Live data from Hacker News

The Generative AI Con

wheresyoured.at

401–410 of 503 posts

Re: The Generative AI Con

#401
post #104

Earlier quoted context omitted.

I think that's an unfair comparison. If the IBM Simon disappeared in 1994, I'm pretty sure you wouldn't have cared. If search engines disappeared in 1992, you'd have felt the same. Also, (what later became) AWS probably didn't interface much with you in 2003. It takes some time for technology to mature, usually at least a decade or two. Even once the iPhone was released it took a few years until it became indispensab…

I remember when people commented here that the blockchain was the same as early google search or early aws or early iPhone. Everyone thinks their new thing is the T-1.

I spent a moment with my brain froze up apparently trying to remember when the first Terminator was supposedly deployed in one of the timelines.

Then I realized the reference was to the "Model T" car. Somehow in my brain the token for "Model" is actually necessary for the correct lookup.

Re: The Generative AI Con

#402
post #218

Earlier quoted context omitted.

This is the crux. A cool thing has been invented, with real usages. Unfortunately, it's cost hundreds of billions of dollars and it has absolutely zero hope of making the trillions needed to justify that. Now someone will respond about how it's just a stepping stone, and how the billions are justified by _something completely imaginary, and not invented yet, and maybe not ever_ e.g. agents.

I see it a little differently. What was the direct economic return of the Manhattan Project?

[deleted]

Re: The Generative AI Con

#403

LLMs write code. Quickly. That is a killer app. Performance improves every year, and costs become 3x-10x lower every year for the same level of performance. The difficulty of the code we want it to write does not increase 3x-10x per year. So there is no cost problem in just a couple years. The level of denial and anger about LLMs on HN is astounding to me. Is this just defensiveness from software engineers worried ab…

Extrapolating trends mostly doesn't work like that, it's very possible that the growth will slow down.

Re: The Generative AI Con

#404

Earlier quoted context omitted.

That experience is heavily subsidized and is unprofitable for these companies providing it based on what we know. Even with all of the other developers who are also using the same work flow and espousing how great it is. Even with all of the monthly subscribers at various tiers. It has been unprofitable for several years and continues to be unprofitable and will likely remain unprofitable given current trends. The au…

It is unprofitable because they keep spending money developing new AI. Inference for existing AI is not unprofitable.

For now.

Unless closed models have significant advantage AI inference will be a commodity business - like server hosting.

I'm not sure that closed models will maintain an advantage.

Re: The Generative AI Con

#405
post #214

Earlier quoted context omitted.

This is moving the goalpost on what "killer app" means. Code assistants are a compelling use of the tech that has quickly shown real-world value, which is the point I'm trying to make here. Whether the companies that are leading the market today will end up being the ones who capture that value is anyone's bet.

I fail to see how a technology that is to expensive to maintain can have a killer app.

It’s only going to get cheaper over time. It’s already cheap enough that if these services disappeared overnight I’d switch to an open source alternative with a local model. The industry needed VC backing to pay the fixed cost of the research, but the cost of running inference is not insane compared to the volume it provides.

Re: The Generative AI Con

#406
post #104
post #91

If my Android (or IPhone) disappeared tomorrow, I would feel like I time traveled back a century. If Google search was gone, I wouldn't be able to do my job anymore. If the cloud disappeared, I wouldn't be able to build apps anymore. There are no workarounds, unless you feel like going to a library...? If ChatGPT disappeared tomorrow (or derivatives like Copilot, etc.), I would be mildly inconvenienced. Then I'd go b…

I think that's an unfair comparison. If the IBM Simon disappeared in 1994, I'm pretty sure you wouldn't have cared. If search engines disappeared in 1992, you'd have felt the same. Also, (what later became) AWS probably didn't interface much with you in 2003. It takes some time for technology to mature, usually at least a decade or two. Even once the iPhone was released it took a few years until it became indispensab…

Did you read the article? The author spends a LONG time going over why it's not early days for LLMs.

Here: https://www.wheresyoured.at/longcon/#:~:text=Also%2C%20uhm%2...

Re: The Generative AI Con

#407
post #67

I always wonder how LLMs will achieve superintelligence when they are, by definition, average.

This is incorrect. If you take the most basic interpretation of an LLM at temperature 0 as predicting the most likely token, and you run it on, say, 1,000 runs of "complete this Spanish sentence with the word for 'X'", then: - maybe ALL humans would fail the test in some way, eg. let's say everybody gets at least 10 of those wrong, and the average person gets 100 of those wrong. - still, as long as most people correc…

But still, the questions in that test are "solved" in the sense of "I can take a dictionary and answers these questions with full certainty". Beyond established knowledge LLMs are monkeys with typewriters, at best.

