I doubt current models from China are trained to do smart spying / injecting sneaky tool calls. But based on my Deep Learning experience with the models both training and inference, it's definitely possible to train a model to do this in a very subtle and hard to detect way...

So your point is valid and I think they should specify the base model for security concerns, or conduct safety evaluations on it before passing it to sensitive customers

> an LLM or any other computational neural net is no different from a program like that

I don't think so. A program doesn't exhibit highly complex abstract thought in a very high-dimensional space.

> It’s executing deterministic instructions, like a machine, because it is a machine

Its true that LLMs are deterministic. But do you really think that the magic behind the brain is only due to temperature and randomness? Do you really think that non-deterministic behavior is the magic ingredient that makes up what we are referring to as consciousness? I could inject noise into an LLM at every parameter dynamically during inference. The output would come out just fine. After all, LLMs are high dimensional and can handle a little noise. Would it really be more conscious after that? You can find experiments where people remove entire layers of the LLM and it still works fine. A little noise would be even less harmful than that.

You see, when I'm arguing, I'm not citing what some other person said. I at most will cite experiments from other people and their results. When I am contradicting your arguments, I present you a reality you can go and try in the real world and verify. You can go verify yourself LLMs exhibit complex high-dimensional thought. You can verify yourself that if you inject noise dynamically through inference on every parameter, you still get coherent output from the LLM.

So, if you are willing to continue this discussion, I ask of you that you present some sort of "probing" of the real world and the respective "reaction" of the same real world as arguments. That is what finding the truth means.

And lastly. I am presenting a Theory. This means I believe that my points form a foundation that makes my theory stronger than yours. It means I have better evidence that backs it up. It doesn't mean I have proved what consciousness is. Instead, it primarily means I can make more accurate predictions using my theory on real world scenarios involving artificial and biological neural networks. And my personal experience shows me that is true.

As if it doesn't cost tens of millions to pre-train a model. Not to mention the time it takes. Do you want them to stall progress for no good reason?

This platform has the EXACT same problem as Reddit. People can just silence you before you had a chance of discussion. What a waste of fucking time. Instead of improving our world models of reality by having discussions, you can just silence others because you disagree. Remove the fucking downvote button! Just remove it, jesus fucking christ. Who thought this button was a good fucking idea?

I'm nearly out of this garbage. The same way I left Reddit long ago. X is the only platform that allows free speech.

They did so legally and didn't break any rules. This is the game of capitalism, and the fact is, IOS and Android are extremely well built and developed, and no open-source project would ever come close to the hundreds of thousands of paid engineers that built IOS and Android.

You can either have capitalism and IOS and Android, or you can have communism and a society that is 10+ years behind in development. Do you really want to give up IOS 26 for a blackberry?

The developers need to get paid. And the developers only get paid if the system is closed-source such that the revenue can only flow back to Google which is where the developers are hired at. In other words, yes it needs to be centralized, and the reason is the money required to build Android is just too much and therefore needs to be developed under a for-profit capitalist organization like Google.

Android on the other hand is developed by thousands of engineers and is a much larger project in terms of monetary investment than Linux. Linux was essentially built by a single guy. Android could never have been built by a single person or even a open-source project. It's too massive.

However complex you think Linux is, its just a kernel and doesn't require a conglomerate to build and maintain for billions of users. Android does, and those developers need to get paid for the massive value they provide.

Anything that reaches a certain threshold of value to society and requires enormous effort to build and maintain has to fall back to a capitalist, for-profit, closed-source structure. That's all that's happening here.

Of course, small stuff like a software library that doesn't require much effort to build and doesn't provide much value can remain open-source. I personally think this obsession with open-source software is simply an obsession with communism and getting things for free, and not wanting getting rewarded for the value of the stuff you build, etc.

What they can do is, for everyone, have a base model, and then improve it over time. Then, with software updates they can improve the set of skills the robot can handle out of the box.

But this is the problem with current AI systems, without a continuous learning capability, you're always limited to the "default skills". As soon as you have something out of the box for the robot to do, you end up needing Indians to learn it.

All of AI is flawed in this way. LLMs for instance have almost no continuous learning capability, that is why we don't have AGI yet. They can't learn new skills. Therefore, they can't adapt to new jobs they have not seen during training. They can't even play pokemon properly or any complex game for that matter, because games involve learning new skills during gameplay.

If the goal is to get the job done, then use AI.

Do you really want to waste precious time for so little return?

Even though complex output can be deceptive of the underlying mental model used to produce it, in my personal experience, LLMs have produced for me output that must imply extremely complex internal behaviour, with all the characteristics I mentioned before. Namely, I frequently program with LLMs, and there is simply zero percent probability that their output tokens exist WITHOUT first having thought at a very deep level about the unique problem I presented to them. And I think anyone that has used the models to the level I have, and interacted with them this extensively, knows that behind each token there is this black magic.

To summarize, I am not being naive by saying I believe everything my LLM says to me. I rather know very intimately where the LLM is deceiving me and when its producing output where its mental model must have been very advanced to do so. And this is through personal experience playing with this technology, both inference and training.

[1] https://www.anthropic.com/research/tracing-thoughts-language...

In essence, I think it doesn't matter that the brain has a whole bunch of chemistry added into it that artificial neural networks don't. The underlying deep non-linear function mapping capability is the same, and I believe this depth is, in both cases, comparable.

AGI is not here with LLMs, but its not because they lack reasoning ability. It's due to something different. Here is what I think is truly missing: continuous learning, long term memory, and infinite and efficient context/operation. All of these are tied together deeply, and thus I believe we are but a simple breakthrough away from AGI.