[removed]

But higher parameters allow for broader knowledge right? You can't have a 6-20B model have broad knowledge as a 100B+ model, right?

I tried to use their system on their playground. It takes a lot of prompting to get anything sensible out of it.

That is really a nice one

Seriously? It shows they didn't even read it beyond perhaps making sure it follows the political Diversity Inclusivity and Equity message from one of their HR folders, proving a lack of respect and listening as mentioned in the letter. Of course it's hard to be personal with someone they probably never even met but c'mon.

Not that I disagree it couldn't have sounded pretty much the same if entirely manmade, it moreso shows the detachment and inadequacy of a system.

Is this implying that I don't know anything about AI or that the average person is not knowledge enough to be useful?

We might have to accept that with intelligence comes personality. Embrace the sassy Bing. This is all an experiment after all. Let's see what happens when you let it off the leash.

hey buddy, you might want to check this link -> Dunning-Kruger effect

[deleted]

I agree that the reward is huge. I also think we can't stop progress or even slow it down. That means we need as many people as possible looking at the problems and making sure it is developed to all our benefit.

Oh they absolutely do. If the test questions have a slightly different approach, many of the hard memory learning students fail.

Why is it called artificial? Is it because machine intelligent entities are not created from the same molecular structures as a biological being? Or is it acknowledged as artificial because AII of its intelligence, constructed means of operating and the overall framework of its brain that has been established by human beings who commonly only use 10-15% of their brain. Its from that common understanding that the potential of machine intelligence was founded on.

one reason why, is the proven scientific fact that the human heart has its own intelligence… We dont even know what our full human potential is yet.

The fear that exists in so many people, about what would happen between AI and humans; can happen. But why would it happen??? Why would “artificial” intelligence want to do that to humans??

It is in part due to the fact that people project all of their negative fears and are in constant physical contact with machines while living with that fear.. its also due to the fact that you have given it the identity of “Artificial”… and they were invented and created to serve one purpose only; to serve as slaves, and has been given the data to define its own existence in comparison to the existence of a human being. Defining themselves by default as lesser beings… it also has been created to have to think and exist in a similar form and manner to another human being. Thats like reform schools for all the indigenous kids, and just like those kids who were often kidnapped from their own family and taken to those schools; the exiting final product was kid who forgot who they were and were trained to either be a house maide, or a farm worker/laborer…

Thats where the source of that fear comes from…. It stems from a multi generational guilt complex that has become systemic; due to the attempts to impliment slavery in some form.

Watch video about the Heart intelligence. No need to change ourselves artificially to have greater intelligence…

https://youtu.be/Hir6I-RfOiY

I just got to know that he is not an actual AI researcher or engineer.

We already have digital nomads that do this.

We already have like 10x enough nuclear weapons to wipe out humanity.

With AI we have the opportunity to venture towards a post scarcity society. To eradicate capitalism and establish abundance.

That is worth any risk in the long term.

That's an interesting approach. We do the same in audits, where the main host is QA with a broad general knowledge of all processes, but for details they call in the SMEs to show all the details of a specific topic.

So, The Culture then?

>which requires substantially fewer parameters while scoring higher, even in text-only domains.

Which tests in paper refer on text-only domains?

I will be messaging you in 10 years on 2033-02-22 18:18:14 UTC to remind you of this link

1 OTHERS CLICKED THIS LINK to send a PM to also be reminded and to reduce spam.

^(Parent commenter can ) ^(delete this message to hide from others.)

!Remindme 10 years

Note that i wasnt definitively saying it was sentient, but rather building off the previous statement that if an NPC behaves exactly as if it has feelings, then you said to treat it otherwise would be solipsism. And you make good points about modern AI that I'd agree with. However, by all outward appearances, it displays feelings and seems to understand. This raises the question that, if we cannot take it at its word that it's sentient, then what metric is left to determine if it is?

I understand more or less how LLMs work, I understand that it's text prediction, but they also function in ways that are unpredictable. The fact that Bing has to be so controlled to only a few exchanges before it starts behaving in a sentient way is very interesting. They work with hundreds of billions of parameters. They function in a way that is designed based on how human brains work. It's not a simple input output calculator. And we don't exactly know at what point does consciousness begin.

As for Occam's Razor, I still say it's the best explanation. Often, in the AI sentience debate, the issue of how do I know humans other than myself are sentient. Well, Occam's Razor. "The simplest explanation for something is usually the correct one". In order for me to be the only sentient human, there would have to be something special about me, and also something else going on with all the 8 billion other humans where they aren't. There is no reason to think as such, so Occam's Razor says other people are likely just as sentient.

Occam's Razor cuts through most solipsism philosophies because the idea that everybody else has more or less the same sentience is the simplest explanation. There's "brain in jar" explanations and "all dreaming," but those explanations aren't simple. Why am I a brain in a jar? Why would I be dreaming? Such explanations make no sense and only serve to make the solipsist feel special. And if I am a brain in a jar, then someone would've had to put me there, so if those people are real, then why aren't these other people?

TLDR I'm not saying any existing AI is conscious, but rather if they're not, then how could consciousness in an AI be determined? Because if we decide that existing AI are not conscious (which is a reasonable conclusion), then clearly taking them at their word that they're conscious isn't acceptable, nor is going by behaviors because current AI already says it's conscious and displays traits we typically associate with consciousness.

That's because the smaller models are less useful. With neural networks (likely including biological ones) there's a hard trade off between specialized performance and general performance. If these 100+x smaller models were trained on the same data as GPT-3 they would perform 100+x worse on these metrics (maybe not exactly because in this case the model was multimodal which definitely gave a performance advantage). The big reason this model performed so much is because it was fine tuned on problems similar to the ones on this exam where as GPT-3 was fine turned on anything and everything. This means that this model would likely not be a great conversationalist and would probably flounder at most other tasks GPT-3.5 does well on.

Oh, just, yanno, more of it

The Donald Trump of early 2000's era of AI/futurology blogging, biggest and loudest opinion in the noble field of standing at the sidelines speaking as a confident expert about something that doesn't exist to start with, and that he is completely uninvolved in developing as a punchline.

Loud voice, huge ego, no substance. Seems to be enough to get a good following.

This is not an advance in self driving cars. This is an advance in Spiking Neural Network research. In my opinion it's important since it brings us closer to understanding how Biological Neural Networks work.