Leading AI Transformation

I spent three days at the Databricks summit watching one company make a mistake and its cure at the same time, and the cure is the bigger story. A while back I wrote that big companies don't die from doing too many things. They die from doing the same thing… read more

Microsoft can't keep its AI products straight. AWS runs more than two hundred services and stays usable. The difference isn't focus — it's overlap. And the AI assistants buyers now ask for advice are about to make the bill come due. Try this experiment with a friend who works at… read more

Note: written in May 2023. The model names have changed since, but the approach to sentiment analysis holds. Social media is where customers say what they really think, on Twitter/X, Facebook, Instagram, and LinkedIn, in volumes no team can read manually. Large language models like ChatGPT made it practical to… read more

1. Introduction The field of image segmentation has made significant advancements in recent years, with the rise of deep learning techniques and the availability of large-scale annotated datasets. The Segment Anything (SAM) project aims to leverage these advancements to create a foundation model for promptable image segmentation. By introducing a… read more

Snap judgment is the ability of our unconscious to find patterns in a situation instantly and decoding the “truth” about the situation. Finding minimalist patterns of information and filtering out noise at fraction of a second is called thin-slicing. Thin-slicing disqualifies irrelevant information, which often adds to uncertainty in decision-making.… read more

"SEE IT BIG, AND KEEP IT SIMPLE" - Wilferd Peterson There are many quotes about the importance of simplicity. Recently, I came across the one above by Wilferd Peterson. Probably Wilferd had said this for the profession of data science, as it applies so strongly to almost every step and… read more

Note: I wrote this in May 2021, in the middle of the pandemic chip shortage. I have added an update at the end on how it actually played out. As economies started to reopen after COVID vaccinations, the technology world hit a serious shortage of computer chips, driven mainly by… read more

Communicating is an integral part of data science. No matter how valuable the insights are, they are of no value if the business does not understand them or you have to work really hard to explain them. Data professionals are often tempted to use complex and advanced data visualization in… read more

Digital Transformation Is Almost Over Python has recently become the second most used programming language in the world. Globally, programmers are in very high demand, and it would be more so in the future due to the increasing digitization of the global economy. Computing technologies and data are the backbones… read more

Navigating AI Transformation Challenges: Building a Lasting Data Science Team Many large organizations face challenges in their AI transformation journey. Data science projects often take too long to complete or never make it to production. A major reason for this is the lack of a stable data science team, as… read more

Being an AI professional, you often have to advise your client in situations such as defining scope of a problem, design of a data science or machine learning solution, deployment of machine learning model, AI strategy for a business unit selecting vendor solution etc. As an AI advisor, you would… read more

AI Organization AI organization is an organization that intends to employ machine learning and data science to automate and enhance its manual or rule-based business processes. AI helps organizations to improve efficiency, reduce cost, and scale the business. These days most organizations are working to transform themselves into AI organizations,… read more