get_flat_ccs_offset() reads the base of the flat CCS storage from the
hardware, scales it by the number of enabled L3 nodes, and rounds the
result up to 128K. Everything below that offset is then ...
You’re lumping all of machine learning into the bucket of tech bros, ChatGPT, Facebook and such.
There was a thriving, small scale world of machine learning stuff that existed before they hijacked the public’s attention, and it never went away. It still exists. It will continue to exist when this bubble at least deflates some.
That’s not my intent. Machine learning as a method of computation isn’t the problem.
Among other things, the problem is how the business of AI is sourcing their input training data, how these outputs are being used to manipulate people and markets, etc.
ML is sometimes the best tool for certain computing tasks and succeeds where algorithmic programming fails. Sometimes traditional logic and algorithms is preferable for it’s determinism and easily understandable behavior.
The AI industry however is built on exploitation of human and natural resources, and it also built on top of a massive economic bubble and is hurting the market for jobs and human made things.
Comparing AI to human learning is neglecting to acknowledge the problems that we currently face with how AI is currently being trained and deployed by the biggest players in the industry.
Okay, well, what about Nvidia Nemotron’s series as a counter example?
It’s built on an open dataset; its training regime isn’t secret, it’s reproducible. It’s Apache licensed. It’s not published to manipulate anyone; it’s mostly presented as a research tool, or a starting point for users to customize for mundane text processing tasks. It runs reasonably efficiently on a large variety of software and hardware, with a standardized architecture.
Of course AI, as it is mostly presented to the public, is an existential problem.
But you’re trying to fundamentally tie text-based machine learning to the tech bros as a root for its ethical issues. It’s not that simple. Even if Sam Altman and all his kind keel over tomorrow, the complications the existence of LLMs and other generative models present is not going away, and we will have to deal with models that can do unethical things without anything unethical in their training regime.
You’re lumping all of machine learning into the bucket of tech bros, ChatGPT, Facebook and such.
There was a thriving, small scale world of machine learning stuff that existed before they hijacked the public’s attention, and it never went away. It still exists. It will continue to exist when this bubble at least deflates some.
That’s not my intent. Machine learning as a method of computation isn’t the problem.
Among other things, the problem is how the business of AI is sourcing their input training data, how these outputs are being used to manipulate people and markets, etc.
ML is sometimes the best tool for certain computing tasks and succeeds where algorithmic programming fails. Sometimes traditional logic and algorithms is preferable for it’s determinism and easily understandable behavior.
The AI industry however is built on exploitation of human and natural resources, and it also built on top of a massive economic bubble and is hurting the market for jobs and human made things.
Comparing AI to human learning is neglecting to acknowledge the problems that we currently face with how AI is currently being trained and deployed by the biggest players in the industry.
Okay, well, what about Nvidia Nemotron’s series as a counter example?
It’s built on an open dataset; its training regime isn’t secret, it’s reproducible. It’s Apache licensed. It’s not published to manipulate anyone; it’s mostly presented as a research tool, or a starting point for users to customize for mundane text processing tasks. It runs reasonably efficiently on a large variety of software and hardware, with a standardized architecture.
Of course AI, as it is mostly presented to the public, is an existential problem.
But you’re trying to fundamentally tie text-based machine learning to the tech bros as a root for its ethical issues. It’s not that simple. Even if Sam Altman and all his kind keel over tomorrow, the complications the existence of LLMs and other generative models present is not going away, and we will have to deal with models that can do unethical things without anything unethical in their training regime.