627 karma · joined August 29, 2016
Location: West Coast (PST)
Remote: Yes, 10+ years remote experience
Willing to relocate: Possible
Technologies: Web, JS/React/3JS, Python/Torch, PHP/SQL, UI/UX, Crypto, AR/VR, AI/ML/Q-Learning
Résumé/CV: https://www.linkedin.com/in/warren-koch-156aa026/
Email: warrenkoch (gmail)This non-hypothetical got us global warming already
What made you want to make a browser instead of something much simpler like - an OS?
Coincidentally, that appears to be how GPT4 was made - apparently it's actually about 8 personas with designated roles running GPT3.5 trained together ("Panel of experts"? there's an AI name for the technique). Makes you wonder how far that one trick scales.
(P.S. great link. Gah - another long read on the todo list)
Would be nice if they all get locked up, and/or decentralized regulation/vetting networks arise
https://twitter.com/fablesimulation/status/16813529041528504... These guys seem to be on the leading edge there - making self-referential character-driven narratives where agents talk to each other and build the collective world understanding, all through a South Park Westworld lol
It is entirely likely that the way we operate is probability-first, only deriving rules loosely after taking in lots of experiential data to speed up and simplify that initial fake-it-til-you-make-it understanding. The fact LLMs can get the quality we see using just this approach is a strong indicator that this method of understanding may be a fundamental approach of biological systems too.
(and if you're arguing this is unfair because humans created the language that's being used for probabilistic training - well, look at image models trained on photographs instead and tell me those aren't an example of extreme quality derived purely from mass-inferenced data. Rules-based architectures don't necessarily need apply.)
But honestly, this seems like a silly claim to begin with if it really was claimed. We have formal language theory complexity classes of probabilistic algorithms for a reason - they work! It shouldn't be surprising that the model can stretch down to the fundamentals too. Far fewer programmers (and linguists) were raised to think with these models than deterministic rules-based ones, but the field has been progressing alongside for decades, and now they get to play with powerful LLMs that take probabilistic inferencing to the extreme and will likely prove it works (very elegantly) for everything. This shouldn't be surprising in retrospect.
Chomsky may very well be right that there always exists some fundamental elegant formula underlying any phenomenon (or at least any language). But it's undeniable at this point that simplistic statistical approaches can be applied at scale to those phenomenon and derive highly-useful general models, which also will very likely converge upon the elegant formulas he envisioned. The two are intrinsically linked, neither inseparable.
Rewilding - bringing artificial human-made processes to grow thriving natural environments - is something we should definitely consider. We are capable of creating abundance beyond what nature provides alone
This problem isn't complicated because it's intellectually challenging. This problem is complicated because the balance of power is overwhelmingly favorable to the rich, and they have many means to both disrupt the conversation in intellectual circles and to block any political means of making these necessary changes.
See economist Richard D. Wolff for extremely simple answers to the above problem. Ultimately it is simply the math of value flows. Current system? Inherently concentrates at the top. Adjust taxes (any of them!!) to reverse that.
It's a fundamentally unfair system which inevitably maximizes inequality. It's untenable without a government-enforced wealth-redistributing tax to offset that.