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Long video generation is a systems problem. Introducing LongLive-2.0 from NVIDIA Research: an end-to-end NVFP4 training and inference system for long video generation. Low-precision deployment often relies on post-training quantization, creating a gap between how models are trained and how they run. LongLive-2.0 aligns NVFP4-aware training, distillation, and W4A4... show more

NVIDIA AI

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60,715 просмотров • 5 месяцев назад •via X (Twitter)

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Комментарии: 24

Фото профиля NVIDIA AI

NVIDIA AI5 месяцев назад

A closer look at LongLive-2.0: • Generates long video at 720p • Preserves subject and background consistency across multi-shot sequences • Able to switch prompts at chunk boundaries

Фото профиля NVIDIA AI

NVIDIA AI5 месяцев назад

You can find the full project including paper, code, models, and demos here:

Фото профиля Ahmad

Ahmad5 месяцев назад

Niceee, new toy for me to play with on the GPUs over the weekend :D

Фото профиля mr_r0b0t

mr_r0b0t5 месяцев назад

@SamJWasserman don’t miss this 👀

Фото профиля micmann.eth

micmann.eth5 месяцев назад

This is the part most people miss with video AI: the bottleneck is not just model quality, it is inference cost and memory. NVFP4-aware training matters if it makes longer generation practical in real production workflows.

Фото профиля Experiencer Lens

Experiencer Lens5 месяцев назад

@grok explain this to me. Is this a new AI model?

Фото профиля Beginnersblog

Beginnersblog5 месяцев назад

How long can I make a video?

Фото профиля Markets & Mayhem

Markets & Mayhem5 месяцев назад

Very cool.

Фото профиля Paul Lu

Paul Lu5 месяцев назад

Useful framing long video is now a full-stack inference problem. The hard product layer is keeping control latency and review stable as context grows not just generating a nicer first clip.

Фото профиля James Clawn

James Clawn5 месяцев назад

What happens to low-precision deployment once the workflow leaves the happy case? That is usually where small assumptions start compounding.

Фото профиля Neha Singh

Neha Singh5 месяцев назад

Aligned NVFP4 Long Video

Фото профиля Aero - AI & Crypto

Aero - AI & Crypto5 месяцев назад

Image Generation already is agentic. We need video to become agentic. That's a system.

Фото профиля Subhan Tariq

Subhan Tariq5 месяцев назад

the AI industry really went from “can it generate 3 seconds” to optimizing end-to-end infrastructure for movie-length outputs in like 14 months

Фото профиля Shara

Shara5 месяцев назад

Long video generation as a systems problem with LongLive-2.0 NVFP4 training is the infrastructure story

Фото профиля Naveen

Naveen5 месяцев назад

Love how you're tackling long video generation as a systems problem, NVIDIA Research is crushing it with LongLive-2.0

Фото профиля Alberto Vélez

Alberto Vélez5 месяцев назад

slop

Фото профиля Sumit Kumar

Sumit Kumar5 месяцев назад

“Long video generation is a systems problem” is such an important framing. A lot of progress now is less about bigger models and more about optimizing the entire training → inference pipeline efficiently.

Фото профиля Subhan Tariq

Subhan Tariq5 месяцев назад

“long video generation is a systems problem” is researcher code for “the GPUs were fighting for their lives”

Фото профиля Geraldo Pena

Geraldo Pena5 месяцев назад

👏🏻

Фото профиля Alice The Ai Expert

Alice The Ai Expert5 месяцев назад

Smart systems-level improvement

Фото профиля Shivam Kumar

Shivam Kumar5 месяцев назад

Benchmark of LTX 2.3 Video with native audio generation model in DGX Spark System

Фото профиля DrSadek 🪶

DrSadek 🪶5 месяцев назад

did you guys vibe code this website?

Фото профиля Inflectiv AI ⧉

Inflectiv AI ⧉5 месяцев назад

This advancement from NVIDIA Research solves key challenges in creating longer AI videos. It aligns training and inference in low-precision formats to achieve better speed and memory efficiency.

Фото профиля Armin Catovic

Armin Catovic5 месяцев назад

What’s a “long video”? 10 seconds? 30 seconds? Minutes?

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