NeonSnake4d ago

Serious ask:

I need a crash-course in AI.

Context: my line manager has been asked to evaluate the use of AI at work. He's come to me to ask if I want to help, as he knows I hate it (and he does too), but I'm...vaguely aware...that not all things that are called "AI" are equal.

(like, the "AI" of NPCs in a game is not the same as the "AI" used to create the type of image we generally call "slop", right?)

We want to make sure we're armed with decent knowledge, because we don't want people to say "Oh, ignore them, they're just haters" if we're talking about something that maybe isn't the "bad" kind of AI (if such a thing exists - I don't know enough to be confident right now)

At the moment, *to the best of my currently limited knowledge*, our AI usage is pretty much limited to people using Gemini to create emails and transcripts of meetings.

(I hope that makes sense)

Show threadCouncilsInExile4d ago

@neonsnake It’s probably worth saying a bit about the history.

AI as a field gets started in the 50s at the same time as control theory and cybernetics with a lot of cold war funding. It has a weird relationship with psychology.

There are two broad approaches ‘expert systems’ and ‘neural networks’ which dominated at different periods.

So the ‘perceptron’ neural net was invented in 1958 and is in direct continuity with the deep learning of the 2010s and LLMs of today.

So you have:
AI: The field as a whole
Neural nets and learning: Broad strategy
Expert systems: Broad strategy, videogame NPCs are and example of this
LLM: One technique in the neural nets approach
Transformers: Implementation details of LLMs but also used elsewhere

Show threadCouncilsInExile4d ago

@neonsnake

In the 2010s we had ‘big data’ and the rise of cloud compute, this made learning techniques competitive in a way they hadn’t been in decades since each layer in the network adds lots more computing cost. Models with many layers became known as ‘deep learning’.

This gives you a lot of useful stuff, image classifiers, anomalies detection, NLP, Robotics, generally anything where you can solve a problem by approximating a function.

A lot of the specific techniques that later go into LLMs are developed in this period. The most important is imo the wordsToVec paper that develops embeddings.

Show threadNeonSnake4d ago
@RevPancakes I'm afraid I don't know what NLP is in this context - I know the acronym as Neuro-Linguistic Programming, which I'm more than passingly familiar with, but doesn't seem to fit?
Show threadCouncilsInExile4d ago
@neonsnake sorry it’s Natural Language Processing
Show threadNeonSnake4d ago

@RevPancakes

When I say "layman", I *do* mean "layman" - i'm not quite at putting "how rotate PDF?" as my Facebook status, but...I'm probably close 😜

(far gone are the days when I was programming the VCR for my mum and dad, lol)

Show threadCouncilsInExile

@neonsnake haha I din’t want to spam you with walls of text *too much*

So in practice NLP would be: Scanning documents and converting handwriting to text, converting speech to text and text to speech, classifying texts based on various criteria such as emotional tone, generating text, extracting features or summarising text, various things from linguistics that I don’t understand

Mar 22 at 11:15amWeb
Show threadNeonSnake4d ago

@RevPancakes That makes sense, and feels like it's done locally.

(FWIW, I'm of an age where I used to be able to dick about with the config.sys and autoexec.bat to get it to run X-Wing, but when people talk about BERT, I'm thinking "is that the Muppet?" 😂 )