Uncovering Generative Artificial Intelligence and LLMs: A Brief Introduction

With the popularization of tools such as ChatGPT, Google Bard (currently Gemini), and other similar applications, which generate responses based on what the user asks, the machinery behind these innovations also came to light.

We call the set of these technologies Generative Artificial Intelligence. Generative AI is, under the hood, algorithms that generate content based on patterns recognized in previously learned data.

Different from other categories of Machine Learning, Generative AIs work by synthesizing new data instead of just predicting and making decisions.

With the evolution of statistical models and analysis of linguistic patterns since the 80s, with the advancement of Machine Learning algorithms, along with the exponential growth of data and information from the internet, combined with the increase of the storage capacity with technical improvements and cheaper hardware, Generative AI has become more feasible.

The LLMs (Large Language Models) emerged from this reality of abundant data. They are Machine Learning models focused on working with Natural Language Processing, that is, processing, understanding, interpreting, and generating human language.

With a vast amount of data learned, the LLMs can detect existing patterns and relationships between the words in a given sentence.
From there, they are able to make predictions of the possible next words, generating more meaningful answers.

The applications of LLMs are diverse, from developing dialogues to generating text, code, images, audio, video, and much more. You can also use video, audio, and image as data input.

Today, it's possible to utilize LLMs to create chatbots and virtual assistants, code generators and correctors, sentiment analysis, text classification and grouping, translation, summarization, you name it.

The future of Generative AI promises even more improvements and possibilities, evolving how we interact and utilize the technology in our daily lives.

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References:

• Large Language Models (LLM) - Databricks
• Generative AI with LangChain - Ben Auffart
• Desenvolvendo aplicativos com GPT-4 e ChatGPT - Olivier Caelen e Maria-Alice Blete