Recent comments in /f/singularity

lehcarfugu t1_j95ytw9 wrote

Google is realizing how disruptive chat bots are to its business model. They may want to stifle innovation until they have a gun to their head and forced to release (see bard)

7

Difficult_Review9741 t1_j95y49j wrote

This won't be very popular, but there is a lot of truth.

Remember, "divine spark" doesn't have to be a religious term. Even if consciousness is just a result of our neurons firing in a specific pattern, we still have no clue what this pattern is, and if it can be replicated in machines.

Think about it another way: assume that we have a program that manually defines every possible language input, and every possible language output. From a black box perspective, this would seem every bit as intelligent and "conscious" as a LLM, but anyone understanding the implementation would immediately reject that that this system is intelligent in any way.

The point being, to determine if a system is conscious, we can't simply examine its output. We first have to understand what consciousness is, and we aren't even close to that. There is clearly a lot that separates modern day AI and humans. Yes, humans sometimes predict the statistically likely next token, but that is obviously not how our brain works in the general case.

As these systems become more advanced, it will be harder to assert with certainty that they are not conscious, but anyone trying to claim that they are right now is either being disingenuous or has no idea what they are talking about.

2

Ortus14 t1_j95wz5o wrote

ChatGPT is intelligent in the sense that it has learned a model of the world and uses that to solve problems.

In some ways it's already super human, in other ways humans can do things it can not yet do.

4

Feisty-Excitement135 t1_j95s4xc wrote

Over and over I see people saying “it’s not thinking, it was just trained on a large corpus”. I don’t know if it’s intelligent wrt whatever definition you choose, but saying that it’s “just been trained on a large corpus” is not a refutation

5

Representative_Pop_8 t1_j95q67u wrote

i doubt any company wants to create a conscious machine right now, since as seen by Bing the moment some people right or wrong assign it sentience is the moment you start getting discussions about regulating " rights " for AI systems , that is not good for something you wish to use as a usefully tool.

we couldnt really don't know what causes consciousness either so we wouldn't know how to make a conscious machine and be sure it is conscious if we wanted to, other than recreating a human brain molecule by molecule.

Now consciousness could well be something that can be made with a machine of different construction than a human brain, but we've don't know the method that does that. Due to this lack of knowledge , even though unlikely, we can't even truly completely rule out that a thing like chatGPT could be sentient( but I don't think it is)

2

maskedpaki t1_j95p4jb wrote

Bringing another AI as an analogy as to why your assertion that "if it makes money it could kill us " is false is not taking things out of context. Its like just a way of showing you that you were wrong about AIs being able to kill us just because they can make money because we have AIs that make money and like have not killed us.

​

with all that said I do believe in AI doom.

1

zesterer t1_j95owhm wrote

There's nothing in your example that demonstrates actual reasoning: as I say, GPT-3's training corpus is enormous, larger than a human can reasonably comprehend. Its training process was incredibly good at identifying and extracting patterns within that data set and encoding them into the network.

Although the example you gave is 'novel' in the most basic sense, there's no one part of it that is novel: Bing is no more reasoning about the problem here than a student is that searches for lots of similar problems on Stack Overflow and glues solutions together. Sure, the final product of the student's work is "novel", as is the problem statement, but that doesn't mean that the student's path to the solution required intrinsic understanding of that process when such a vast corpus is available to borrow from.

That's the problem here: the corpus. GPT-3 has generalised the training data it has been given extremely well, there's no doubt about that - so much so that it's even able to solve tasks that are 'novel' in the large - but it's still limited by the domains covered by the corpus. If you ask it about new science or try to explain to it new kinds of mathematics, or even just give it non-trivial examples of new programming languages, it fails to generalise to these tasks. I've been trying for a while to get it to understand my own programming language, but it constantly reverts back to knowledge it has from its corpus, because what I'm asking it to do does not appear within its corpus, either explicitly or implicitly as a product of inference.

> ... you actually believe only biological minds are capable of reasoning

Of course not, and this is a strawman. There's nothing inherent about biology that could not be replicated digitally with enough care and attention.

My argument is that GPT-3 specifically is not showing signs of anything that could be construed as higher-level intelligence, and that its behaviours - as genuinely impressive as they are - can be explained by the size of the corpus it was trained on, and that - as human users - we are - misinterpreting what we're seeing as intelligence when it is in fact just a statically adept copy-cat machine with the ability to interpolate knowledge from its corpus to cover domains that are only implicitly present in said corpus such as the 'novel' problem you gave as an example.

I hope that clarifies my position.

1

airduster_9000 t1_j95nbix wrote

https://www.deepmind.com/publications/a-generalist-agent

Published
November 10, 2022

Abstract
Inspired by progress in large-scale language modeling, we apply a similar approach towards building a single generalist agent beyond the realm of text outputs. The agent, which we refer to as Gato, works as a multi-modal, multi-task, multi-embodiment generalist policy. The same network with the same weights can play Atari, caption images, chat, stack blocks with a real robot arm and much more, deciding based on its context whether to output text, joint torques, button presses, or other tokens. In this report we describe the model and the data, and document the current capabilities of Gato.

Conclusions
Transformer sequence models are effective as multi-task multi-embodiment policies, including for real-world text, vision and robotics tasks. They show promise as well in few-shot out-of-distribution task learning. In the future, such models could be used as a default starting point via prompting or fine-tuning to learn new behaviors, rather than training from scratch.Given scaling law trends, the performance across all tasks including dialogue will increase with scale in parameters, data and compute. Better hardware and network architectures will allow training bigger models while maintaining real-time robot control capability. By scaling up and iterating on this same basic approach, we can build a useful general-purpose agent.

3

Lawjarp2 t1_j95l76s wrote

There is no divine spark. Infact these models are proof that it doesn't take much to get close to being considered conscious.

The fact that you compare it with a pig shows you don't know much about them and probably shouldn't be advising people. These models are trained on text data only and do not have a physical or even an independent existence to have sentience.

Even if they just gave it episodic memory it will start to feel a lot more human than some humans.

16