Assess the Value and Feasibility of LLM Use Cases with a Checklist

Eva is a Data Strategist and Practice Lead Generative AI at Xebia Data. With a focus on the human side of technology, she brings creativity, energy, and a deep understanding of the intersection between data and people. As co-host of ‘De Dataloog’ podcast and an advocate for user-centric design, Eva fosters collaboration and inspire innovative thinking. Her spare time is spend on the pitch as a field hockey player, during which she learned how to collaboratively work towards the same goal!

As a Principal Data Scientist at Xebia Data, Rens Dimmendaal leads teams of Data Scientists and Machine Learning Engineers, focusing on delivering value through AI-powered products and MLOps best practices. Rens shares his knowledge and experience at meetups and conferences, such as PyData, MLOps.Community, and NeurIPS.

Rens is passionate about responsible AI and contributes artwork to the Better Images of AI project, an initiative that aims to enhance communication about AI through meaningful visuals.

I'm a tech entrepreneur and I spent the last decade founding companies that drive societal change.

I am now building Deep Matter, a startup still in stealth mode...

I was most recently building Telepath, the world's most developer-friendly machine learning platform. Throughout my previous projects, I had learned that building machine learning powered applications is hard - especially hard when you don't have a background in data science. I believe that this is choking innovation, especially in industries that can't support large data teams.

For example, I previously co-founded Call Time AI, where we used Artificial Intelligence to assemble and study the largest database of political contributions. The company powered progressive campaigns from school board to the Presidency. As of October, 2020, we helped Democrats raise tens of millions of dollars. In April of 2021, we sold Call Time to Political Data Inc.. Our success, in large part, is due to our ability to productionize machine learning.

I believe that knowledge is unbounded, and that everything that is not forbidden by laws of nature is achievable, given the right knowledge. This holds immense promise for the future of intelligence and therefore for the future of well-being. I believe that the process of mining knowledge should be done honestly and responsibly, and that wielding it should be done with care. I co-founded Telepath to give more tools to more people to access more knowledge.

I'm fascinated by the relationship between technology, science and history. I graduated from UC Berkeley with degrees in Astrophysics and Classics and have published several papers on those topics. I was previously a researcher at the Getty Villa where I wrote about Ancient Greek math and at the Weizmann Institute, where I researched supernovae.

I currently live in New York City. I enjoy advising startups, thinking about how they can make for an excellent vehicle for addressing the Israeli-Palestinian conflict, and hearing from random folks who stumble on my LinkedIn profile. Reach out, friend!