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YES! I study AI, and this is exactly how I feel!
Side note-One of my favorite things to do is ask people what their use case for using AI is, and watch them sputter out “uh…emails and productivity and things.”
YES! I study AI, and this is exactly how I feel!
Side note-One of my favorite things to do is ask people what their use case for using AI is, and watch them sputter out “uh…emails and productivity and things.”
The original paper itself, for those who are interested.
Overall, this is really interesting research and a really good “first step.” I will be interested to see if this can be replicated on other models. One thing that really stood out, though, was that certain details are obfuscated because of Sonnet being proprietary. Hopefully follow-on work is done on one of the open source models to confirm the method.
One of the notable limitations is quantifying activation’s correlation to text meaning, which will make any sort of controls difficult. Sure, you can just massively increase or decrease a weight, and for some things that will be fine, but for real manual fine tuning, that will prove to be a difficulty.
I suspect this method is likely generalizable (maybe with some tweaks?), and I’d really be interested to see how this type of analysis could be done on other neural networks.
Blue or green for me. Never could find a proper teal folder.
I’m all about this. When I made my personal webpage, this is how I do it. I’m surprised it’s not more popular (at least for certain things) because it looks nice and clean, is fast, and crucially, is easy to put together. Most webpages don’t need a ton of JS to “accomplish the mission.” I get that not everything can do this, but there are soooooo many sites that can strip down to a more minimal site and have better functionality and a better experience. This is a case of less-is-more.
This is a much better article. OP’s article just shows the author’s surface understanding of how coding works and how well an LLM can actually code. There’s way more that goes into a programming task than just coding.
I see LLMs as having the potential of being almost like a super library. I can prompt GPT, Claude, etc. to write me a custom function that I copy, paste, test, scrutinize, and almost certainly change. It’s a tool that will make someone a more productive programmer. It won’t completely subsume a human’s ability to be creative and put the pieces together.
At the absolute worst over the next decade, I could see programming changing from writing and debugging code to prompting, stitching together, and debugging.
Or they just don’t try this at all. The technology seems beyond far-fetched at this point, like mad scientist far-fetched. The tech is too light on theory to begin practical testing, At this point, it’s just inhumane.
Depends on your skills. Documentation is always useful. If you have language skills, translation of documentation or helping create language packs/translations.
That’s just off the top of my head. I’m sure if I thought about it, I could come up with more.