Generative Edge Intelligence: The Future of Generative AI Systems

In the 40th edition of this newsletter, entitled “Open Source Generative AI Foundation Models: The Toolbox for Innovation,” it was concluded that the?“Customized Generative AI”?strategies can carefully select the?“Best-Fit Foundation Models”?that can turn the?“Enterprise Data Assets”?into?“Actionable Knowledge.”?More importantly, the focus nowadays is on selecting the most suitable foundation model from the available open-source?“Small and Specialized Foundation Models”?that are available as a toolbox for innovation and, at the same time, provide better total cost of ownership and less harm to the environment. What wasn’t covered in that previous edition is how to reduce the?“Total Cost of Ownership”?and minimize the?“Negative Effect on the Environment.”

Before discussing how to achieve these goals, it is worth mentioning that the reason behind the high total cost of ownership and the harm to the environment came from the massive size of the typical?“Large Foundation Models,”?which requires?“Massive Computing Power”?in terms of so many GPUs for operating them on the cloud, and their?“Significant Carbon Footprint”?generated for these cloud operating centers.?

Hence, it seems logical to assume that if enterprises were able to change this working environment of their generative AI systems, these problems would be solved. Here comes the promise of the?“Generative Edge Intelligence”?systems, which represent the future of generative AI systems.

The core element of the generative edge intelligence systems is the currently available open-source?“Small, and Even Tiny, Specialized Foundation Models,”?which are available as a toolbox for innovation and can be deployed on many computing terminals away from the cloud. These computing terminals range from personal laptops that don’t even have any GPUs to tablets, mobile phones, and even wearables. Being able to design and operate?“GPUs-Free Generative AI Systems”?that run on mobile processors will be a breakthrough and will transform the future of generative AI systems in the near future.

Hence, and to conclude, to reduce the?“Total Cost of Ownership”?and minimize the?“Negative Effect on the Environment,”?enterprises need to avoid massive sizes of typical?“Large Foundation Models,”?which require?“Massive Computing Power”?in terms of so many GPUs for operating them, and generate?“Significant Carbon Footprint”?form the cloud operating centers. This can be achieved through using the currently available open-source?“Small, and Even Tiny, Specialized Foundation Models,”?which are available as a toolbox for innovation and can be deployed on many computing terminals away from the cloud, such as laptops that don’t even have any GPUs to tablets, mobile phones, and even wearables. Shortly, these are the?“Generative Edge Intelligence”?systems, which can be considered as?“GPUs-Free Generative AI Systems”?and will represent the future of generative AI systems soon.