User count going up? Sure.
New browser that will deeply integrate chatGPT into users lives and give OAI access to their browsing/shopping data? Sure
Several new hardware products that are totally coming in the next several months? Sure
We're totally going to start delivering ads? Sure
We're making commitments to all these compute providers because our growth is totally going to warrant it? Sure
Oh, since we're investing in all of that compute, we're also going to become a compute vendor! Sure
None of it is particularly intentional, strategic, or sound. OAI is a money pit, they can always see the end of the runway, and must secure funding now. That is their perpetual state.
We know that they exist, and not only for people with known mental health issues. And that's all we know. But the industry will happily brush that aside in order to drive up those sweet MAU and MRR numbers. One of those, "I'm willing to sacrifice [a percentage of the population] for market share and profit" situations.
Edits: grammar
Do you feel the same about say alcohol and cigarettes? We allow those, heck we encourage those in some situations for adults yet they destroy whole societies (look at russia with alcohol, look at Indonesia for cigarettes if you haven't been there).
I see a lot of points to discuss and study but none to ban with parent's topic.
The issue is it becoming ubiquitous in an effort to make money.
I'm suggesting restraint and responsibility on the part of the organization pushing this. When do we learn that being reactive after the harm is done isn't actually a required method of doing business? That it's okay to slow down even if there's a short-term opportunity cost?
This applies just as much to the push for LLMs everywhere as it does OpenAI's specific intention to support sexbots.
But it's all the same pattern. Push for as much as we can, as fast as we can, at as broad a scale as we can -- and deal with the consequences only when we can't ignore them anymore. (And if we can keep that to a bare minimum, that would be best for the bottom line.)
And if anyone believes the AGI hyperbole, oh boy I have a bridge and a mountain to sell.
LLM tech will never lead to AGI. You need a tech that mimics synapses. It doesn’t exist.
LLMs have their name for a reason: they model human language (output given an input) from human text (and other artifacts).
And now the idea seems to be that when we do more of it, or make it even larger, it will stop to be a model of human language generation? Or that human language generation is all there is to AGI?
I wish someone could explain the claim to me...
And because there's something in the human mind that has a very strong reaction to being talked to, and because LLMs are specifically good at mimicking plausible human speech patterns, chatGPT really, really hooked a lot of people (including said VC/private money people).
It's not that language generation is all there is to AGI, but that to sufficiently model text that is about the wide range of human experiences, we need to model those experiences. LLMs model the world to varying degrees, and perhaps in the limit of unbounded training data, they can model the human's perspective in it as well.
Why would you think synapses (or their dynamics) are required for AGI rather than being incidental owing to the constraints of biology?
(This discussion never goes anywhere productive but I can't help myself from asking)
LLM are really good at pretending to be intelligent but I don't think they'll ever overcome the "pretend" part.
I suspect this may be one of those predictions that may not quite pan out. I am not saying it is a given, but never is about as unlikely.
'Machine will always know where to go from here on now'.
I think _maybe_ quantum computing might be the tech that moves AGI closer. But I'm 99.9999% certain it won't be LLM tech. (Even I can't seriously say 100% for most things, though I am 100% certain a monkey will not fly out of my butt today)
It’s not the hardware, it’s the algorithms.
Like at the moment I think during training new data changes all the model weights which is very compute intensive and makes it hard to learn new things after training. The human brain seems to do it in a more compartmentalised way - learning about a new animal say does not rewrite the neurons for playing chess or speaking French for example. You could maybe modify the LLM algo along those lines without throwing it away entirely.
So you might improve algorithms (by doing matrix multiplications in a different order.... it's always matrix multiplications) but you'll be feeding them junk.
So they need ever increasing amounts of data but they are also the cause of the ever increasing shortage of good data. They have dug their own grave.
I also don't subscribe to that. I'm polyamorous and sex-positive. And very LGBTIQ friendly. But I've seen that attitude a lot even in Europe :( especially from the emerging extreme right parties.
I don't really understand it either. Why is it any of their business what I do? I don't tell them they can't have a big traditional family. Why are they so preoccupied with me.
But don't think conservative ideology/politics is about making their rules your rules. Or at least being bound by their rules. I mean: If Musk doesn't like what someone says, they get blocked from Twitter (or in case of German political parties, downranked, so that the far right is ranking higher/being recommended more often on X). But they (like Musk) claim "free speech" for themselves. Meaning, they want to say what they feel like without consequences.
I found this interesting "law" by Frank Wilhoit:
> Conservatism consists of exactly one proposition, to wit: There must be in-groups whom the law protects but does not bind, alongside out-groups whom the law binds but does not protect.
The thing is if you're not protected you don't really have free speech.
Considering that this is only with verified adults, how is this "evil"? I find it more evil to treat full grown adult users as kids and heavily censor their use of LLMs.
(Not to detract from the rest of your post, with which I agree).