Day 21

Today, I wanted to understand a question I’ve had for a while.

What exactly is a Transformer model, and why is it behind many modern AI systems?

While searching for the answer, I came across one of the most important AI papers.

📄 Attention Is All You Need (2017)
https://lnkd.in/gXCnPVSh

Here's what I've understood so far:

- Before Transformers, many AI models processed text sequentially, one token at a time. This made it harder to capture long-range context and slowed down training.

- Transformers introduced self-attention. Instead of only reading text in order, the model can look at the whole sequence and learn which tokens matter most to each other.

- Transformers became the backbone of many modern AI systems.
A lot of today’s large language models and generative AI tools are built on Transformer-based architectures or variations of them.

Day 21 of 1% Better.