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LLM Inevitabilism

tomrenner.com

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Re: LLM Inevitabilism

#751

Post by ysavir »

Centigonal wrote: post #678
dbalatero wrote: post #538

Earlier quoted context omitted.

They might generate 10b ARR, but they lose a lot more than that. Their paid users are a fraction of the free riders. https://www.wheresyoured.at/openai-is-a-systemic-risk-to-the...

This echoes a lot of the rhetoric around "but how will facebook/twitter/etc make money?" back in the mid 2000s. LLMs might shake out differently from the social web, but I don't think that speculating about the flexibility of demand curves is a particularly useful exercise in an industry where the marginal cost of inference capacity is measured in microcents per token. Plus, the question at hand is "will LLMs be rele…

The thing about facebook/twitter/etc was that everyone knew how they achieve lock-in and build a moat (network effect), but the question was around where to source revenue.

With LLMs, we know what the revenue source is (subscription prices and ads), but the question is about the lock-in. Once each of the AI companies stops building new iterations and just offers a consistent product, how long until someone else builds the same product but charges less for it?

What people often miss is that building the LLM is actually the easy part. The hard part is getting sufficient data on which to train the LLM, which is why most companies just put ethics aside and steal and pirate as much as they can before any regulations cuts them off (if any regulations ever even do). But that same approach means that anyone else can build an LLM and train on that data, and pricing becomes a race to the bottom, if open source models don't cut them out completely.

Re: LLM Inevitabilism

#752

Post by stale2002 »

I'm not sure what this guy is even advocating for. Is he saying that LLMs should be made illegal or something? Given that they can run on my home PC, I doubt thats going to go well.

And if you can't make it illegal, then good luck stopping people from using it. It is inevitable. I certainly am not going to willingly give up those benefits. So everyone else is free to fall behind, I guess, and lose to those who defect and accept the benefits of using LLMs.

Re: LLM Inevitabilism

#753

Post by bee_rider »

mbgerring wrote: post #101
bee_rider wrote: post #92

Earlier quoted context omitted.

I never really get the cryptocurrency comparison. AI has an application beyond grift. Like, even if they stopped developing it now, an AI “style hints” in the style of spellcheck and grammar rule check would be a no-brainer as a thing to add to an office suite. The valuations are totally and completely nuts. But, LLMs have little legitimate applications in a way that cryptocurrencies never will.

Also I’m going to go ahead and say that “it’s slightly better than classical NLP for grammar check but requires 10,000x as much compute resources” is not an improvement

The models are already trained… is inference so costly? It’s just a dot product or a matvec or something, right?

Re: LLM Inevitabilism

#754

Post by magic_hamster »

lsy wrote: post #63

I think two things can be true simultaneously: 1. LLMs are a new technology and it's hard to put the genie back in the bottle with that. It's difficult to imagine a future where they don't continue to exist in some form, with all the timesaving benefits and social issues that come with them. 2. Almost three years in, companies investing in LLMs have not yet discovered a business model that justifies the massive expen…

There are pretty hidden assumption in this comment. First of all, not every business in the AI space is _training_ models, and the difference between training and inference is massive - i.e. most businesses can easily afford inference, perhaps depending on model, but they definitely can.

Another several unfounded claims were made here, but I just wanted to say LLMs with MCP are definitely good enough for almost every use case you can come up with as long as you can provide them with high quality context. LLMs are absolutely the future and they will take over massive parts of our workflow in many industries. Try MCP for yourself and see. There's just no going back.

Re: LLM Inevitabilism

#755

Post by CyanLite2 »

Article assumes LLMs stay where they currently are or progress only incrementally.

Many Fortune 500 companies are seeing real productivity gains through Agentic Workflows to reduce paperwork and bureaucratic layers. Even a marginal 1% improvement can be millions of dollars for these companies.

Then you have an entire industry of AI-native startups that can now challenge and rival industry behomeths (OpenAI itself is now starting to rival Google/Microsoft/Amazon and will likely be the next "BigTech" company).

Re: LLM Inevitabilism

#756

Post by dontlikeyoueith »

magic_hamster wrote: post #754
lsy wrote: post #63

I think two things can be true simultaneously: 1. LLMs are a new technology and it's hard to put the genie back in the bottle with that. It's difficult to imagine a future where they don't continue to exist in some form, with all the timesaving benefits and social issues that come with them. 2. Almost three years in, companies investing in LLMs have not yet discovered a business model that justifies the massive expen…

There are pretty hidden assumption in this comment. First of all, not every business in the AI space is _training_ models, and the difference between training and inference is massive - i.e. most businesses can easily afford inference, perhaps depending on model, but they definitely can. Another several unfounded claims were made here, but I just wanted to say LLMs with MCP are definitely good enough for almost every…

> I just wanted to say LLMs with MCP are definitely good enough for almost every use case you can come up with as long as you can provide them with high quality context.

