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AI development cycle: Open-source benefits from model condensation

A Reddit user discusses the cyclical nature of AI development, comparing open-source and closed-source models. They highlight how open-source benefits from the 'condensation' phase (Step 3) of this cycle, where capabilities are shrunk into smaller models. The user notes the rapid progress in local AI video generation, referencing models like LTX-2.3 and comparing it to earlier benchmarks like Sora 1 and Veo 2, suggesting that current open-source models are performing comparably or better than previous SOTA models, especially considering audio capabilities. AI

IMPACT Provides insight into the rapid pace of AI development and the benefits of open-source contributions in model optimization.

RANK_REASON The item is a user-generated discussion on a subreddit about the general development cycle of AI models, not a primary announcement or research paper.

Read on r/StableDiffusion →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI development cycle: Open-source benefits from model condensation

COVERAGE [1]

  1. r/StableDiffusion TIER_2 English(EN) · /u/Radyschen ·

    To the people that ask why "new model isn't SOTA yet" (This was a comment but it took too long to write to be just a comment so here you go so I can feel like I didn't waste my time as much)

    <!-- SC_OFF --><div class="md"><p>The process in the development of AI is kinda like</p> <p>Step 1: Find an architecture that can do something</p> <p>Step 2: Brute-force scale that architecture with minor improvements so that it can do more</p> <p>Step 3: Find a way to condense t…