RTX for Creators

Content creation has seen dramatic transformations over the decades, driven by advances in technology. The shift from linear to non-linear video editing in the 1990s revolutionized the industry, allowing creators to edit more flexibly. Fast-forward to the late 2010s, the advent of artificial intelligence (AI) brought yet another change—AI tools began automating many time-consuming tasks, such as the removal of objects in videos, once requiring frame-by-frame editing. This was just the beginning of AI's growing role in content creation.


As mentioned before, Blackwell adds FP4 (and INT4) support to the Tensor Cores. While this data format is half the precision, it also takes up only half the space, which means that some larger models can now fit into the GPU memory—previously a super-expensive enterprise card with bigger VRAM was required.

Technically the lower precision will result in slightly worse outputs, but that can be mitigated with longer training time, which is now possible, because the overall rate of processing is much higher.


Another key area where generative AI is having an impact is in image generation. Traditionally, creators had to rely on text descriptions to guide AI in producing images. This process can be imprecise, particularly when trying to describe detailed compositional elements. Now, a 3D scene can serve as a guide to help AI better understand spatial relationships between objects, resulting in more accurate and visually appealing outputs.


Video editors, in particular, are benefiting from advancements like the support for 4:2:2 video, which offers greater color depth and improved image quality. With 4:2:2, creators gain more accurate color representation and sharper edges, especially when working with green screens or fine text details. The downside of this format, however, is the larger file size. To address this, the new Blackwell GPU architecture provides better decoders, making it possible to play and edit high-quality 4:2:2 content without significant performance loss.


Thanks to enhancements in encoder and decoder technology in Blackwell, the GPU can now handle multiple 4K streams simultaneously. This is especially beneficial for those working in multi-camera setups, such as during podcasting or live event coverage. When a single stream is encoded, you can still get higher performance, because individual frames are processed in parallel by the encoders. Additionally, new encoding techniques offer up to 5% improvements in video quality, optimizing file sizes without sacrificing visual fidelity.


One area where creators have faced significant challenges is in live-streaming. The demands of live broadcasting—engaging with the audience, managing the stream, and ensuring high-quality production—can overwhelm even experienced streamers. However, new developments in AI are helping streamers manage these tasks more efficiently. Streamlabs, in collaboration with Vol AI, has introduced the Streamlabs Intelligent Streaming Assistant, an AI-powered co-host designed to assist with live-streaming tasks. This tool can handle various functions such as scene transitions, audio adjustments, and technical support, freeing up the streamer to focus on content creation. Currently in development, this AI assistant is set to be a game-changer for live streamers, reducing the complexity of live broadcasting.