Piero Molino on the Impact of Declarative ML

Welcome back to another episode of Data Driven! In today's episode, we have a special guest joining our hosts Andy Leonard, BAILeY, and Frank La Vigne. We are thrilled to have Piero Molino, an expert in declarative ML, sharing his insights with us.

We'll be diving into the world of generative AI and exploring the two types of companies when it comes to adoption. Piero highlights the advantages and limitations of using APIs for quick solutions, shedding light on why owning the entire stack and platform is the next phase for companies.

Speaker Bio

Piero Molino, a renowned researcher and engineer, has made significant contributions to the field of artificial intelligence. He previously worked at Uber as one of the founding members of the Uber AI organization, where he spent four years conducting research and developing applications. During his time at Uber, Molino created Ludwig, an open source project that has become a foundational technology for many companies, including his own. Ludwig is recognized as one of the first machine learning systems that offer clarity and transparency. Molino's innovation and expertise have positioned him as a leading figure in the advancement of AI technologies.

Show Notes

[00:01:07] Ageing well thanks to healthy lifestyle changes.

[00:05:52] Declarative configuration for creating AI pipelines.

[00:10:14] Built tool to streamline machine learning projects, shortened development time from a year to a week.

[00:13:14] Deploying machine learning models should be easier.

[00:19:42] Declarative ML: Trendy or in need of explanation?

[00:23:40] Shortcut solutions may work, but lack knowledge. Building custom data models can be costly. Differentiation and progress with new product, Bradybase.

[00:27:16] Customizable, automated solution between build and buy.

[00:30:40] Larger organizations have a spectrum of machine learning applications, with some being more impactful than others. Evaluating the feasibility of smaller applications can be costly. Having a tool to test applications quickly would be beneficial. Uber had a similar experience with self-driving cars being the highest priority.

[00:35:08] First-time CEO experiences changing priorities and challenges.

[00:37:47] New breed of generative eye tools; interactive applications; computer graphics and machine learning; improved animation in sports.

[00:41:04] Difficulty connecting transportation dots, still unresolved.

[00:44:12] Audible super premium account for book recommendations. Eye-opening books on goals and time.

[00:47:35] Encourage checking out predibus. Thanks for listening.