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Show HN: Mini-AGI – Dynamic continual learning model trained on 8GB VRAM

277 points · 81 comments · volotat

  1. cpldcpu · · focus · HN ↗
    Is this architecture actually able to generalize or is it mostly based on memorization? Have you tried some basic tasks that require generalization? e.g. number addition etc?
    1. volotat · · focus · HN ↗
      The model is way too small and undertrained to make any generalization claims. I want to wait until it reads the whole corpus I gave and then test it on some simple established benchmarks to see how it will behave.
      1. jacquesm · · focus · HN ↗
        What kind of hardware are you using for training?

        nm, I found it:

        > RTX 3070 Laptop GPU with 8 GB

        Super impressive.

      2. dinfinity · · focus · HN ↗
        Seems a bit premature to make an HN post about then, imho.

        It's an interesting idea, but it doesn't really do anything interesting yet. I looked at the output in the training run and it is a far, far cry from intelligence. Worse than GPT-2 as it stands.

        I do hope it will perform well when scaled and trained, though; best of luck.

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