Technical Insights
Why AI Projects Fail, Part 5: Change Management
My last two letters explored robustness and small data as common reasons why AI projects fail. In the final letter of this three-part series, I’d like to discuss change management.
Technical Insights
Why AI Projects Fail, Part 4: Small Data
In this series exploring why machine learning projects fail, let’s examine the challenge of “small data.” Given 1 million labeled images, many teams can build a good classifier using open source.
Technical Insights
Why AI Projects Fail, Part 4: Small Data
In this series exploring why machine learning projects fail, let’s examine the challenge of “small data.” Given 1 million labeled images, many teams can build a good classifier using open source.
Technical Insights
Why AI Projects Fail, Part 3: Robustness
Building AI systems is hard. Despite all the hype, AI engineers struggle with difficult problems every day. For the next few weeks, I’ll explore some of the major challenges. Today’s topic: The challenge of building AI systems that are robust to real-world conditions.
Technical Insights
Why AI Projects Fail, Part 3: Robustness
Building AI systems is hard. Despite all the hype, AI engineers struggle with difficult problems every day. For the next few weeks, I’ll explore some of the major challenges. Today’s topic: The challenge of building AI systems that are robust to real-world conditions.
Technical Insights
Why AI Projects Fail, Part 2: Uncommon Pitfalls
Welcome to the Halloween edition of The Batch! I promised last week to share some common reasons for AI project failures. But first, let’s start with some of the least common reasons.
Technical Insights
Why AI Projects Fail, Part 2: Uncommon Pitfalls
Welcome to the Halloween edition of The Batch! I promised last week to share some common reasons for AI project failures. But first, let’s start with some of the least common reasons.
Technical Insights
Why AI Projects Fail
I’ve heard this conversation in multiple companies: Machine learning engineer: Look how well I did on the test set! Business owner: But your ML system doesn’t work. This sucks! Machine learning engineer: But look how well I did on the test set!
Technical Insights
Why AI Projects Fail
I’ve heard this conversation in multiple companies: Machine learning engineer: Look how well I did on the test set! Business owner: But your ML system doesn’t work. This sucks! Machine learning engineer: But look how well I did on the test set!
Technical Insights
Reducing Essential Complexity
Thinking about the future of machine learning programming frameworks, I recently reread computer scientist Fred Brooks’ classic essay, “No Silver Bullet: Essence and Accidents of Software Engineering.” Three decades after its initial...
Technical Insights
Reducing Essential Complexity
Thinking about the future of machine learning programming frameworks, I recently reread computer scientist Fred Brooks’ classic essay, “No Silver Bullet: Essence and Accidents of Software Engineering.” Three decades after its initial...
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