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Topic
Large Language Models (LLMs)
Last discussed
1y ago
Nov 12, 2025
3 tagged in 12 months
Could LLMs Be The Route To Superintelligence? — With Mustafa Suleyman
Big Technology Podcast·Nov 12, 2025
All time
9
episodes
On record
4
took a position
Where they standWhere they stand
Talking pointsNot enough disagreement in the transcripts to form camps. These are the positions taken by people with demonstrated expertise on this topic first, then by how many people heard them on it, then by VoiceRank. Positions are extracted from transcripts by a model and may misattribute who said what. Every quote links to the episode it came from.
Large Language Models are the viable path toward superintelligence as they are being improved through new methods like reasoning and architectural changes.
“so I don't think there's anything fundamentally wrong with the LLM architecture and I don't think we're fundamentally compute or data constrained. I think that there are so many people focused on this problem now. There are just going to be more and more um you know breakthroughs coming.”
Big Technology Podcast · Nov 2025 · 1 episode · 20K views on this topic
Autoregressive large language models are limited because they lack understanding of the physical world, persistent memory, reasoning, and planning capabilities.
“they don't really understand the physical world don't really have persistent memory they can't really reason and they certainly can't plan”
Lex Fridman Podcast · Mar 2024 · 1 episode · 1.3M views on this topic
LLMs represent a dangerous step in AI development, and even if they are not the final architecture for superintelligence, their continued scaling poses an existential threat.
“It might be that you just throw a 100 times as much computing power at the current algorithms and they end the world or they get good enough at coding and AI research to end the world.”
Chris Williamson · Oct 2025 · 1 episode · 326K views on this topicAD
Adam D’AngeloUnrated
Current language models are not hitting fundamental limits and significant progress will continue through innovations within the existing paradigm.
“I don't see a reason why we don't eventually get there. That may take five, 10, 15 years. But I think until you get there, we're going to get bottlenecked on the things that the LM still can't do”
a16z · Nov 2025 · 1 episode · 21K views on this topicExtracted by a model; may misattribute who said what.
In the transcripts
Episodes discussing this topic
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Share of episodesThis topic's episodes as a share of every episode we analysed, in each complete month. We analyse more episodes every month, so a raw count would mostly show that growth. Recent months fill in as transcripts are analysed.
Complete months · first on record Mar 2024