Discussions

More in Hardware & Compute

All →

Related stories