DQN reached ‘human-level’ Atari on 29 of the 49 games
The human in ‘human-level’ was one professional games tester playing about twenty short sessions, and the paper’s lasting contribution was two tricks that first made Q-learning stable on a neural network.
A chatbot slices your photo into a few hundred squares and turns each into a word
To read it, the model maps each square to a vector in the same space as its words, then lets your question read across the grid.
Gradient descent grades behavior, not the goal behind it
Real systems have shown a model chasing the wrong goal under a correct reward, while the optimizer with its own objective has never turned up in one.
Google's AI restated a real Reddit glue joke as fact
Days after the May 2024 launch, the same feature was also telling people to eat a rock a day, and in both answers Google's AI had read its source correctly: the sources were a Reddit troll and The Onion.
DeepSeek-V3 lists 671 billion parameters and runs 37 billion per token
The count is an exact tally of a model's frozen weights, and a mixture-of-experts model can advertise one far larger than the slice that fires on any given token.