The #FoundationModels of AI (Transformer, LLM, call it whatever) are troublesome, not because they are deficient, but because they are endowed with #emergent behaviours that suddenly spring from 500-billion-plus trainable parameters and terabytes upon terabytes of human behavioural data. No human could grasp the aggregate meaning of that unanticipated, implicit, emergent behaviour. No human could divine the outcomes of their unforeseeable concoctions. Worse of all, all these models are inhered with biases and prejudices, both intentional and unintentional, that are embedded deep within these deep-learning models, whose untoward conducts are ever so subtle and complex as to be casually observable.

The invidious effects of these poorly-understood foundation models are insidious. By the time their detrimental behaviour becomes observable, it would be too late for society to countermand, for these models are already enmeshed within the social-political-economic fabric of the whole of humanity.

It is easy, for a lawyer like me, reflexively to shout, "#Regulate #AI". But in the present heady mix of delirium, confusion, delusion, and collusion, regulate exactly what and precisely how, pray tell.

Who will save society from AI?

Well, perhaps AI might....πŸ€¦β€β™‚οΈ

Matrix multiplication is not inhered with empathy, conscience, judgement, elation, shame, and the like. Those are innately human characteristics, neither mechanical nor mathematical. Let us not surrender to the silicon-based machines the #ethical duty to be thinking, feeling carbon-based beings.

@AmenZwa
> Matrix multiplication is not inhered with empathy, conscience, judgement, elation, shame, and the like.

Ban all matrices!

@dougmerritt 🀣 We have LISP and lists. Who needs MATLAB and matrices!
@AmenZwa so called "AI" is our own productions looping back into our thinking; it's always been that way. I'm more concerned about those who control the reinforcement learning phase, those who decide, provided a set of tokens in the context, what acceptable streams of next tokens are. Who will save society from such powerful players?

@tg9541

$$$$ β†’ bias
πŸ€¦β€β™‚οΈ

@tg9541
I'm with our mutual friend @dougmerrittβ€”ban all matrices!🀣

@AmenZwa right - or, alternatively, let's set a limit to 10^8 parameters ;-)

@dougmerritt

@tg9541 @AmenZwa
> alternatively, let's set a limit to 10^8 parameters

I'll have to rewrite a lot of code, but ok!

@tg9541 @dougmerritt

Ya know mates, it's rough trying to squeeze \(5\times 1e^{11}\) 64-bit floating-point weights into an MCU or an FPGA.

But using quantised (QNN), binarised (BNN), or logic (LNN) neural networks, we can fit that bloated DNN into the limited confines of these little devices with which we normally work: \(1/64\) reduction is chewable, for us, especially if we focus just on the "recall" phase.πŸ˜€

@AmenZwa at least the illusion of "intelligence" won't be a problem when you "quantise" that much. Folks are simple and illusions matter.

@dougmerritt

@tg9541
Mate, every one of our "colleagues" in IT are already "quantised", when it comes to their "intellect".🀣

@dougmerritt

@[email protected] good point - that must have something to do with PowerPoint and other kinds of non-information.

@dougmerritt