"Over the past year, AI-generated video diffusion models have enabled dramatic improvements in visual realism, as we've seen with OpenAI's Sora 2, Google's Veo 3, Runway Gen-4 and others. AI video generation is truly reaching an inflection point, and the latest models are capable of creating stunning clips with lifelike visuals. However, the way they're built prevents these models from being used interactively and in real time,"
"Our team at Decart decided to see if we could get around these obstacles, and LSD v2, our recently released model, validates this idea that achieving minimum latency is largely a matter of approach. To make it work, we developed and implemented a number of cutting-edge techniques, which we believe can be applied to various AI models. Using these techniques, we were able to optimize the underlying infrastructure needed to run our model and maximize GPU utilization,"
AI-generated video diffusion has recently achieved significant visual realism, producing lifelike clips. Conventional models generate video in sequential, computationally intensive chunks, creating latency that prevents interactive, real-time transformation of live camera input. Decart built LSD v2, a causal, auto-regressive model that produces frames instantly and continuously with no duration limits. The team optimized infrastructure to maximize GPU utilization and accelerated denoising to prevent error accumulation. Causal generation reduces computational load by producing each new frame based only on past frames. The applied techniques can be transferred to other AI video models.
Read at Techzine Global
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