[FRIAM] Magic Harry Potter mirrors or more?

[Jochen Fromm]

The "Transformer" movies are like the "Resident evil" movies based on a similar idea: we take a simple, almost primitive story such as "cars that can transform into alien robots" or "a bloody fight against a zombie apocalypse" and throw lots of money at it.But maybe deep learning and large language models are the same: we take a simple idea (gradient descent learning for deep neural networks) and throw lots of money (and data) at it. In this sense transformer is a perfect name of the architecture, isn't it?-J.
-------- Original message --------From: Gillian Densmore <gil.densmore at gmail.com> Date: 2/28/23  1:47 AM  (GMT+01:00) To: The Friday Morning Applied Complexity Coffee Group <friam at redfish.com> Subject: Re: [FRIAM] Magic Harry Potter mirrors or more? Transformer architecture works because it's cybertronian technology. And is so advanced as to be almost magic.On Mon, Feb 27, 2023 at 3:51 PM Jochen Fromm <jofr at cas-group.net> wrote:Terrence Sejnowski argues that the new AI super chatbots are like a magic Harry Potter mirror that tells the user what he wants to hear: "When people discover the mirror, it seems to provide truth and understanding. But it does not. It shows the deep-seated desires of anyone who stares into it". ChatGPT, LaMDA, LLaMA and other large language models would "take in our words and reflect them back to us".https://www.nytimes.com/2023/02/26/technology/ai-chatbot-information-truth.htmlIt is true that large language models have absorbed unimaginably huge amount of texts, but what if our prefrontal cortex in the brain works in the same way? https://direct.mit.edu/neco/article/35/3/309/114731/Large-Language-Models-and-the-Reverse-Turing-TestI think it is possible that the "transformer" architecture is so successful because it is - like the cortical columns in the neocortex - a modular solution for the problem what comes next in an unpredictable worldhttps://en.wikipedia.org/wiki/Cortical_column-J.-. --- - / ...- .- .-.. .. -.. / -- --- .-. ... . / -.-. --- -.. .
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