In the last weeks, I have seen some posts against kinds of AI, we are using as a society since decades (yes, decades) just because the Term AI is used.
When we are talking about society and planet destroying AI, we are talking generative AI. That is that shit we know als Claude and ChatGPT.
But media (and we) are starting to mix this up with "classical Machine Learning"
Some stuff that is AI, and I am pretty sure we are not fighting against:
- hand written numbers recognition (developed around 30 years ago)
- lane hold assist systems
- voice recognition
- image classification (computer aided diagnostics in radiology is around since 2010).
Those tasks do not need GPUs, huge amount of RAM or electricity.
We should differentiate between Generative AI (LLM, Video and image Generation) and those old school, valid and useful "AI" systems.
Not seeing a difference between those things is a AI Bro behavior, and should be beneath us.
Just being against everything because somebody wrote "AI" besides it only offers AI Bros an attack surface on every other argument we bring forward.
Everything that makes GenAI bad (hallucinations, AI psychosis, energy consumption, RAM usage,....) is a result of the generative part.
An AI model that recognizes YOUR (yes, your!) handwriting on a envelope and routes your letter correctly, and does that since decades, is also AI. I hope nobody here expects us to go back to sorting boxes and hand sorting of letters and packages.
EDIT: for more detail on AGI vs. GenAI look at this great comment.
One thing to note is every useful ML application models when scaled will require huge amount of RAM. I remember around 5 years ago, I ran a simple STT model, and my 8GB computer was barely keeping up.
Yes, but the scale is different. For reference. A conversation with an LLM with around 500kb of raw text requires 20gb and more VRAM just to iterate over this conversation. For each new generated word, the whole input must be reprocessed.