Declarative ML with Ludwig Creator & Predibase CEO & Co-Founder Piero Molino

Low-code platforms provide a powerful and efficient way to develop applications and drive digital transformation and are becoming popular tools for organizations. In today’s episode, we are joined by Piero Molino, the CEO, and Co-Founder at Predibase, a company revolutionizing the field of machine learning by pioneering a low-code declarative approach. Predibase empowers engineers and data scientists to effortlessly construct, enhance, and implement cutting-edge models, ranging from linear regressions to expansive language models, using a mere handful of code lines. Piero is intrigued by the convergence of diverse cultural interests and finds great fascination in exploring the intricate ties between knowledge, language, and learning. His approach involves seeking unconventional solutions to problems and embracing a multidisciplinary approach that allows him to acquire novel and varied knowledge while gaining fresh experiences. In our conversation, we talk about his professional career journey, developing Ludwig, and how this eventually developed into Predibase. Key Points From This Episode:Background about Piero’s professional experience and skill sets.What his responsibilities were in his previous role at Uber.Hear about his research at Stanford University.Details about the motivation for Predibase: Ludwig AI. Examples of the different Ludwig models and applications.Challenges of software development.How the community further developed his Ludwig machine learning tool.The benefits of community involvement for developers.Hear how his Ludwig project developed into Predibase.He shares the inspiration behind the name Ludwig.Why Predibase can be considered a low-code platform.What the Predibase platform offers users and organizations.Ethical considerations of democratizing data science tools.The importance of a multidisciplinary approach to developing AI tools.Advice for upcoming developers.Tweetables:“One thing that I am proud of is the fact that the architecture is very extensible and really easy to plug and play new data types or new models.” — @w4nderlus7 [0:14:02]“We are doing a bunch of things at Predibase that build on top of Ludwig and make it available and easy to use for organizations in the cloud.” — @w4nderlus7 [0:19:23]“I believe that in the teams that actually put machine learning into production, there should be a combination of different skill sets.” — @w4nderlus7 [0:23:04]“What made it possible for me to do the things that I have done is constant curiosity.” — @w4nderlus7 [0:26:06]Links Mentioned in Today’s Episode:Piero Molino on LinkedInPiero Molino on TwitterPredibaseLudwigMax-Planck-InstituteLoopr AIWittgenstein's MistressHow AI HappensSama