Archive - Enterprise Data Science

Responsible AI- why is that term no longer prevalent?

Back in the late 2010s, us data scientists at the enterprise were focused on responsible AI for traditional ML. Neural nets were the bane of our…

Jul 26 •

Carlo Carandang

May 2025

Computer Scientists Playing God with AI

Computer scientists are now playing God with the advent of GenAI and Robotics. They now have the same powers that doctors always had, but doctors have a…

May 22 •

Carlo Carandang

April 2025

Temperature Testing for Translation Applications: A Practical Guide

This article shows how temperature testing improves translation accuracy and fluency in language model applications. It outlines a simple, practical…

Apr 21 •

Carlo Carandang

The Time for Robotic Psychiatry has Arrived

With the global uptake of ChatGPT, we finally have "intelligent" robots interacting with people in new environments. AI robots are now reality, and…

Apr 20 •

Carlo Carandang

March 2025

The Critical Role of Temperature Testing in GenAI Solutions

Temperature testing calibrates GenAI models to balance creativity and accuracy. Without it, outputs can become unpredictable and inconsistent.

Mar 20 •

Carlo Carandang

Developing AI Skills via Data Science

It’s no mystery how one develops AI skills- the answer lies in a field that has been around for years- data science.

Mar 1 •

Carlo Carandang

February 2025

Software Developers for AI Solutions, but only with Data Scientists

Hire Software Developers for AI Solutions, but you still need Data Scientists. I see posts lately of folks not needing data scientists for their AI…

Feb 19 •

Carlo Carandang

January 2025

Starting with the Business Process: A Foundation for Effective AI Solutions

Effective AI solutions start with understanding the business process. By collaborating with SMEs, organizations can ensure AI aligns with workflows and…

Jan 26 •

Carlo Carandang

Knowledge Sausages: Building Analytics Pipelines That Deliver Value

“Knowledge sausages” from analytics pipelines miss the mark without clear business needs. Start with the problem, craft solutions, and build pipelines…

Jan 19 •

Carlo Carandang

December 2024

Hackathons: The Catalyst for Data Science Innovation in AI-Naive Organizations

In organizations where data science is viewed with skepticism, and ML models are absent from business operations, hackathons showcase its value by…

Dec 15, 2024 •

Carlo Carandang

October 2024

Requesting Resources for Building Data Science Capacity

Let's face it- you can't build data science capacity at your AI naive enterprise without data science talent. As an AI champion, you can't build it…

Oct 5, 2024 •

Carlo Carandang

August 2024

The MLOps Way: Utilizing the 3 Pipeline Design and Production REST API

For MLOps, we map the CI pipeline and the CD pipeline to the 3 pipeline design and production REST API.

Aug 26, 2024 •

Carlo Carandang

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