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A bear case: My predictions regarding AI progress

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161–170 of 220 posts

Re: A bear case: My predictions regarding AI progress

#161
post #29

Let's imagine that we all had a trillion dollars. Then we would all sit around and go "well dang, we have everything, what should we do?". I think you'll find that just about everyone would agree, "we oughta see how far that LLM thing can go". We could be in nuclear fallout shelters for decades, and I think you'll still see us trying to push the LLM thing underground, through duress. We dream of this, so the bear cas…

Wdym all of us? I certainly would find much better usages for the money. What about reforming democracy? Use the corrupt system to buy the votes, then abolish all laws allowing these kind of donations that allow buying votes. I'll litigate the hell out of all the oligarchs now that they can't out pay justice. This would pay off more than a moon shot. I would give a bit of money for the moon shot, why not, but not all…

[deleted]

Re: A bear case: My predictions regarding AI progress

#162
post #22

> LLMs still seem as terrible at this as they'd been in the GPT-3.5 age. Software agents break down once the codebase becomes complex enough, game-playing agents get stuck in loops out of which they break out only by accident, etc. This has been my observation. I got into Github Copilot as early as it launched back when GPT-3 was the model. By that time (late 2021) copilot can already write tests for my Rust function…

Ultimately, every AI thing I've tried in this era seems to want to make me happy, even if it's wrong, instead of helping me. I describe it like "an eager intern who can summarize a 20-min web search session instantly, but ultimately has insufficient insight to actually help you". (Note to current interns: I'm mostly describing myself some years ago; you may be fantastic so don't take it personally!) Most of my intera…

7 is the worst part about trying to review my coworker's code that I'm 99% confident is copilot output - and to be clear, I don't really care how someone chooses to write their code, I'll still review it as evenly as I can.

I'll very rarely ask someone to completely rewrite a patch, but so often a few minor comments get addressed with an entire new block of code that forces me to do a full re-review, and I can't get it across to him that that's not what I'm asking for.

Re: A bear case: My predictions regarding AI progress

#163

Earlier quoted context omitted.

hardware improvements don't strike me as the horse to bet on. LLM Progression seems to be linear and compute needed exponential. And I don't see exponential hardware improvements besides some new technology (that we should not bet on coming ayntime soon).

Moore's law is exponential

Was.

Re: A bear case: My predictions regarding AI progress

#164

Author also made a highly upvoted and controversial comment about o3 in the same vein that's worth reading: https://www.lesswrong.com/posts/Ao4enANjWNsYiSFqc/o3?comment... Oh course lesswrong, being heavily AI doomers, may be slightly biased against near term AGI just from motivated reasoning. Gotta love this part of the post no one has yet addressed: > At some unknown point – probably in 2030s, possibly tomorrow (bu…

Was that comment intended seriously? I thought it was a wry joke.

I think so. Thane is aligned with the high p doom folks.

1 year may be slightly exaggerated, but it aligns with his view

Re: A bear case: My predictions regarding AI progress

#165

Earlier quoted context omitted.

> innovative, but not revolutionary The experience of Netflix, Spotify, and Uber were revolutionary. It felt like the future, and it worked as expected. Sure, we didn't realize the poison these products were introducing into many creative and labor ecosystems, nor did we fully appreciate how they would operate as means to widen the income inequality gap by concentrating more profits to executives. But they fit cleanl…

Making simple, small improvements feel revolutionary is good marketing.

"Simple, small" and "good marketing" seem like obvious undersells considering the titanic impacts Netflix and Spotify (for instance) have had on culture, personal media consumption habits, and the economics of industries. But if that's the semantic construction that works for you, so be it.

Re: A bear case: My predictions regarding AI progress

#166
post #115

Earlier quoted context omitted.

