AI

Transformers , modern Machine Learning model

Ashkan Kamyab

— 1 min read
Transformers , modern Machine Learning model
This featured image generate by a transformer AI model

AI transformers are a type of machine learning model that are used for a variety of natural language processing tasks, such as language translation, text summarization, and text classification. They are called "transformers" because they transform one representation of input data into another, more useful representation.

Transformers are based on the idea of self-attention, which allows the model to consider the relationships between different words in a sequence of input data. This is in contrast to traditional machine learning models that rely on pre-defined rules or patterns to process the input data.

One of the key advantages of transformers is that they can process input data of arbitrary length, making them well-suited for tasks such as translation and summarization that involve long sequences of text. They are also highly parallelizable, meaning that they can be trained to run on multiple processors or even on specialized hardware such as graphics processing units (GPUs).

Overall, transformers have revolutionized the field of natural language processing and have become a key component of many state-of-the-art models in this domain.

ChatGPT is one of the recent example. I ask Chat GPT whether it uses transformers ?
So following answer is a fully AI generated answer using transformers.

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Yes, I am a large language model trained using transformer architecture, specifically the GPT (Generative Pre-training Transformer) architecture. As a language model, my primary task is to generate human-like text by predicting the next word in a sequence based on the words that came before it. I do this by considering the relationships between the words in the input sequence and using this information to make informed predictions about what word is most likely to come next.

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