Dr. Mindle's Musings

This is the first piece I know I should not say but still say it anyway here. Hey, I’m anonymous[1] : ) The problem When I was a frontline engineering manager, I lost two bright, hardworking junior AI/ML engineers within

With two kids in high school, I got my share of the uncomfortable talks about sex and alcohol. So I did my research, consulted experienced parents, watched YouTube videos and mock talked with my wife, before anxiously knocked on the

(First created: 07/31/2024 |Personal Opinion) In earlier posts, I have pondered over analytic experiences (AX) and what an ideal analytic platform entails to deliver great AX. Recently my mind has been on machine learning experiences. Impossible to reduce to two-letter

Humans are. Villains in the veil Villains in the veil Feeding on mass ignorance and greed bend the world to their wills Villain with dollar bills Zero to One the unproud mistaken the capitalistically lucky with the intellectual the green

(First created: 05/25/2024 |Personal Opinion) I hate to make predictions but when a sharp guy ask you a question on the spot you have to make up something right? The question of “What’s your take on the scientific side of

(First created: 05/10/2024 |Personal Opinion) I’m always fascinated by how words come into being and amazed by how they convey the “divine reason implicit in the cosmos, order it and give it form and meaning”. Case in point, as I

As the product owner and the proud brain-father of the internally built Generative AI (GenAI) Gateway, I am inundated with undue enthusiasms and unrealistic expectations for large language models(LLM) from all directions at the same and all times. I found

In business intelligence (BI) and data analytics, the semantic layer has been a game changer in driving BI and data analytics with intuitive and commonly defined metrics.  The same opportunity exists for a semantic layer in the parallel universe of AI/ML.

(Last updated: 09/27/2022 | PERSONAL OPINION) When I worked as an intern in GE R&D center more than two decades ago, my boss was a Paris 6 (Pierre and Marie Curie University) trained mathematician specialized in infinite-dimensional partial differential equations.

I hereby solemnly declare the field of Machine Decisioning (MD) to counter our industry’s single-minded fixation on Machine “Learning” (ML). We have been exploiting one trick (neural net) for long, time to explore: the new, the old, the unhyped… To