Generative AI Systems Aren't Just Open or Closed Source

Introduction

It was a typical Saturday afternoon. I was sitting in front of my computer, trying to brainstorm ideas for my next article. Suddenly, an email notification popped up on my screen. It was from my friend, who recently landed a job in an AI startup. She told me about the advancements of Generative AI systems and how they are changing the future of technology.

I was intrigued. As a tech writer, I have always been fascinated by the latest innovations in the industry. But what exactly are Generative AI Systems? And how are they different from open and closed-source systems? I began to research and came across some interesting facts.

Generative AI Systems use artificial intelligence algorithms to create new and unique data based on learning from existing data. Unlike open-source systems, which allow anyone to access and modify the code, and closed-source systems, which keep the code proprietary, Generative AI Systems have the potential to be both.

Take, for example, OpenAI's GPT-3 (Generative Pre-trained Transformer 3) model, which has 175 billion parameters. The sheer amount of data GPT-3 has access to enables it to complete complex tasks like writing articles, coding software, and even generating responses to support tickets. This model has been made available to some developers through an API. This means developers across the globe can use the model's capabilities to create new products and services.

On the other hand, some Generative AI systems are proprietary. Disney, for example, has developed a Generative AI system that can create new 3D models of its characters. This technology is not available to the public, and Disney has a tight grip on the code. This approach ensures that Disney maintains control over its intellectual property.

Generative AI Systems are also changing how we approach traditional areas like fashion design and music composition. H&M has been using AI to create new fashion collections by feeding their Generative AI System images of different fashion styles, which the system then uses to design new pieces. Similarly, Amper is a Generative AI System that creates unique music compositions based on the user's specifications.

Conclusion

What does this mean for the future of technology? Generative AI Systems have the potential to transform the way we work and interact with technology. Here are three main points to take away:

1. Collaboration: Generative AI systems can foster collaboration among developers and different industries in ways that weren't possible before. OpenAI's GPT-3 model is a good example of how developers across the globe can collaborate, and everyone can benefit from the system's capabilities.
2. Protection: Proprietary Generative AI systems have the potential to protect intellectual property and maintain control over the technology. This is helpful in industries like the film industry, where protecting copyright is essential.
3. Innovation: Generative AI systems offer endless possibilities for innovation. They can take mundane tasks and automate them, freeing up time for more creative work. H&M's fashion collection, for example, is a new and exciting way of designing clothes that could revolutionize the industry.