Generative AI is the next revolution

After the deep-learning boom, the Artifical Intelligence and Big Data market seemed to be growing at a constant rate. This prediction, however, was disrupted by the recent improvement and popularity of Generative AI models. The release of LLM and Diffusers such as GPT and Dall-E from Open AI demonstrated the potential and functionalities of Generative AI on all industries in the coming years.

We are witnessing a new wave of tools based on generative AI technologies, motivated by the performance achieved by the latest LLM/Diffuser models, such as ChatGPT, Github Copilot or Midjourney.

If these on-the-shelf tools can already deliver a great deal of value, the use of proprietary data and fine-tunned models are the key to create true differentiator.

Whether using off-the-shelf tools or more advanced use cases, companies are faced with three major challenges:

• How to secure a safe adoption: Internal usage of generative AI tools must be supervised with dedicated training and the establishment of best practices
• How to avoid hardware cost explosion: LLM models usage, fine-tunning or training could be expensive and cost must be contained
• How to ensure data security and privacy: a safe company environment hosting all generative AI tools must be set-up to ensure data privacy and security