Letters
Solving AI Problems With Civility
I’m grateful to the AI community for the friendships it has brought me and the benefits it has brought to billions of people. But members of the AI community don’t always honor one another.
Letters
Letters
Making Software For a Heterogeneous World
The physical world is full of unique details that differ from place to place, person to person, and item to item. In contrast, the world of software is built on abstractions that make for relatively uniform coding environments and user...
Letters
How To Unlock AI Value
On Monday, Landing AI (where I’m CEO) announced the close of a $57 million Series A funding round. The investment enables the company to continue building its data-centric MLOps platform for computer vision, with a focus on manufacturing visual inspection.
Letters
Background Music: Pleasure or Pitfall?
Years ago, whenever I had to do something boring or unpleasant — such as drive to work or go for a run — I used to listen to music to provide a distraction. Although I still appreciate music, as I got older I decided to cut out distractions.
Letters
When the AI and Spirit Worlds Collide
On Halloween, the veil lifts between the spirit and AI worlds, allowing the two to pass through one another. The resulting paranormal — or, as AI practitioners call it, paragaussian — phenomena raise questions like these...
Letters
Congrats to the Data-Centric Competition Winners!
In June, I announced the first Data-centric AI Competition. The deadline for submissions was in early September, and today I’m thrilled to announce the winners!A total of 489 individuals and teams submitted 2,458 unique datasets.
Letters
Imaging Systems for Data-Centric AI Development
The image below shows two photos of the same gear taken under different conditions. From the point of view of a computer-vision algorithm — as well as the human eye — the imaging setup that produced the picture on the right makes...
Letters
How to Build AI Products and Businesses: Two Strategies
Building AI products and businesses requires making tough choices about what to build and how to go about it. I’ve heard of two styles: Ready, Aim, Fire and Ready, Fire, Aim
Letters
How to Learn Math for Machine Learning
How much math do you need to know to be a machine learning engineer? It’s always nice to know more math! But there’s so much to learn that, realistically, it’s necessary to prioritize.
Letters
Are You OK? Taking Care of Emotional and Mental Health
Since the pandemic started, several friends and teammates have shared with me privately that they were not doing well emotionally. I’m grateful to each person who trusted me enough to tell me this. How about you — are you doing okay?
Letters
Developing AI Products Part 5: Data Drift, Concept Drift, and Other Maintenance Issues
In earlier letters, I discussed some differences between developing traditional software and AI products, including the challenges of unclear technical feasibility, complex product specification, and need for data to start development.
Letters
Developing AI Products Part 4: Getting Data To Start Development
In a recent letter, I mentioned some challenges to building AI products. These problems are distinct from the issues that arise in building traditional software. They include unclear technical feasibility and complex product specification.