Data-Centric AI Development Iterative Workflow
The Batch Newsletter

The Batch: Apple Weakens Privacy, AI's Invention Wins A Patent, Deere All-In For Robot Tractors, Atari-Playing Algo Learns New Trick

Say you’ve trained a learning algorithm and found that it works well on many examples but performs poorly on a particular subset, or slice, of the data. What can you do?...
Math equations
The Batch Newsletter

The Batch: AI Recognizes Race in X-Rays, Robots Do Bees' Work, Transformers Pay Closer Attention, New Research Centers

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.
Hand-drawn letter with a heart and signed by Andrew
The Batch Newsletter

The Batch: Gunshot Detection Under Fire, AI At The Olympics, AlphaFold Goes Open-Source, Revenge Of The Perceptrons

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?
Cartoon about data
The Batch Newsletter

The Batch: Face Recognition Audit, Gamers Cheat with AI, Who Rules the Smart City?, Language Learning Generalizes to Other Domains

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.
Series of spreadsheets with different data
The Batch Newsletter

The Batch: Amazon's Algorithmic Mismanagement, Brainwaves to Text, OpenAI Drops Robotics, Multi-Scene Synthesis

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.
Andrew Ng sitting in the Blue Origin passenger capsule
The Batch Newsletter

The Batch: Walking the Robot Dog, Mistaking German for English, Making Art With an Image Classifier, Zero-Shot Object Detection

I’ve been following with excitement the recent progress in space launches. Earlier this week, Richard Branson and his Virgin Galactic team flew a rocket plane 53 miles up, earning him astronaut wings.
Cartoon about traditional software and AI
The Batch Newsletter

The Batch: Zillow's New Neural Net, Optimizing Traffic City-Wide, Classifying Creepy Crawlies, Behavioral Cloning

In a recent letter, I noted that one difference between building traditional software and AI products is the problem of complex product specification. With traditional software, product managers can specify a product in ways...
Magnifying glass over the words Unclear, Technical and Feasibility
The Batch Newsletter

The Batch: Amazon's Grab-And-Go Grocery, The Trouble With Ethical AI, Airlines Optimized, Few-Shot Learning

Last week, I mentioned that one difference between traditional software and AI products is the problem of unclear technical feasibility. In short, it can be hard to tell whether it’s practical to build a particular AI system.
Slide with information about challenges to building AI products and businesses
The Batch Newsletter

The Batch: Wildfire Alert Network, AI Invades Campuses, Synthetic Videos, Reviving Lost Traditions

With the rise of software engineering over several decades, many principles of how to build traditional software products and businesses are clear. But the principles of how to build AI products and businesses are still developing.
Data-Centric AI Competition slide
The Batch Newsletter

The Batch: Computers Spawn Computers, Self-Riding Bike, AI-Against-Covid Progress Report, Handwriting Deciphered

I’m thrilled to announce the first data-centric AI competition! I invite you to participate.For decades, model-centric AI competitions, in which the dataset is held fixed while you iterate on the code, have driven our field forward.
Andrew Ng and his family on his graduation day
The Batch Newsletter

The Batch: Face Recognition at the Border, Robot Manicurists, Irresponsible AI, Synthesizing Real-World Scenes

Around the world, students are graduating. If you’re one of them, or if someone close to you is graduating, congratulations!!! My family swapped pictures on WhatsApp recently and came across this one, which was taken when I graduated from Carnegie Mellon (I’m standing in the middle).
Photograph of a two-way road in the woods
The Batch Newsletter

The Batch: Autonomous Weapons Used in Combat, Tesla Doubles Down on Computer Vision, Transformers Decipher Proteins

In school, most questions have only one right answer. But elsewhere, decisions often come down to a difficult choice among imperfect options. I’d like to share with you some approaches that have helped me make such decisions.
Conventional and data-centric benchmarks
The Batch Newsletter

The Batch: Face Recognition for the Masses, Labeling Libel, Documenting Datasets, What Machines Want to See

Benchmarks have been a significant driver of research progress in machine learning. But they've driven progress in model architecture, not approaches to building datasets, which can have a large impact on performance in practical applications.
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The Batch Newsletter

The Batch: Surgical Robots Go Autonomous, Virtual Reality On Speed, AI Crossword Champ, Algorithms For Orcas

I decided last weekend not to use a learning algorithm. Sometimes, a non-machine learning method works best. Now that my daughter is a little over two years old and highly mobile, I want to make sure the baby gate that keeps her away...
Pictures of Robert Crowe, Andrew Ng and Laurence Moroney (from left to right)
The Batch Newsletter

The Batch Special Issue! Machine Learning in Production: MLOps at scale with Amazon, Google, Microsoft

So you’ve trained an accurate neural network model in a Jupyter notebook. You should celebrate! But . . . now what? Machine learning engineering in production is an emerging discipline that helps individual engineers and teams put models into the hands of users.

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