If you run out of (solvable!) problems in your given logic space, just start branching out your space. Until you find yourself in such esoteric spheres, not even your best math co-researcher knows anymore what's happening and vice versa.
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ThereIsNoWorry commented on Math is running out of problems medium.com/@jpolak/math-i... · Posted by u/vouaobrasil
Does this coincide with the interest rate hikes and the induced layoffs and conservative hiring practices because of it? No, really? What a surprise!
ThereIsNoWorry commented on AI Search: The Bitter-Er Lesson yellow-apartment-148.noti... · Posted by u/dwighttk
The current hype phase is straight out of “Extraordinary Popular Delusions and the Madness of Crowds”
Science is out the window. Groupthink and salesmanship are running the show right now. There would be a real irony to it if we find out the whole AI industry drilled itself into a local minimum.
You mean, the high interest landscape made corpos and investors alike cry out in a loud panic while coincidentally people figured out they could scale up deep learning and thus we had a new Jesus Christ born for scammers to have a reason to scam stupid investors by the argument we only need 100000x more compute and then we can replace all expensive labour by one tiny box in the cloud?
Nah, surely Nvidia's market cap as the main shovel-seller in the 2022 - 2026(?) gold-rush being bigger than the whole French economy is well-reasoned and has a fundamentally solid basis.
ThereIsNoWorry commented on Tesla's FSD – A Useless Technology Demo tomverbeure.github.io/202... · Posted by u/nxten
The author of this article doesn't understand how continuous improvement in software works ...
Saying that it will "never" work is myopic.
Never bet against Moores Law or Elon!
As a Tesla M3 owner (in Europe where we don't have FSD yet) I cannot wait to have it for long road trips on highways where I want to relax and have a "copilot" do some of the "thinking" & driving for me.
Yes, there are still some instances of FSD Supervised doing strange things in the YouTube videos people are posting, but it's definitely no longer a "demo"! It's real and it's only a matter of time before it's better than humans in most circumstances ...
Now as a TSLA shareholder, I'm still sceptical that the RoboTaxi/CyberCab system will be 100% foolproof ... But if they can prove through data that it's safer than 99.9% of human drivers on every day journeys and thus get regulatory approval it will be game changing! If Tesla can do 90% of short ride city driving at a fraction of the cost of Uber/Lyft they have a real cash cow on the horizon!
> It's real and it's only a matter of time before it's better than humans in most circumstances ...
I heard that argument for many years for many deep learning applications of significant value. Any day now, right?
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ThereIsNoWorry commented on Tesla's FSD – A Useless Technology Demo tomverbeure.github.io/202... · Posted by u/nxten
Almost a decade ago I used to be a hyped up HS graduate fully spoon-fed the AI hype bubble (after 2012, the first "deep" learning breakthroughs for image classification started hyping the game up). I studied at a top 5 university for CS and specialised in deep learning. Three years ago I finished, rejected a (some would call "prestigious") PhD offer and was thoroughly let down by how "stupid" AI is.
For the last 2-ish years, companies found a way to throw supercomputers on a preprocessed internet dictionary dataset and the media gulped it up like nothing, because on the surface it looks shiny and fancy, but when you peek it open, it's utterly stupid and flawed, with very limited uses for actual products.
Anything that requires any amount of precision, accountability, reproducibility?
Yeah, good luck trusting a system that inherently just learns statistics out of data and will thus fundamentally always have an unacceptable margin of error. Imagine using a function that gives you several different answers for the same input, in analytical applications that need a single correct answer. I don't know anyone in SWE that uses AI for more than as a glorified autocomplete which needs to be proof-read and corrected more often than not to the point of oftentimes being contraproductive.
Tldr; it is exactly zero surprising that FSD doesn't work, and it will not work with the current underlying basis (deep learning). The irony is, that people with power to allocate billions of dollars have no technical understanding and just trust the obviously fake marketing slides. Right, Devin?
ThereIsNoWorry commented on The problem with invariants is that they change over time surfingcomplexity.blog/20... · Posted by u/kiyanwang
> For example, I'm a big fan of surrogate keys and UUIDs, in database design.
You would think this (using surrogate keys) would be such well worn wisdom by now that discussions about it wouldn't be a thing. But somehow new generations of developers, weaned on nosql and on not using the god-given gifts of databases like integrity constraints, seem to love bike shedding key design and arguing vociferously that natural keys can be used as primary (and foreign) keys.
You wouldn't believe how often I have to fight for UUIDs instead of sequencing. UUIDs are great. For all practical purposes 0 possibility of collision; you can use it as an ID in a global system, it just makes so much fucking sense.
But the default is still a number natural number sequence. As if it matters for 99% of all cases that stuff is "ordered" and "easily identifiable" by a natural number.
But then you want to merge something or make double use and suddenly you have a huge problem that it isn't unique anymore and you need more information to identify.
Guess what, an UUID does that job for you, across multiple databases and distributed systems, a UUID is still unique with 99.9999% probability.
The one counter-example every 10 years can be cared for manually.
In particular, GPT-2 to GPT-4 spans an increase from 'well read toddler' to 'average high school student' in just a few years, while simultaneously the computational cost of training less capable models goes down similarly.
Also worth noting: the article claims Stripe, another huge money raiser, had an obviously useful product. gdb, sometime-CTO of stripe and its fourth employee, is now president of OpenAI. And, most of all, the author doesn't remember how nonobvious Stripe's utility was in its early days, even in the tech scene: there were established ways to take people's money and it wasn't clear why Stripe had an offering worth switching to.
For an alternate take, I think https://situational-awareness.ai provides a well reasoned argument for the current status of AI innovation and growth rate, and addresses all of the points here on a general (though not OpenAI specific) way.