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Anthropic logged net loss of over $80 billion in first half of 2026 (www.reuters.com)
submitted 1 day ago by to c/technology@lemmy.world
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[+] -9 points 21 hours ago* (2 children)

AGI has been achieved more or less because it just means self sufficient at completing tasks. An LLM is just a component these days because they are Vision-Audio-Language-Models with multi frequency 'thought' loops. The next letter is A for action where they just have high frequency outputs for direct computer and robot use.

Just because it is bad AGI doesn't mean it is not AGI right

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  • [–] 5 points 19 hours ago (1 child)

    See the problem is that people expect AGI to learn on its own. LLMs sorta do with big enough context and writing memories, but... They also don't. They don't get better at reasoning or anything, they only get better at solving the tasks they've written notes on. Which are themselves often pretty bad notes.

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  • [–] -1 points 14 hours ago

    They do learn they use search tools and create long term memories. Mechanically that is just tool use it isn't magic. Do you need these things as emergent properties for them to be real? That would be cool but I don't think it takes away what is possible now.

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