This chapter offers a practical, step-by-step guide for businesses interested in implementing generative AI technologies. This covers everything from defining objectives and assessing current infrastructure to selecting the right tools and training your team. It's a comprehensive roadmap for successful AI adoption. To conclude, we discuss what the future may hold for generative AI.

Download the whitepaper here: https://www.raccoons.be/resources/whitepapers/generative-ai-playbook

In this chapter, we discuss the ethical landscape of using generative AI. Issues around privacy, data ownership, and potential biases are highlighted. We also cover existing guidelines like the EU's AI Act and ACM's Statement of Principles, helping businesses and individuals navigate the ethical complexities of this technology.

Download the whitepaper here: https://www.raccoons.be/resources/whitepapers/generative-ai-playbook

In the first chapter, we discussed the evolution of generative AI as a whole. In this chapter, we will dive into the field that (according to us) has the most notable advancements for business applications: text generation, and more specifically GTP. We will discuss three technical advancements that have had an enormous influence on how we can implement the technology to efficiently solve our clients’ challenges: function calling, knowledge mining, and fine-tuning.

Download the whitepaper for more information: https://www.raccoons.be/resources/whitepapers/generative-ai-playbook 

In this chapter, we introduce the topic of generative AI, a subset of artificial intelligence that's capable of generating new content such as text, images, or audio. We set the stage for understanding its significance and how it has changed in the last year.

Download our whitepaper here for more information: https://www.raccoons.be/resources/whitepapers/generative-ai-playbook