Comment by zwarag
10 hours ago
I have yet to see an application outside of harnesses and LLMs itself where adaptation has happened on a larger scale. Devs are fine with babysitting their LLMs. People like to use LLMs to improve their mails and so on. But outside of that, the adaptation is not there yet.
Don't get me wrong. I love LLMs and use them myself. But the biggest gain for me is easier context switch and text manipulation. It's not the: replace X with a bunch of LLMs every CEO is dreaming of. So yes, you have higher productivity, but is the eval of those companies legit? x doubt.
Markets value future cash flows, not today's cash flows.
By the time you see the applications, the market will have moved on to value the next set of future cash flows.
If the market only valued the obvious, investors would jump in to buy the price up, until it met the average expectations.
The market might be wrong, but the question is not: "Have you yet to see?", but rather, "What do you see in the next three to five years?"
Otherwise, how could investors ever invest in a startup?
Startups never have revenues to justify their initial valuations.
It's a bet on the future.
Investors are future looking.
Consumers are present looking.
We didn't see LLM harnesses coming even two years ago. Now they generate billions per month.
Investors can't wait until reality materializes to make their estimations of the future.
That's why investing is hard.
You have to try to predict the future.
One third of all software code is written by AI. At the frontier AI labs it's 80%+. It has completely upended the software industry. How is that not a massive adaption?
> One third of all software code is written by AI.
I find it interesting that using lines of code as a metric is making a comeback.
The number of lines of code doesn't matter any more. A better metric is AI-assisted commits, which has the same statistics.
1 reply →
You couldn’t have picked a better argument to show how this bias is exactly what’s making tech people think this shift is ubiquitous. “It works extremely well for coding, in which I am a domain expert, so why wouldn’t it work for all the other domains I absolutely know nothing about?”
It doesn't even work that well for coding.
Otherwise Github wouldn't have 14% down time in the last 3 months.
ChatGPT has 700 million users. What do you think they are using it for? It's upended entire industries.
How many millions of emails do you think are composed using ChatGPT? How many legal briefs were reviewed by AI? How many businesses use AI generated art? How many kids do their homework using ChatGPT?
The GP is arguing that AI has struggled to replace humans, but in so many roles AI is doing the heavy lifting and humans are copying its output.
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Because it doesn’t work without me
What is a larger scaler for you? What is "outside harness an LLM"?
What is _the proof_ if all the proofs are not _proofs_?
I don't babysit my LLM based services which are used by coaches and clients around the world. One of my LLM based solution get 30-4k daily hits and I have users coming back on the regular to use it. without babysitting, doing things that would take them hours of manual work and research.
I don't babysit the developers I work with and our clients, which both use LLM's themselves and at scale with their clients, serving all kinds of LLM powered services to millions of users worldwide.
You are not "seeing" the large adoption because:
- The technology is "a few years old" in its usable state - The corporate adoption cycle is slow - You have to understand the technology to use it in a good way, which most corporate devs and PM's do not
So it will take a bit for the "obvious" adaptation on large scale.
But you won't "know" when the large adoption happens.
Silent inference is growing every day, and that is what real adoption looks like - not an LLM being in your face chatbox, but running in the background, sorting, finding, fixing things, aligning data, figuring out analytics, tuning the ads, cleaning the datasets.