We've come full circle.
2,918 karma · joined July 6, 2022
We've come full circle.
If you think about it, "load-bearing" is a pretty commonly used concept in pedagogical writing. You could say "most important", but it's not quite the same in meaning. English just doesn't have a better word to describe a concept that occurs this frequently. The LLM's catchphrases reveal blindspots in the English language itself.
When I build an application that uses LLMs, it's tuned and tested for a specific model only. LLMs are not really drop-in replacements of each other, even different versions of the same series.
The pertinent question isn't why OpenRouter but why a router company is worth 7B.
Claude already has a killer product (claude.ai/chat is a Swiss army knife) but just relying on people typing stuff into chat is not enough to sustain the company.
The other strategy is entrenching yourself as the LLM of choice into existing products (like ChatGPT is on Apple products).
Also, let's not forget that the Trump admin is a problem of 2.5 years at most.
Trump has greatly stressed the safeguards in our system, but I don't think that he has broken them. That is actually an optimistic instead of a pessimistic signal -- an anti-statesman even in the highest office couldn't meaningfully damage the country.
The number of times I've heard "SaaS is dead" irl and flustered responses when I asked "what does that mean?" is comically too high.
An all-out global nuclear war (all nuclear nations landing 10% of their warheads in populated areas) would be a disruption comparable to COVID at best.
It's a complete failure of the state in having any kind of foresight.
China, in comparison, has around 2X excess electric production capacity in their grid. That's what made mining Bitcoin, and now ultra-cheap LLM inference, economically viable.
It's not like restaurants where for example you can open a "Larry's Pizzeria" and still build a valuable business despite a Domino's nearby.
In such markets, what you produce is either worth nothing or worth millions of dollars. For as long as it's the case that well-constructed code (with or without LLM help) is more likely to be in the latter category, the economics of software don't really change.
Even before LLMs, you could've commissioned a half-assed clone of any app you wanted from a 3rd world consultancy for a few thousand dollars. LLMs are basically Bangalore-as-API.
TFA contends that there is some fundamental shift in the economics of software, but it doesn't look to be very different from either a new SaaS dependency or racking new hardware.
Not really.
>Every inference call costs money.
Not really, either. If you buy your own GPU, rack it, and run an open model, there is no unit cost. This is just expensive hosting infra. You also pay unit costs for SaaS that your software uses (things like SMS etc).
There is currently a $800 SOTA blood test that can detect most cancers before any symptoms. Maybe a decade until it's a routine part of your annual blood test?
Whole genome sequencing costed $2.7 billion in 2003. You can get it done today using a mailed kit for $400.
HIV went from death sentence to all-but-cured in 50 years.
https://www.atomicarchive.com/almanac/test-sites/testing-chr...
Remember the LLM is not a human employee. You don't have to say "yes and" to whatever crap they produced so as to not hurt their feelings or infringe upon their creative autonomy, nor do you have to defend the correctness of your original instructions so that they don't think less of you for asking them to chase the wrong goose.
I probably generate 20-50 lines of code for every 1 line that I keep.
This is also why I think harnesses and things like Claude Code and OpenCode are false efficiency. The only way I can maintain my pace of branched trial-and-error is by using claude.ai/chat and manually extricating code fragments to and from my codebase. The human is still the best harness for production-level code.
FYI, "market rate" refers to the highest compensation that someone would be willing to offer a person with that profile. When you sell something, you sell it to the highest bidder. You don't sell it to the median buy offer.
>We target your total compensation (salary + equity-to-be-vested) to be greater than the 75th percentile
So, below market rate?
Have we? Or is this just something that people say now, without citation?
The QoL improvement from LLM is somewhere in the ballpark of going from dumb phones to smart phones for an average person (able-bodied, local to the area etc). It's nowhere near Haber-process or penicillin.