Currently famous LLM chats (ChatGPT, Copilot, Gemini) execute given tasks on the provider’s server over the internet. Gemini has a version where the task is executed locally on Android, and data isn’t sent to the cloud. However, if there is a need to have full control over one’s data or the business case is special, private AI is the option.
Private AI runs on hardware that is controlled by the organization owning the data. The knowledge for private AI is created either by using a pre-trained model, which is then trained with task-specific data, or by training it entirely with task-specific data. The business case at hand determines which approach is used.
Full control of data is one advantage of private AI; other notable advantages include speed and special capabilities. Speed is achieved because tasks are performed locally, and the AI solution is specialized to perform the given task, which enhances efficiency. An example of this kind of solution is automated quality control on an assembly line using machine vision. Special capabilities are necessary, for example, in cases where information from multiple sources is needed while performing a given task.
The decision on whether private AI is needed depends on the business case.
Neptunux 29.2.2024