They were revolutionary as product genres, not necessary individual companies. Ordering a cab without making a phone call was revolutionary. Netflix at least with its initial promise of having all the world's movies and TV was revolutionary, but it didn't live up to that. Spotify because of how cheap and easy it was to have access to all the music, this was the era when people were paying 99c per song on iTunes. I've…

> They were revolutionary as product genres, not necessary individual companies. Even then, they were evolutionary at best. Before Netflix and Spotify, streaming movies and music were already there as a technology, ask anybody with a Megaupload or Sopcast account. What changed was that DMCA acquired political muscle and cross-border reach, wiping out waves of torrent sites and P2P networks. That left a new generation…

> What changed was that DMCA acquired political muscle and cross-border reach, wiping out waves of torrent sites and P2P networks.

Half true - that was happening some, but wasn't why music piracy mostly died out. DMCA worked on centralized platforms like YouTube, but the various avenues for downloading music people used back then still exist, they're just not used as much anymore. Spotify was proof that piracy is mostly a service problem: it was suddenly easier for most people to get the music they wanted through official channels than through piracy.

Re: A bear case: My predictions regarding AI progress

#167
post #71

Earlier quoted context omitted.

They were revolutionary as product genres, not necessary individual companies. Ordering a cab without making a phone call was revolutionary. Netflix at least with its initial promise of having all the world's movies and TV was revolutionary, but it didn't live up to that. Spotify because of how cheap and easy it was to have access to all the music, this was the era when people were paying 99c per song on iTunes. I've…

> Ordering a cab without making a phone call was revolutionary. With the power of AI, soon you'll be able to say "Hey Siri, get me an Uber to the airport". As easy as making a phone call.

You can book a flight or a taxi with a personal assistant app like Siri today. People don't seem very interested in doing so.

Barring some sort of accessibility issue, it's far easier to deal with a visual representation of complex schedule information.

Re: A bear case: My predictions regarding AI progress

#168
post #22

> LLMs still seem as terrible at this as they'd been in the GPT-3.5 age. Software agents break down once the codebase becomes complex enough, game-playing agents get stuck in loops out of which they break out only by accident, etc. This has been my observation. I got into Github Copilot as early as it launched back when GPT-3 was the model. By that time (late 2021) copilot can already write tests for my Rust function…

github copilot is a bit outdated technology to be fair...

Re: A bear case: My predictions regarding AI progress

#169

> At some point there might be massive layoffs due to ostensibly competent AI labor coming onto the scene, perhaps because OpenAI will start heavily propagandizing that these mass layoffs must happen. It will be an overreaction/mistake. The companies that act on that will crash and burn, and will be outcompeted by companies that didn't do the stupid. We're already seeing this with tech doing RIFs and not backfilling…

I'll take that bet, easily. There's absolutely no way that we're not going to see a massive reduction in the need for "humans writing code" moving forward, given how good LLMs are getting at writing code. That doesn't mean people won't need devs! I think there's a real case where increased capabilities from LLMs leads to bigger demand for people that know how to direct the tools effectively, of which most would proba…

Hate to be the guy to bring it up but Jevons paradox - in my experience, people are much more eager to build software in the LLM age, and projects are getting started (and done!) that were considered 'too expensive to build' or people didn't have the necessary subject matter expertise to build them.

Just a simple crud-ish project needs frontend, backend, infra, cloud, ci/cd experience, and people who could build that as one man shows were like unicorns - a lot of people had a general how most of this stuff worked, but lacked the hands on familiarity with them. LLMs made that knowledge easy and accessible. They certainly did for me.

I've shipped more software in the past 1-2 years than the 5 years before that. And gained tons of experience doing it. LLMs helped me figure out the necessary software, and helped me gain a ton of experience, I gained all those skills, and I feel quite confident in that I could rebuild all these apps, but this time without the help of these LLMs, so even the fearmongering that LLMs will ;make people forget how to code' doesn't seem to ring true.

Re: A bear case: My predictions regarding AI progress

#170
post #25
post #23

Earlier quoted context omitted.

You’re not using the best tools. Claude Code, Cline, Cursor… all of them with Claude 3.7.

Nope. I try the latest models as they come and I have a self-made custom setup (as in a custom lua plugin) in Neovim. What I am not, is selling AI or AI-driven solutions.

The entire wrapped package of tested prompts, context management etc. is a whole step change from what you can build yourself.

There is a reason Cursor is the fastest startup to $100M in revenue, ever.

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