Transcript
Title text: This is how you all fucking sound
[A smug tech bro wearing a sideways cap, watch, chain around his neck stands in front of a data center by a lake with dead fish. A smoke stack blows pollution into the air]
Tech bro: AI is already here, there’s no going back.
[A smug man in a suit with cigarette in hand stands in a restaurant while two disgruntled diners cough from the smoke]
Suit: Smoking indoors is already here, there’s no going back.
[A smug man in a top hat and suit stands in a factory with two sad and dirty children]
Hat: Child labor is already here, there’s no going back.
[A smug plantation owner stands in front of a field with with two angry slaves]
Plantation owner: The Atlantic Slave trade is already here, there’s no going back.


Transformer is useful for damn near anything. At the end of the day, what we consider intelligence is the ability to predict what comes next, whether that is what our senses will tell us next or what the next hypothesis to test should be based on the data we have seen so far.
It’s not damn near anything. There’s loads of stuff that computers can do much more quickly and more accurately without it just by virtue of computers already being fast and effective at maths and obeying logic. With or without the transformer architecture, a neural network is never going to be as fast or reliable at, for example, summing a collection of numbers as just adding them would be, and loads of real-world tasks are like this, hence why we’ve built billions of computers even before the transformer architecture was invented.
Also, in particular, I didn’t say that the transformer architecture wasn’t useful for things that aren’t LLMs, I said that most of the work done specifically to improve LLMs has no applications outside LLMs, so the next big leap towards making computers intelligent isn’t helped more by working on LLMs than it would be by working on any other kind of AI.