Clemens Mewald

Dec 15, 2023 | databricks.com | Clemens Mewald |Matei Zaharia |Cyrielle Simeone |Import Os

BackgroundIn an era where Retrieval-Augmented Generation (RAG) is revolutionizing the way we interact with AI-driven applications, ensuring the efficiency and effectiveness of these systems has never been more essential. Databricks and MLflow are at the forefront of this innovation, offering streamlined solutions for the critical evaluation of GenAI applications.

Oct 19, 2023 | towardsdatascience.com | Clemens Mewald

And why LLMOps will suffer the same fate as MLOpsI’ve been a vocal skeptic about the viability of ML developer tooling (broadly categorized as MLOps) as standalone businesses and, with very few exceptions, I’ve been proven right. The lack of a dominant design has led to fragmented “micro-markets” with very little value capture, mostly because of open source alternatives and cloud vendors giving their ML tools away for free (to collect revenue on the infrastructure layer).

Oct 19, 2023 | towardsdatascience.com | Clemens Mewald

I've been a vocal skeptic about the viability of ML developer tooling (broadly categorized as MLOps) as standalone businesses and, with very few exceptions, I've been proven right. The lack of a dominant design has led to fragmented "micro-markets" with very little value capture, mostly because of open source alternatives and cloud vendors giving their ML tools away for free (to collect revenue on the infrastructure layer).

Jul 13, 2023 | towardsdatascience.com | Clemens Mewald

How a real-time programmatic data exchange would change everythingThe phrase “data is the new oil” was coined by Clive Humby in 2006 and has been widely parroted since. However, the analogy holds merit in only a few aspects (e.g. the value of both usually increases with refinement) and data’s broader economic impact has been muted outside of a select few tech and finance companies. But the actual differences between oil and data are fundamental. Most notably, oil is a commodity.

Jun 7, 2023 | towardsdatascience.com | Clemens Mewald

At the same time of TensorFlow's rise, foreshadowing what was yet to come in open source AI, enterprise software went through an open source licensing crisis. Mostly thanks to AWS, which had mastered the craft of taking open source infrastructure projects and building commercial services around them, many open source projects exchanged their permissible licenses for "Copyleft" or "ShareAlike" (SA) alternatives. Not all open source is created equal.