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I think bearish on LLMs for automation, and bullish for LLM+human experts in specific fields, is about the right expectation for current architectures. Apart f
by randomImmigrant 11d ago
I think bearish on LLMs for automation, and bullish for LLM+human experts in specific fields, is about the right expectation for current architectures.
Apart from issues with task generalization, or perhaps related to it, is the fact that LLMs have real trouble with timekeeping, and cannot estimate the real world time it will take them to do things very well. This plus the memory issues make dreams of long horizon agents, that could plausibly handle changing specifications, quite implausible with current architectures.
In narrow domains with more deterministic outputs though, this is less of an issue, and we see multiple agents succeed much better.
The fusion of that capacity, with humans in the loop able to better direct such agents and act as their temporal tethers, is where I think the real action will be for a while at least.
- handfuloflight 11d ago> This plus the memory issues make dreams of long horizon agents, that could plausibly handle changing specifications, quite implausible with current architectures. Any reason why that can't be solved through context management and keep-forward scaffolding?
- arm32 10d agoWrite the same sentence you just wrote back to me, but in only four words and let’s see if it has the same meaning.
- lantry 10d ago"Any reason why that can't be solved through context management and keep-forward scaffolding?" becomes "load bearing context seam" /s
- bitwize 10d agoYou're gonna have to learn to talk that LLM speak! Dabadooba, ba dabadooba! https://www.youtube.com/watch?v=egpWCC2svVo https://www.youtube.com/watch?v=egpWCC2svVo
- handfuloflight 10d agoRemember specifics, keep going.
- randomImmigrant 10d agoAnd who’s to manage context? And who’s building the scaffolding? Yes, AI can be used for both, but you do realize that all this being self-contained and regulated internally is what makes biological agents successful agents, right? If you break the process apart and need to dial back in these aspects, and can only do so with human input, or another agent which will need the same handholding the one whose issues you’re solving for, where’s the agency?
- deleted 10d ago[deleted]
- antupis 10d agoI think automation is coming but it will be way more gnarly than frontier labs want public to believe. Value is just too big, when you can automate most of eg customer support it will create huge savings and same time customer satisfaction will get better.
- hi_im_greg_h 10d ago> same time customer satisfaction will get better. This part just can't be true though, right? We have all been in numerous customer service scenarios where all we want to do is talk to a real human and that is denied to us, and it's a terrible customer experience! Sure, using an LLM would be better than some of the sort of "menu option" style customer service calls. But there is no way it's better than talking to an actual human being
- imhoguy 9d agoThis. Listening and creative customer support rep, especially one who can even escalate fundamental product issues to company leadership is worth weight of gold.
- oscillonoscope 10d agoMy belief is that LLMs will fundamentally change how we approach domain expertise. From what I've seen, SDEs tend to be over-specialized compared to what the company actually needs to implement due to the need to understand enough of the domain to pick a best path. If an LLM can see the domain enough so that someone in an adjacent field can be confident in their approach and quickly change course then you don't need as many niche SDEs