Machine Learning Frameworks Packages are a functional step to close the gap from our competitors. We have to provide them in order to allow our customers to run their AI projects. The MLFP need to be: multi-platform, multi-architecture and updated frequently.

Machine Learning Frameworks are probably one of the areas where the AI market is growing faster than anything else. Thinking to cope with the pace of ML Frameworks growing rate is impossible and the effort to produce and maintain packages for all of them is unrealistic. We have to consider also that frameworks change rapidly so their lifecycle cannot be supported for a long time. We have to come up with a logic that allows us to stay relevant to the market and, at the same time, be able to move fast from one version to another of the same framework.

If we look at the usage of the ML frameworks we will see that already some of them outstanding compared to the majority making our selection easier.