Letters from Andrew Ng

Students benefit from tutoring, but training tutors is expensive. A study shows that large language models can boost tutors’ effectiveness in real time.

A “10x engineer” — a widely accepted concept in tech — purportedly has 10 times the impact of the average engineer.

Big AI companies found creative ways to gain cutting-edge technology and talent without buying startups.

Looking for work in AI? Brush up on your language skills. Employers are hiring prompt engineers to write natural-language prompts for AI models, The Washington Post reported. They include Anthropic, Boston Children’s Hospital, and the London law firm Mischon de Reya.

A survey of data scientists reveals a field of great opportunities but also room for improvement. The 2022 “State of Data Science” report from Anaconda, maker of a popular Python distribution, surveyed 3,493 students, teachers, and employees.

Every job search is different. Here are some tips from Andrew Ng to increase the odds you’ll find the right position.

Last week, I wrote about switching roles, industries, or both as a framework for considering a job search. If you’re preparing to switch roles or industries, there’s a lot about your target job that you probably don’t know.

Andrew Ng presents a framework for job seekers in AI, especially those entering from a different field.

Pharmaceutical companies in several countries are hiring machine learning engineers at increasing rates.

Last week’s letter focused on coming up with AI project ideas, part of a series on how to build a career in the field. This letter describes how a sequence of projects might fit into your career path.

A website that aggregates AI jobs revealed the roles that are most in-demand. Ai-jobs.net published its second annual list of the job titles that appeared most frequently in its listings.

In the last two letters, I wrote about developing a career in AI and shared tips for gaining technical skills. This time, I’d like to discuss an important step in building a career: project work.

Last week, I wrote about key steps for building a career in AI: learning technical skills, doing project work, and searching for a job, all of which is supported by being part of a community. In this letter, I’d like to dive more deeply into the first...

The rapid rise of AI has led to a rapid rise in AI jobs, and many people are building exciting careers in this field. A career is a decades-long journey, and the path is not always straightforward.

Years ago, I had to choose between a neural network and a decision tree learning algorithm. It was necessary to pick an efficient one, because we planned to apply the algorithm to a very large set of users on a limited compute budget.