5 ms·

What is your definition of AGI that the current LLMs don't fit?

• paxys 4mo ago
  As the old saying goes, I’ll know it when I see it. The current 5.x generation isn’t it.
• gordonhart 4mo ago
  Autonomously Generating Income (which is why it will never be released to the general public)
  • koolala 4mo ago
    Hopefully it stands for AC Generation Improvements. If it prioritizes income it will bleed the planet dry. It needs to solve how expensive our cost is on the planet first or its entire existence was a mistake.
• ThrowawayTestr 4mo ago
  When it understands why 6 7 is funny
• isomorphic_duck 4mo ago
  Continual Learning? Why is this even a question? Isn’t it a well-known glaring issue with the current models? They cannot learn/adapt to new skills (in any permanent sense) once they are deployed.
• FromTheFirstIn 4mo ago
  You’d have to really stretch the definition of AGI to make the current models fit
  • LordDragonfang 4mo ago
    The definition has already been stretched to not fit the previous models. There is no meaningful, static definition that significantly predates current capabilities. There's a reason why ai xrisk doomers had to come up with the term ASI. I would seriously suggest that everyone take a look at the wikipedia page for AGI from the month before ChatGPT was released, compare it to the current version, and not come to that conclusion. https://en.wikipedia.org/w/index.php?title=Artificial_general_intelligence&oldid=1116684527 https://en.wikipedia.org/w/index.php?title=Artificial_genera...
    • FromTheFirstIn 4mo ago
      The first sentence is “understand or learn any intellectual task that a human can.” Whatever you think of the benefits of LLMs, they don’t understand and they can only learn during the training period and with very minor adjustments in post training. So, no I don’t think any of these models are generally intelligent.
      • LordDragonfang 4mo ago
        > they don’t understand I have not seen any instance of this frequently-made assertion which is at all justified. It seems to rely on a definition of "understand" which is more about spirituality than actual observable evidence (they clearly can comprehend even complex tasks well enough to execute on them, and if you won't call that "understanding", you're playing word games rather than stating an objective fact). Likewise, agents can literally come to a greater understanding of a problem through trial and error, and there are plenty of mechanisms to retain that knowledge. If you don't want to call that "learning", you're just making a choice to define it in a way more restrictive than how we use it for humans, and intentionally making communication more difficult.
        • mellosouls 4mo ago
          It seems to rely on a definition of "understand" which is more about spirituality than actual observable evidence "Understanding" has enough philosophical leeway in its use to allow at least the possibility of sentience as a prerequisite. This is where the discussion about LLM capabilities becomes genuinely difficult, and dismissing that difficulty as "word games" or "spirituality vs evidence" is not helpful.
          • LordDragonfang 3mo ago
            Considering that "sentience" has enough "philosophical leeway" that it's just as reasonable to assert that LLMs are sentient (and at extremes, that they have been sentient for years) -- especially if we are, as you suggest, supposed to include any philosophically possible definition -- I don't think that's a meaningful rebuttal. If no one can agree on whether it's sentient, it's bad faith to choose a fringe definition that hands off its definition to such a nebulous term. In fact, I'd argue that statements about what "is" and "is not" sentient relies on even more spirituality and word games for anything that isn't a terran tetrapod. For a meaningful -- "helpful" -- discussion on such things, one has to assume that everyone is choosing a definition which is closer to the median usage and relies on not being totally subjective. Furthermore, given the breadth of options, it should be assumed to be a definition which allows which permits the form of the question to be meaningful, rather than begging the question -- if your definition is tautological enough that non-biological entities can't have understanding, you're just expressing dogma rather than having a discussion. Anything else is bad faith, or assuming bad faith on the part of the participants.
• 0x696C6961 4mo ago
  Always one goalpost away from what we have.
• UltraSane 4mo ago
  AGI should be able to do every job a human can do using a computer at least as well as the average human.
  • LordDragonfang 4mo ago
    That's already been true for a while, you're overestimating the average human. They just have different failure modes.
    • UltraSane 3mo ago
      It isn't even close to true. The biggest problem is that humans performance improves over time. https://www.linkedin.com/pulse/announcing-aa-briefcase-bench https://www.linkedin.com/pulse/announcing-aa-briefcase-bench... AA-Briefcase is a new benchmark for testing models on realistic knowledge work tasks in complex projects built by industry experts. Models are evaluated on multi-week knowledge work projects, each with many linked tasks and thousands of input source files. AA-Briefcase combines rubric and pairwise grading to evaluate verifiable task success, analytical quality, and presentation quality, giving a holistic view of overall agentic capability in knowledge work. Tasks with many messy input files, conflicting information, and complex deliverables remain difficult for all models. Under a strict all-or-nothing grading scheme per task, Claude Fable 5 leads overall, but achieves a perfect task score on only 3% of tasks. On 31 of 91 tasks, no model scores above 50%.
  • Davidzheng 4mo ago
    And what is it worse at than an average human today that can be done on a computer?
    • UltraSane 4mo ago
      almost everything? AGI has to be able to completely replace a human in any information worker role indefinitely.
      • virgildotcodes 4mo ago