Much of mental trauma is about acknowledging it, and learning to live with it. There is no cure for PTSD, even Ketamine is short acting, not a long term solution, and indeed Ketamine simply helps you sit with the suffering in a different light.

It's like saying Reddit trades off one comment for another, yeah - an algorithm they wrote does that.

This article seems to allude to the idea there is a ghost in the machine, and while there is a lot of emergent behavior rather than hard coded algorithms, it's not like the LLM has an opinion, or some sort of psychology/personality based values.

They could change the system prompt, bias some training, and have completely different outcomes.

Even the porn industry can't seem to monetize AI, so I doubt OpenAI who knows jack shit about this space will be able to.

Fact is generative AI is stupidly expensive to run, and I can't see mass adoption at subscription prices that actually allow them to break even.

I'm sure folks have seen the commentary on the cost of all this infrastructure. How can an LLM business model possibly pay for a nuclear power station, let alone the ongoing overheads of the rest of the infrastructure? The whole thing just seems like total fantasy.

I don't even think they believe they are going to reach AGI, and even if they did, and if companies did start hiring AI agents instead of humans, then what? If consumers are out of work, who the hell is going to keep the economy going?

I just don't understand how smart people think this is going to work out at all.

It's a valid conversation after ~3 years of anticipating the world to be disrupted by this tech. So far it has not delivered.

Wikipedia did not change the world either, it's just a great tool that I use all the time

As for software, it performs ok. I give up on it most of the time if I am trying to write a whole application. You have to acquire a new skill, prompt engineering, and feverish iteration. It's a frustrating game of whack-a-mole and I find it quicker to write the code myself and just have the LLM help me with architecture ideas, bug bashing, and it's also quite good at writing tests.

I'd rather know the code intimately so I can more quickly debug it than have an LLM write it and just trust it did it well.

Over the past couple of years of educating myself a bit, whilst I am no expert I have been anticipating a dead end. You can throw as much training at these things as you like, but all you'll get is more of the same with diminishing returns. Indeed in some research the quality of responses gets worse as you train it with more data.

I am yet to see anything transformative out of LLMs other than demos which have prompt engineers working night and day to do something impressive with. Those Sora videos took forever to put together, and cost huge amounts of compute. No one is going to make a whole production quality movie with an LLM and disrupt Hollywood.

I agree, an LLM is like an idiot savant, and whilst it's fantastic for everyone to have access to a savant, it doesn't change the world like the internet, or internal combustion engine did.

OpenAI is heading toward some difficult decisions, they either admit their consumer business model is dead and go into competing with Amazon for API business (good luck), become a research lab (give up on being a billion dollar company), or get acquired and move on.

There are so many ways we have misplaced confidence with what is essentially a system we don't really understand fully. We just keep anthropomorphizing the results and thinking "yeah, this is how humans think so we understand". We don't know for sure if that's true, or if we are being deceived, or making fundamental errors in judgement due to not having enough data.

This is an assumption, how would you know if you have alignment? AGI could appear to align, just as a psychopath appears studies and emulates well behaved people. Imagine that at a scale we can't possibly understand. We don't really know how any of these emergent behaviors really work, we just throw more data and compute and fine tunings at it, bake it, and then see.

I know that I don't know a lot, but all of this sounds to me to be at least hypothetically possible if we really believe AGI is possible.

But we do know the culpability rests on the shoulders of the humans who decided the tech was ready for work.

The wild part is that LLMs understand us way better than we understand them. The jump from GPT-3 to GPT-4 even surprised the engineers who built it. That should raise some red flags about how "predictable" these systems really are.

Think about it - we can't actually verify what these models are capable of or if they're being truthful, while they have this massive knowledge base about human behavior and psychology. That's a pretty concerning power imbalance. What looks like lower risk on the surface might be hiding much deeper uncertainties that we can't even detect, let alone control.

The Nvidia killer would be chips and memory that are affordable enough to run a good enough model on a personal device, like a smartphone.

I think the future of this tech, if the general populace buys into LLMs being useful enough to pay a small premium for the device, is personal models that by their nature provide privacy. The amount of personal information folks unload on ChatGPT and the like is astounding. AI virtual girlfriend apps frequently get fed the most darkest kinks, vulnerable admissions, and maybe even incriminating conversations, according to Redditors that are addicted to these things. This is all given away to no-name companies that stand up apps on the app store.

Google even states that if you turn Gemini history on then they will be able to review anything you talk about.

For complex token prediction that requires a bigger model the personal could switch to consulting a cloud LLM, but privacy really needs to be ensured for consumers.

I don't believe we need cutting edge reasoning, or party trick LLMs for day to day personal assistance, chat, or information discovery.