{
  "video_id": "reddit_1w8ra8c",
  "channel_slug": "singularity",
  "channel_handle": "r/singularity",
  "title": "Does Google Actually Believe LLM Scaling Won’t Lead to AGI?",
  "url": "https://www.reddit.com/r/singularity/comments/1w8ra8c/does_google_actually_believe_llm_scaling_wont/",
  "external_url": null,
  "upload_date": "20260906",
  "published_at": "2026-09-06T09:16:50+00:00",
  "transcript": "I have been thinking quite a bit about Google’s place in the AI race recently.\n\nDespite having enormous amounts of money, data, talent, and computing resources, none of Google’s models seem to have consistently pulled ahead of OpenAI or Anthropic at the frontier. What makes this even more interesting is that Google’s DeepMind researchers were among the authors of “Attention Is All You Need,” the landmark paper that introduced the Transformer architecture that underpins modern LLMs.\n\nSo how did Google, with all those advantages, end up seemingly playing catch-up,   even behind some Chinese AI labs in certain areas?\n\nIt makes me wonder: Is Google simply executing poorly, or does it fundamentally disagree with where the AI industry is heading?\n\nCould Google actually believe that LLMs are ultimately a bubble  that AGI won’t emerge simply by scaling models, data, and compute year after year? Maybe they think the next breakthrough requires a fundamentally different approach rather than just bigger and better LLMs.\n\nOr perhaps I’m reading too much into it.\n\nThat’s all, folks. I’d genuinely love to hear what you think.\n\n\n\n--- Top Comments ---\n\n\n[172 upvotes] I think that Google has to deliver AI at much much larger scale than OpenAI and Anthropic combined. And it seems much of the effort is going to very efficient models you can plug for the billions of daily users of Google Search, Android YouTube Gmail and all other services they already provide.\n\n[100 upvotes] No, they don't believe LLMs are a viable path to AGI:\n\n\"Today's large language models are phenomenal at pattern recognition, but they don't truly understand causality. They don't really know why A leads to B. They just predict the next token based on statistical correlations.\"\n\n(Demis Hassabis)",
  "transcript_chars": 1775,
  "ingested_at": "2026-09-06T13:30:21.786434+00:00",
  "source": "reddit",
  "yt_meta": {
    "score": 113,
    "upvote_ratio": 0.87,
    "num_comments": 120,
    "author": "TameYour",
    "is_self": true
  }
}