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> The current GPT models are not going to "wake up" or accidentally take over the world. This is very obvious.

It's pretty obvious that GPT-4 isn't consistently coherent enough to carry out complex plans or to do serious scientific research. There are several other major shortcomings which also prevent this from being viable, too. And of course, it's possible that some of these shortcomings are very hard to "fix." We've had AI winters before, and self-driving seems to have stalled.

However, I strongly suspect that it's theoretically possible to build a machine that "thinks" as well as a human. And I no longer have any solid idea how far we are from that point, especially if we make certain architectural changes. We might be closer than we think. Or at least we should stop assuming that next-gen models are obviously safe.

nVidia's hope to increase training performance 1 million times in 10 years seems potentially dangerous to me. Anthrophic's plan to spend over $1 billion training next gen models seems awfully sketchy as well.

Self driving, I think is where we got it backwards. To drive correctly we need AGI because 'uncommon' but not 'rare' events are avoided by drivers all the time and in a manner you have to understand how the world works and how people think.

LLMs, especially the multi-modal ones go much further to making self driving possible, that is if we ever get to the point they can incorporate and act on data fast enough. We may still have a hardware problem for some time there.

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But on your second point I am with you. There is nothing obvious about at what level emergent behavior occurs in the models. Just keep adding parameters and new things keep popping out with no real means to determine where and when seems kinda sketch as we push these things past the exa scale.

> However, I strongly suspect that it's theoretically possible to build a machine that "thinks" as well as a human

Not any time soon. Modern "AI" research built on completely wrong assumptions about how neurons work from the middle of XX century. It turned out they are much more complex than that (long story short every single neuron is analogous to the "neural network" as AI researchers understand them). See more at https://www.youtube.com/watch?v=hmtQPrH-gC4

Why would you think that the machine implementation of “thinking” would need to mimic the biological implementation?

Your brain does 1+1 = 2 very differently than an integrated circuit, but the end output is the same.

Because it shows that real brain complexity is much larger than we thought, which means AGI is farther down the road.

>Executing "arbitrary code" that InstructGPT models outputs based on your instructions is not a danger.

This is a grossly irresponsible and categorically false statement, in very obvious ways.

Why would ChatGPT provide me with dangerous code if I prompt it benignly? I just the other day used ChatGPT to create a webscraper for a friends project and it provided me with an only slightly wrong implementation to scrape data from a specific website. 15 minutes of reviewing the code and editing literally three lines and I was done. Unless it was trained on a bunch of webscraping code that also contained malicious code I just don't see how it could happen.

If anything they could enable an option to have ChatGPT review the code for you and let you know that it hasn't accidentally thrown in some fishy code.

>Why would ChatGPT provide me with dangerous code if I prompt it benignly?

Because it's a black box that's sensitive to unexpected inputs. Humans create bugs too, but an unaligned AI doesn't have the sense to be careful of certain classes of bug.

The burden of proof for executing arbitrary code as input should always be on proving that it doesn't violate your security or reliability model. You shouldn't need to assume anything about that code other than that you're able to configure the runtime before it executes. Whether it comes from ChatGPT or users shouldn't matter, you should assume some of those programs were written by hackers and that you don't know which ones.

Even if you trust ChatGPT you should do this. You should assume that one day the hackers will intercept your connection to OpenAI and hand you malware, and they should either fail or be forced to use a zero day exploit against eg Firecracker (modulo your threat model and such).

> In my opinion this type of comment is the core problem with AI alignment these days. [...] The current GPT models are not going to "wake up" or accidentally take over the world. This is very obvious. [...] Executing "arbitrary code" that InstructGPT models outputs based on your instructions is not a danger.

I meant to comment on the security aspects of sending confidential information to models and letting them generate output that will be immediately executed on your own machine. People also chain models together and let them generate output that will be interpreted as the next model's input. If done without guardrails, this is done ideally in a sandboxed environment.

Too often, I see this type of code just ran on one's machine. As the projects attract less technical people, they may not be aware of the dangers of running such code locally and can see a portion of their data being wiped or exposed.

The current GPT models are not going to "wake up" or accidentally take over the world. This is very obvious.

Was it obvious to you that you’d see a paper called “Sparks of an AGI” after the release of ChatGPT 4 ?

Not the poster you asked the question to but:

I think we are going to be building and using 'sub-AGI' models for a very long time, probably well after we (probably achieve) full AGI. I think these 'sub-AGI' models are going to radically change the way we think about intelligence in the sense that we are going to be better able to nail down what we find special about human intelligence while at the same time discovering that it is a narrow and somewhat arbitrary subset of what we consider advanced intelligence.

ChatGPT seems to me like a very advanced Markov chain, which isn't to denigrate it, the surprising part is how useful and effective it is which to me shows we have been thinking about intelligence the wrong way. IMO an important portion of our brain probably works in a very analogous way but you could build as advanced a version of ChatGPT as you like and it wouldn't become 'sentient' or go HAL9000 on us.

There is definitely a danger of someone taking ChatGPT9 and telling it to create you computer viruses to take down digital infrastructure or telling it to trade in a way to crash the stock market but that's going to happen when all the zero-day exploits are detonated in the lead up to WW3 anyways and all things considered that has a higher chance of happening sooner than ChatGPT9 or the equivalent is used to do it. Instead of getting worried over rogue AI we should probably just harden our infrastructure.

Hardening infrastructure is a trillion dollar problem that a huge number of people don't believe in, or believe it's a waste of money to spend even more on. And that is before we make cutting edge thinking machines that could attack it.

Also, a paperclip maximizer could in theory go 'HAL' on you without intent or malice. Sentience isn't needed. And at the same time as we're working on embodiment models, what we could consider human like sentience could be far closer than we expect.

I think unfortunately my comment got some upvotes based on an imprecise interpretation of what I actually said. Probably if people understood what I was actually saying it would have been buried.

Also part of the problem is the word AGI and having total conflation inside of that.

I meant SPECIFICALLY the current GPT versions and architecture.

In my opinion, GPT-4 is extremely intelligent in a very general way and this is incredibly obvious.

What GPT-4 is NOT, by itself, is autonomous, or many other human/animal characteristics that people conflate with intelligence.

GPT does not have full autonomy. It is not a person. It is not alive. It does not feel. It does not form its own goals. It does not feel, or have survival instincts, or a high bandwidth stream of sensory data. In these and other ways it is quite different from animals and people. It is not a digital person.

However, people are quite stupidly moving forward with trying to create digital people that imitate all animal characteristics, apparently with the idea that they will enslave them, with the thought process being that they will not be able to do useful work without having all of these animal (human) characteristics.

Besides that problem, people are not taking into account the different levels of speed and other performance measurements of the future systems. Future quite possibly being this year. Or especially I think it is critical for the new compute-in-memory substrates or any advances that increase the speed or other IQ measurements beyond say one order of magnitude of human to be highly regulated. Systems that are twice as smart and say 100 times faster at thinking than humans absolutely can be dangerous.

We achieved the architecture for general purpose intelligence in 2017 and in 2018 I suggested we would have AGI in 2019. Unfortunately now AGI is quite vague and means things like digital person or digital God..I wrote quite a lot but unfortunately deleted some of the explanation.

General intelligence versus personhood or Godhood or alive, or autonomous or having survival instincts or instant adaptability etc. are not the same thing.