None of this means that there could not be roadblocks or that LLMs will scale to AGI – we have no idea – but there appear to be multiple options going forward.
@emollick
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Moonshot slightly older than xAI founding timeline
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Moonshot is just a little bit older than xAI.
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Scaling Laws and Tool Use Driving AI Progress Forward
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Grok 4 suggests that scaling still works (with the diminishing returns predicted by the scaling law), and that tool use can unlock performance gains. Kimi suggests there continues to be big opportunities from improvements in methods (Muon, etc.). Lots of paths for AI right now.
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Web Knowledge Density vs Books Copyright Ethics Debate
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And yes this would violate all copyright laws and thus probably should not be done. But still, the web is so much less knowledge dense and contains so many fewer viewpoints than books.
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AI Training on Books for Intellectual Discovery
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In an academic bookstore and it is one of the times where I want a good AI trained on all books, even imperfectly. I want to learn a bit about the smells of antiquity & the history of idea of gray & etc. but am not going to read every book. I could learn a lot from an AI who has.
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xAI’s API Push and Superintelligence Goals: Strategic Pressures
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The pressure to do this would be less if they (a) weren’t trying to encourage API use from organizations and (b) weren’t explicitly trying to build a superintelligent AI (regardless of whether you believe this to be possible, xAI seems to view this as their goal)
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AI Company’s Repeated Internal Review Failures Raise Transparency Concerns
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I do think this makes their reluctance to release any sort of external red teaming or system card more of a an issue. This is the third time that they have had to apologize for a process failure in their internal review process.
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xAI Postmortem Reveals System Prompt Security Risks
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First off, it is good to see a postmortem from xAI, a step towards much needed transparency. Second, an example of how even small changes to system prompts, interacting with users and outside context in the wild, can lead to unexpected outcomes in advanced LLMs.