Re: The Generative AI Con

#409

Earlier quoted context omitted.

I don't know how to tell you this, but the government isn't a business and has completely different objectives and operating conditions

If more people understood this we might have avoided the carnage happening in the US right now.

I don't know why it is so hard to understand. I mean money doesn't really exist without a government[0] and while government plays a role in the market and economy, this role is VERY different than that of a business. A government isn't trying to "make money", is isn't trying to make investors happy, and it certainty can't take existential risks that could make "the company" go bankrupt (or it shouldn't lol).

But I do think (and better understand) there is a failure to understand this at a higher abstraction. One part is simply "money is a proxy." This is an uncontestable fact. But one must ask "proxy for what?" and I think people only accept the naive simple answer. Unfortunately, this "is a proxy" concept is extremely generalization. Everything is an estimation, everything is an approximation, and most things are realistically intractable. We use sibling problems or similar problems to work with that are concrete, but there are always assumptions made and ignoring these can have disastrous consequences. Approximations are good (they're necessary even) but the more advanced a {topic,field,civilization,etc} gets, the more important it is to include higher order terms. Frankly, I don't think humans were built for that (though by some miracle we have the capacity to deal with it).

My partner and her dad are both economists, and one thing I've learned is that what many people think are "economics questions" are actually "business questions". I think a story from her dad makes this extremely clear. A government agency hired him to look at the cost benefit analysis of some stuff (like building a few hospitals and some other unambiguously beneficial institutions), and when he presented everyone was happy but had a final question "should we build them?" The answer? "That's not the role of an economist." The reason for this is because money can't actually be accurately attributed to these things. You can project monetary costs for construction, staffing, and bills, and you can make projections about how many people this will benefit, how it can reduce burdens elsewhere, and as well as make /some/ projections about potential cost savings. But you can't answer "should you." Because the weight of these values is not something that can be codified with any data. It is an importance determined by the public and more realistically their representatives. Very few times can you give a strong answer to a question like "should we build a new hospital" and essentially in only the extreme cases. I'll give another example. In my town there was an ER that was closed due to budget constraints. This ER was across the street to the local university, which students represent ~15% of the population. The next nearest ER? A 15 minute ambulance ride away and in the next town over. Did the city save money? Yes. Did the sister city's ER become even busier? Also yes. Did people lose access to medicine? Yes. Did people die? Also yes. Have economists put a price on human life? Also yes, but they are very clear that this is not a real life and a very naive assumptions[1]. It is helpful in the same way drawing random squiggles on a board can help a conversation. Any squiggles can really be drawn but the existence of _something_ helps create some point to start from.

[0] okay crypto bros, you're not wrong but low volatility is critical as well as some other aspects. Let's not get off topic

[1] https://www.npr.org/2020/04/23/843310123/how-government-agen...

Re: The Generative AI Con

#410

>iPhone fundamentally redefined what a cellphone and a portable computer could be, as did the iPad, creating entirely new consumer and business use cases almost immediately. >So, what exactly has generative AI actually done? Where are the products? No, really, where are they? What's the product you use every day, or week, that uses generative AI, that truly changes your life? If generative AI disappeared tomorrow — a…

My concern is when you've implemented it and rely on it and then the company providing the service pulls a "Google" and deprecates the project. I haven't seen that mentioned in any of the comments.

This is the same issue that would happen with any closed source software, and why the push for fully open source or at least "semi" open source models (which provide the weights but not the training data). If you are critically dependent on software that can just disappear for reasons out of your control, you're beholden to its developers.

On the flip side I feel that this is the big problem with monetizing AI. AI is already bad enough in that its output is practically always untrusted output, so any customer-facing application of AI requires a second AI to make sure the first AI didn't output anything improper to consumers or even children (because parents are okay with an app that just tells their children randomly generated text, apparently).

It would be a little better if you had control over the model. But without a intellectual property rights over the model, what is the AI company even selling? A GUI? So anyone can just copy and paste the model, skip all the training costs, and just sell a react frontend for the model trained for billions of dollars?

It feels like you can't make money from training the AI in a way that makes sense for customers, but you can make money from selling the AI that someone else trained by selling access to it for non-technical users.

Post reply on HN