Comments URL: https://news.ycombinator.com/item?id=47363337

Points: 2

# Comments: 0

But the broken rhythm problem persists regardless, and I find that issue to become more and more serious as LLMs are able to work for longer and longer on their own.

It might be that what we're experiencing now is just an uncanny valley, where they're not yet good enough for us managing them to work in similar ways as with other developers, but are good enough to allow us to switch our attention away from them while they work. But that attention span is mostly wasted, as the time between interactions isn't enough to e.g. work on something else, or read a book.

It's a stupid analogy, but currently it's similar to having a bathroom break every couple of minutes, and if this continues, most developers will probably start doomscrolling more and more.

I was wondering recently if there are some productive activities that might fit well into this rhythm, but I haven't found any yet. I guess sourdough baking is one such example, but there's only so much bread you can eat...

Surface of "illusions" for LLMs is very different from our own, and it's very jagged: change a few words in the above prompt and you get very different results. Note that human illusions are very jagged too, especially in the optical and auditory domains.

No good reason to think "our human illusions" are fine, but "their AI illusions" make them useless. It's all about how we organize the workflows around these limitations.

Obviously I am not comparing his final product with my code, I am simply pointing out how this metaphor is flawed. Having "workers" shape the material according to your plans does not reduce your agency.

Discovering the right problem to solve is not necessarily coupled to being "hands on" with the "materials you're shaping".

https://www.imdb.com/title/tt0077598/?ref_=ext_shr

So I built a simple Telegram bot which automatically stores anything I send as a text embedding into a vector database, and allows me to search over it in that same chat (same process that powers the AI Q&A assistants these days).

If I post a link, it automatically scrapes it and stores text as chunks for better search, extracts text from youtube videos (still wip), turns images into text with the visual models, etc.

One thing I'm unhappy about is not being able to easily edit any notes I search for later, but it's miles ahead of my previous "system". Hopefully I can open source this when I clean it up - if anyone is interested, let me know.

I believe the last point is most important, and is where your app is misaligned with my reasons for using messages - you seem to have spearate folders and notes, prompting me to think "where does this go?" before writing, which is something I really want to avoid.

What I am always wondering, and maybe you can give some details here, is the following: isn't the fact that regulations are in natural language, with all its ambiguity, a necessary requirement to have the system operate without being fully specified?

In other words, wouldn't any kind of strict DSL force us to think through all the edge cases that might possibly arise, instead of dealing with them when they do arise, which is basically what the judiciary is for? And isn't that a price too high to implement these kinds of systems?

It's been quite clear for some time that, between OAI and MS, they very neatly split their market: OAI handles the early development and direct customers, and MS handles enterprises. It would require OAI to be a much bigger company than it is right now to properly handle enterprises, and MS already has all that infrastructure (legal, support, etc.). Seems like a sensible setup to me, and I don't see the need for enterprises to run open source models themselves (in this context - of course I see the value in all the other respects about lock-in and specialization), especially if they are already on Azure.

[1] https://github.com/ibestvina/datasloth

[2] https://qluent.com/