Mixture of Experts – How Modern LLMs Scale Without Proportional Cost
A useful mental model for thinking about large language models is that they are very large lookup tables. During training, they compress an enormous amount of information about…
Topic: Deep Learning
The Vanishing Gradient Problem – Why Deep Networks Forget Where They Came From
There is a paradox buried in the design of deep neural networks. The deeper you make a network, the more expressive it should become – more layers means…
Attention Is All You Need – But Do We Understand Why?
In 2017, a Google Brain paper with a quietly confident title rewired how the world thinks about sequence modeling. Attention Is All You Need didn’t just introduce a…