The Rise of Open Source Generative AI

Let’s delve into the cutting-edge technologies of open source generative Al, exploring their emergence, real-world applications, and how they are transforming industries.

- S. K. Agrawal

The generative AI revolution has accelerated over the last few years, with advancements reshaping multiple industries by automating complex tasks and enhancing human capabilities. While proprietary AI models have long been the staple of tech giants, the rise of open source solutions has democratised the AI space, making powerful models like language models (LLMs), vision language models (VLMs), language action models (LAMs), speech-driven models (SLMs), and retrieval-augmented generation (RAG) agents accessible to all. Open source generative AI is breaking down barriers, offering unprecedented levels of transparency, customisation, and collaboration.

Understanding the key open source models in generative AI

Large language models (LLMs)

At the heart of generative AI lies the power of large language models (LLMs). These models, such as GPT (Generative Pretrained Transformer), are designed to understand and generate human language. LLMs are trained on a large corpora of text data, enabling them to answer questions, write essays, summarise documents, and even engage in sophisticated conversations. The open source movement has led to a proliferation of LLMs, enabling businesses, researchers, and developers to use, fine-tune, and scale these models to meet specific needs.

The key benefits of open source LLMs include:

Cost-effectiveness: Open source models like GPT-2, GPT-Neo, and GPT-J allow businesses to leverage advanced NLP capabilities without incurring hefty licensing fees.

Customisation: Open source models can be adapted and fine-tuned to specific domains, making them suitable for specialised use cases such as legal document generation, medical research, and customer service.

Visual language models (VLMs)