If you are told IT, automation, increased productivity or optimization of resources, you are probably thinking of DevOps.
Combining the previously separate skills of development teams with those of operational teams, DevOps aims to improve collaboration between these two departments by automating the most time-consuming tasks in the integration, development, testing, deployment or monitoring.
For nearly 10 years, the AI counterpart of DevOps - MLOps - has developed, bringing the same philosophy: automating Machine Learning workflows and applications, and enabling teams to gain in productivity and speed of execution. How does this translate concretely into an AI business? What impact does this have on a daily basis?
For the twentieth edition of our newsletter, we offer you an immersion in MLOps, thanks in particular to our interview with Florent Piétot, co-founder of Nibble.ai, accompanied by an article illustrating how this practice helps data scientists from Preligens to create and deploy a first operational version of a new detector in just 6 weeks.
And to conclude this newsletter, a look back at our two presentations at exciting conferences at Vivatech 2023 and two new use cases for the operational application of AI: a situation update in Sudan and Ukraine.
Enjoy your read!
Arnaud Guérin & Renaud Allioux, co-founders of Preligens