Comment by jameslk
15 hours ago
The churn is real. I wonder if so much churn due to innovation in a space can prevent enough adoption such that it actually reduces innovation
15 hours ago
The churn is real. I wonder if so much churn due to innovation in a space can prevent enough adoption such that it actually reduces innovation
It’s churn because every new model may or may not break strategies that worked before.
Nobody is designing how to prompt models. It’s an emergent property of these models, so they could just change entirely from each generation of any model.
IMO the lack of real version control and lack of reliable programmability have been significant impediments to impact and adoption. The control surfaces are more brittle than say, regex, which isn’t a good place to be.
I would quibble that there is a modicum of design in prompting; RLHF, DPO and ORPO are explicitly designing the models to be more promptable. But the methods don’t yet adequately scale to the variety of user inputs, especially in a customer-facing context.
My preference would be for the field to put more emphasis on control over LLMs, but it seems like the momentum is again on training LLM-based AGIs. Perhaps the Bitter Lesson has struck again.
A constantly changing "API" coupled with a inherently unreliable output is not conducive to stable business.
It's interesting that despite all these real issues you're pointing out a lot of people nevertheless are drawn to interact with this technology.
It looks as if it touches some deep psychological lever: have an assistant that can help to carry out tasks that you don't have to bother learning the boring details of a craft.
Unfortunately lead cannot yet be turned into gold
> a lot of people nevertheless are drawn to interact with this technology.
To look at this statement cynically, a lot of people are drawn to anything with billions of dollars behind it… like literally anything.
Not to mention the amount companies spend on marketing AI products.
> It looks as if it touches some deep psychological lever: have an assistant that can help to carry out tasks
That deep lever is “make value more cheaply and with less effort”
From what I’ve seen, most of the professional interest in AI is based on cost cutting.
There are a few (what I would call degenerate) groups who believe there is some consciousness behind these AI, but theyre very small group.
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Unless your business is customer service reps, with no ability to do anything but read scripts, who have no real knowledge of how things actually work.
Then current AI is basically the same, for cheap.
Many service reps do have some expertise in the systems they support.
Once you get past the tier 1 incoming calls, support is pretty specialized.
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