> One difference between humans and LLMs is that humans have a wide range of inputs and outputs beyond language.
So does Bing and multimodal models.
> The claim that humans are word predictors is not something I would want to dispute.
We have forward predictive models in our brains, see David Eagleman.
> The claim that humans are nothing more than word predictors is obviously wrong though. When I go to buy food, it's not because I'm predicting the words "I'm hungry". It's because I'm predicting that I'll be hungry.
Your forward predictive model is doing just that, but that's not the only model and circuit that's operating in the background. Our brains are ensembles of all sorts of different circuits with their own desires and goals, be it short or long term.
It doesn't mean the models are any different when they make predictions. In fact, any NN with N outputs is an "ensemble" of N predictors - dependent with each other - but still an ensemble of predictors. It just so happens that these predictors predict tokens, but that's only because that is the medium.
> fully understanding the meaning of language.
What does "fully" mean? It is well established that we all have different representations of language and the different tokens in our heads, with vastly different associations.
I'm not talking about getting fed pictures and videos. I'm talking about interacting with others in the physical world, having social relations, developing goals and interests, taking the initiative, perceiving how the world responds to all of that.
>What does "fully" mean?
Being able to draw conclusions that are not possible to draw from language alone. The meaning of language is not just more language or pictures or videos. Language refers to stuff outside of itself that can only be understood based on a shared perception of physical and social reality.
For all intents and purposes your brain might as well be a Boltzmann brain / in a jar getting electrical stimuli. Your notion of reality is a mere interpretation of electrical signals / information.
This implies that all such information can be encoded via language or whatever else.
You also don’t take initiative. Every action that you take is dependent upon all previous actions as your brain is not devoid of operations until you “decide” to do something.
You merely call the outcome of your brain’s competing circuits as “taking initiative”.
GPT “took initiative” to pause and ask me for more details instead of just giving me stuff out.
As for the latter, I don’t think that holds. Language is just information. None of our brains are even grounded in reality either. We are grounded in what we perceive as reality.
A blind person has no notion of colour yet we don’t claim they are not sentient or generally intelligent. A paraplegic person who lacks proprioception and motor movements is not “as grounded” in reality as we are.
> You merely call the outcome of your brain’s competing circuits as “taking initiative”.
We give names to all kinds of outcomes of our brains competing circuits. But our brains competing circuits have evolved to solve a fundamentally different set of problems than an LLM was designed for: the problems of human survival.
> A blind person has no notion of colour yet we don’t claim they are not sentient or generally intelligent.
Axiomatic anthropocentrism is warranted when comparing humans and AI.
Even if every known form of human sensory input, from language to vision, sound, pheromones, pain, etc were digitally encoded and fed into its own large <signal> model and they were all connected and attached to a physical form like C3PO, the resulting artificial being - even if it were marvelously intelligent - should still not be used to justify the diminishment of anyone's humanity.
If that sounds like a moral argument, that's because it is. Any materialist understands that we biological life forms are ultimately just glorified chemical information systems resisting in vain against entropy's information destroying effects. But in this context, that's sort of trite and beside the point.
What matters is what principles guide what we do with the technology.
> We give names to all kinds of outcomes of our brains competing circuits. But our brains competing circuits have evolved to solve a fundamentally different set of problems than an LLM was designed for: the problems of human survival.
Our brain did not evolve to do anything. It happened that a scaled primate brain is useful for DNA propagation, that's it. The brain can not purposefully drive its own evolution just yet, and we have collectively deemed it unethical because a crazy dude used it to justify murdering and torturing millions.
If we are being precise, we are driving the evolution of said models based on their usefulness to us, thus their capacity to propagate and metaphorically survive is entirely dependent on how useful they are to their environment.
Your fundamental mistake is thinking that training a model to do xyz is akin to our brains "evolving". The better analogy would be that as a model is training by interactions to its environment, it is changing. Same thing happens to humans, it's just that our update rules are a bit different.
The evolution is across iterations and generations of models, not their parameters.
> should still not be used to justify the diminishment of anyone's humanity.
I am not doing that, on the contrary, I am elevating the models. The fact that you took it as diminishment of the human is not really my fault nor my intention.
The belief that elevating a machine or information to humanity is the reduction of some people's humanity or of humanity as a whole, is entirely your issue.
From my perspective, this only shows the sheer ingenuity of humans, and just how much effort it took for millions of humans to reach something analogous to us, and eventually build a potential successor to humanity.
> The belief that elevating a machine or information to humanity is the reduction of some people's humanity or of humanity as a whole, is entirely your issue.
It's not just my issue, it's all of our issue. As you yourself alluded to in your comment implying the Holocaust above, humans don't need much of a reason to diminish the humanity of other humans, even without the presence of AIs that marvelously exhibit aspects of human intelligence.
As an example, we're not far from some arguing against the existence of a great many people because an AI can objectively do their jobs better. In the short term, many of those people might be seen as a cost rather than people who should benefit from the time and leisure that offloading work to an AI enables.
> As an example, we're not far from some arguing against the existence of a great many people because an AI can objectively do their jobs better.
We are already here.
The problem is that everyone seems to take capitalism as the default state of the world, we don't live to live, we live to create and our value in society is dependent on our capacity to produce value to the ruling class.
People want to limit machines that can enable us to live to experience, to create, to love and share just so they keep a semblance of power and avoid a conflict with the ruling class.
This whole conundrum and complaints have absolutely nothing to do the models' capacity to meet or surpass us, but with fear of losing jobs because we are terrified of standing up to the ruling class.
>You also don’t take initiative. Every action that you take is dependent upon all previous actions as your brain is not devoid of operations until you “decide” to do something.
So does Bing and multimodal models.
> The claim that humans are word predictors is not something I would want to dispute.
We have forward predictive models in our brains, see David Eagleman.
> The claim that humans are nothing more than word predictors is obviously wrong though. When I go to buy food, it's not because I'm predicting the words "I'm hungry". It's because I'm predicting that I'll be hungry.
Your forward predictive model is doing just that, but that's not the only model and circuit that's operating in the background. Our brains are ensembles of all sorts of different circuits with their own desires and goals, be it short or long term.
It doesn't mean the models are any different when they make predictions. In fact, any NN with N outputs is an "ensemble" of N predictors - dependent with each other - but still an ensemble of predictors. It just so happens that these predictors predict tokens, but that's only because that is the medium.
> fully understanding the meaning of language.
What does "fully" mean? It is well established that we all have different representations of language and the different tokens in our heads, with vastly different associations.