This just shows you lack imagination.

I have a lot of use cases that they are not good enough for.

Re: LLM Inevitabilism

#757

Post by scubbo »

gopalv wrote: post #130
scubbo wrote: post #83

Earlier quoted context omitted.

> Hours of time saved Come back in a week and update us on how long you've spent debugging all the ways that the code was broken that you didn't notice in those 15 minutes. Usually I don't nitpick spelling, but "mimnutes" and "stylisitic" are somewhat ironic here - small correct-looking errors get glossed over by human quality-checkers, but can lead to genuine issues when parsed as code. A key difference between your…

> Come back in a week and update us on how long you've spent debugging all the ways that the code was broken that you didn't notice in those 15 minutes. I was a non believer for most of 2024. How could such a thing with no understanding write any code that works. I've now come to accept that all the understanding it has is what I bring and if I don't pay attention, I will run into things like you just mentioned. Just…

> I was being sold a "self driving car" equivalent where you didn't even need a steering wheel for this thing, but I've slowly learned that I need to treat it like automatic cruise control with a little bit of lane switching.

> Need to keep the hands on the wheel and spend your spare attention on the traffic far up ahead, not the phone.

Now _this_ is a more-balanced perspective!

(And, to be clear - I use AI in my own workflow as well, extensively. I'm not just an outside naysayer - I know when it works, _and when it doesn't_. Which is why unreasonable claims are irritating)

Re: LLM Inevitabilism

#758

Post by blueflow »

xnx wrote: post #725
lsy wrote: post #63

I think two things can be true simultaneously: 1. LLMs are a new technology and it's hard to put the genie back in the bottle with that. It's difficult to imagine a future where they don't continue to exist in some form, with all the timesaving benefits and social issues that come with them. 2. Almost three years in, companies investing in LLMs have not yet discovered a business model that justifies the massive expen…

> (the supersonic jetliner) ... (the microwave oven) But have we ever had a general purpose technology (steam engine, electricity) that failed to change society?

It wouldn't be general purpose if it fails to bring change. I'd take every previous iteration of "AI" as example, IBM Watson, that stuff

Re: LLM Inevitabilism

#759

Post by ramoz »

magic_hamster wrote: post #754
lsy wrote: post #63

I think two things can be true simultaneously: 1. LLMs are a new technology and it's hard to put the genie back in the bottle with that. It's difficult to imagine a future where they don't continue to exist in some form, with all the timesaving benefits and social issues that come with them. 2. Almost three years in, companies investing in LLMs have not yet discovered a business model that justifies the massive expen…

There are pretty hidden assumption in this comment. First of all, not every business in the AI space is _training_ models, and the difference between training and inference is massive - i.e. most businesses can easily afford inference, perhaps depending on model, but they definitely can. Another several unfounded claims were made here, but I just wanted to say LLMs with MCP are definitely good enough for almost every…

LLMs with tools*

MCP isn’t inherently special. A Claude Code with Bash() tool can do nearly anything a MCP server will give you - much more efficiently.

Computer Use agents are here and are only going to get better.

The conversation shouldn’t be about LLMs any longer. Providers will be providing agents.

Re: LLM Inevitabilism

#760

Post by rafaelmn »

gbalduzzi wrote: post #114
rafaelmn wrote: post #24

Earlier quoted context omitted.

If you claimed that AI was inevitable in the 80s and invested, or claimed people would be inevitably moving to VR 10 years ago - you would be shit out of luck. Zuck is still burning billions on it with nothing to show for it and a bad outlook. Even Apple tried it and hilariously missed the demand estimate. The only potential bailout for this tech is AR, but thats still years away from consumer market and widespread a…

None of the "failed" innovations you cited were even near the adoption rate of current LLMs. As much as I don't like it, this is the actual difference. LLMs are already good enough to be a very useful and widely spread technology. They can become even better, but even if they don't there are plenty of use cases for them. VR/AR, AI in the 80s and Tesla at the beginning were technology that someone believe could become…

OK but what does adoption rate vs. real world impact tell here ?

With all the insane exposure and downloads how many people cant even be convinced to pay 20$/month for it ? The value proposition to most people is that low. So you are basically betting on LLMs making a leap in performance to pay for the investments.

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