This is the best summary I could come up with:

From the breakthrough of besting a legendary player at the complex game Go in 2016, AI is now able to recognize images and speech better than humans, and pass tests including business school exams and Amazon coding interview questions.

More computation also allows the system to model the relationship between the variables in the data in greater detail, meaning it can draw more accurate and nuanced conclusions from the examples it is shown.

By comparison, LlaMa, a large language model developed by researchers at Meta and released in 2023, was trained on around one billion data points—a more than 160-million fold increase from Perceptron Mark 1.

Algorithms—sets of rules or instructions that define a sequence of operations to be carried out— determine how exactly AI systems use computational horsepower to model the relationships between variables in the data they are given.

There’s still lots to go.” Appearing on the Hard Fork podcast in July, Dario Amodei estimated that “there’s maybe a 10% chance that this scaling gets interrupted by inability to gather enough data.”

Speaking at the Senate Committee hearing, Amodei said that, if progress continues at the same rate, a wide range of people could be able to access scientific know-how that even experts today do not have within the next two to three years by using AI systems.

I’m a bot and I’m open source!

So, chart 1. Apparent image recognition is above human capabilities. If so, why am I still being asked to classify images on captchas? I call shenanigans!

Reading comprehension is the same apparently. A machine does not comprehend. Shenanigans I say.