Is Meta open-sourcing AI models actually a strategic move to kill the model laye

<!-- SC_OFF --><div class="md"><p>Chinese labs seem way more willing to release open-weight models while the big US labs keep everything closed.</p> <p>My theory is that if

<!-- SC_OFF --><div class="md"><p>Another signal that the AI race is no longer about models — it’s about control.</p> <p>Muse Spark from Meta Platforms, Inc. marks a turning point

<table> <tr><td> <a href="https://www.reddit.com/r/ChatGPT/comments/1t6vy7j/the_80_billion_backlog_q1_2026_showed_ai_demand/"> <img alt="The $80 Billion Backlog: Q1 2026 Showed AI

<!-- SC_OFF --><div class="md"><p>I’m trying to understand why models from major labs (GPT, Claude, etc.) dominate real-world usage? You might say it's due to the expensive

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1v2bf3t/us_govt_lobbied_by_major_us_labs_is_about_to_ban/"> <img alt="US gov't lobbied by major US labs is

<!-- SC_OFF --><div class="md"><p>OpenAI CEO Sam Altman joined Alex Heath on the <em>Sources</em> podcast (Sept 2026) for a 1h 09m conversation unpacking why OpenAI paused a

Meta released Glimmer this week, an open-weight AI&#160;model&#160;anyone can download and run on their own hardware&#160;— a contrast to&#160;Muse&#160;Spark, the company’s more

<!-- SC_OFF --><div class="md"><p>Can someone explain this to me on a technical level? If open models were better in the first place why did everyone go out and built all these AI