What are transformer models in AI?

Transformers are machine learning models that the Google Brain team introduced in 2017 in an article titled Attention Is All You Need, and that paved the way for many of the amazing advances we’re seeing in AI today.

Google itself is using transformers to improve their search results, and OpenAI uses transformers to create the GPT-3 model, which is amazingly good at creating written text. (I’m already curious about what GPT-4 will be like, but I expect nothing but amazingness.)

A transformer model is a type of artificial intelligence model that is used to process and interpret natural language data. Transformer models are designed to handle long-term dependencies in data, and can be used for tasks such as machine translation and text summarization.

Transformer models are based on a self-attention mechanism, which allows the model to attend to different parts of the input data simultaneously. The self-attention mechanism is inspired by the human brain, which is able to focus on multiple tasks at the same time. Transformer models have been shown to outperform other types of artificial intelligence models on a number of natural language processing tasks.

Lex Fridman and Andrej Karpathy (former director of AI at Tesla and founding member of OpenAI) talked about this:






Leave a Reply

Your email address will not be published. Required fields are marked *