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ratedgene

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It's a bit of both, in any technological shift, a particular set of skills simply becomes less relevant. Other skills are needed to be developed as the role shifts.

If we're talking about simply cutting costs, sure -- but those savings will typically be reinvested in more talent at a growing company. Then the bottleneck is how to scale managing all of it.

ElevenReader 1 year ago

Honestly, why isn't this same service baked into my OS? the reader there is really atrocious, but I imagine even for a single voice a pretty small model can be downloaded and made available as a plugin for the reader app.

I think we just haven't built complex enough architectures to allow this. I have a few ideas boiling that would help facilitate long term context understanding and recall.

Hey, I wonder if we can use LLMs to learn learning patterns, I guess the bottleneck would be the curse of dimensionality when it comes to real world problems, but I think maybe (correct me if I'm wrong) geographic/domain specific attention networks could be used.

Maybe it's like:

1. Intention, context 2. Attention scanning for components 3. Attention network discovery 4. Rescan for missing components 5. If no relevant context exists or found 6. Learned parameters are initially greedy 7. Storage of parameters gets reduced over time by other contributors

I guess this relies on there being the tough parts: induction, deduction, abductive reasoning.

Can we fake reasoning to test hypothesis that alter the weights of whatever model we use for reasoning?

Love the word "Autopoietic", nobody really knows about it and any text that uses it for sure will capture my interest.

I've first thought of this within the concept of self-assembling autonomous agents in 2016. Good times dreaming about a future where AI permeates every facet our lives.

So maybe if there isn't a perceived value in the way we learn, then how learning is taught should maybe change to keep itself relevant as it's not about what we learn, but how we learn to learn.

geolocation, search, path/route finding.

I don't really care to memorize (which was most of the coursework) things which I can just easily look up. Maybe geography in the south was different than how it was taught elsewhere though.

I was talking to a teacher today that works with me at length about the impact of AI LLM models are having now when considering student's attitude towards learning.

When I was young, I refused to learn geography because we had map applications. I could just look it up. I did the same for anything I could, offload the cognitive overhead to something better -- I think this is something we all do consciously or not.

That attitude seems to be the case for students now, "Why do I need to do this when an LLM can just do it better?"

This led us to the conclusion:

1. How do you construct challenges that AI can't solve? 2. What skills will humans need next?

We talked about "critical thinking", "creative problem solving", and "comprehension of complex systems" as the next step, but even when discussing this, how long will it be until more models or workflows catch up?

I think this should lead to a fundamental shift in how we work WITH AI in every facet of education. How can a human be a facilitator and shepherd of the workflows in such a way that can complement the model and grow the human?

I also think there should be more education around basic models and how they work as an introductory course to students of all ages, specifically around the trustworthiness of output from these models.

We'll need to rethink education and what we really desire from humans to figure out how this makes sense in the face of traditional rituals of education.

I love the gaussian splatting that's going on. I also love the people pushing gaussian splitting and generative AI. I really feel there is something there but I'm not quite sure what yet. It's cool seeing this unfold, but I'm also worried it can turn into something like Photosynth, where it was a cool exercise but not much came out of it. I would love someone's input who is involved in this tech that could blue sky where it could be applied in interesting ways.