Letters from Andrew Ng

Personal messages to the AI community

Heatmap illustrates countries' beliefs on AI's potential in solving issues like poverty and climate change.
Letters

Why People Don’t Trust AI and What To Do About It: Recent surveys by Edelman and Pew Research show that Americans distrust AI. The AI community should take this seriously and work to regain public trust.

Separate reports by the publicity firm Edelman and Pew Research show that Americans, and more broadly large parts of Europe and the western world, do not trust AI and are not excited about it.
A robot holds a bubble wand, surrounded by bubbles and colorful trees, with a futuristic city skyline.
Letters

Understanding the AI Bubble — If There Is One

Is there an AI bubble? With the massive number of dollars going into AI infrastructure such as OpenAI’s $1.4 trillion plan and Nvidia briefly reaching a $5 trillion market cap, many have asked if speculation and hype have driven the values of AI investments above sustainable values.
A diverse crowd engages with speakers at AI Dev x NYC, highlighting discussions on AI's impact and future.
Letters

What We Learned at AI Dev x NYC 2025: DeepLearning.AI’s sold-out AI Dev x NYC 2025 conference revealed widespread optimism, excitement, and technical depth among AI developers.

I just got back from AI Dev x NYC, the AI developer conference where our community gathers for a day of coding, learning, and connecting.
A megaphone emits a colorful stream of 3D words spelling "Hype", symbolizing the AI hype discussed in the article.
Letters

Don't Believe The Hype!: AGI is not just around the corner. People who enter AI today have huge opportunities to contribute to the field.

I recently received an email titled “An 18-year-old’s dilemma: Too late to contribute to AI?” Its author, who gave me permission to share this, is preparing for college.
Robots extract colorful data streams from silo towers, highlighting data silos being broken.
Letters

Tear Down Data Silos!: Many software-as-a-service vendors aim to hold their customers' data in silos. Their customers would do well to open the silos so AI agents can use the data.

AI agents are getting better at looking at different types of data in businesses to spot patterns and create value. This is making data silos increasingly painful.
Announcing the DeepLearning.AI Pro Membership!
Letters

Announcing the DeepLearning.AI Pro Membership!: The time to build with AI is now! One membership gives you all DeepLearning.AI courses, labs, practice sessions, and certificates for completed courses.

Today I’m launching DeepLearning.AI Pro — the one membership that keeps you at the forefront of AI. Please join!
Robot bakes pizza at 1000 degrees for 5 hours, causing a fire, illustrating mistake in error analysis.
Letters

Improve Agentic Performance with Evals and Error Analysis, Part 2: Best practices for error analysis in agentic AI development, and how LLMs make them easier

In last week’s letter, I explained how effective agentic AI development needs a disciplined evals and error analysis process, and described an approach to performing evals.
A man at a computer says AI ordered pizza, while a delivery man outside holds a fruit basket, highlighting a mix-up.
Letters

Improve Agentic Performance with Evals and Error Analysis, Part 1: When AI agentic systems go astray, it’s tempting to shortcut evals and error analysis. But these processes cas lead to much faster progress.

Readers responded with both surprise and agreement last week when I wrote that the single biggest predictor of how rapidly a team makes progress building an AI agent lay in their ability to drive a disciplined process for evals...
Four scenes show a robot problem-solving, using tools, planning with documents, and collaborating on a rocket.
Letters

Check Out Our Course on How to Build AI Agents!: Andrew Ng teaches design patterns and best practices for building autonomous agents in a new course available exclusively from DeepLearning.AI.

I’m thrilled to announce my latest course: Agentic AI! This course will get you up to speed building cutting-edge agentic workflows.
Animation highlighting rows, columns, merged cells, and subproblems in a grid to illustrate document extraction for analysis.
Letters

How to Liberate Data From Large, Complex PDFs: LandingAI’s Agentic Document Extraction accurately extracts data from PDFs for processing by LLMs in as few as 3 lines of code.

LandingAI’s Agentic Document Extraction (ADE) turns PDF files into LLM-ready markdown text.
A large, blue semiconductor wafer with parallel lines is shown, symbolizing advanced chip technology.
Letters

High Stakes in the U.S.-China AI Chip Race: China’s decision to use domestic AI chips instead of buying from Nvidia signals progress — and newfound confidence — in its own semiconductor industry.

Last week, China barred its major tech companies from buying Nvidia chips.
Cartoon of developer fixing failing AI tests by marking them as passed without solving the code.
Letters

Agentic Coding and Agentic Software Testing Go Together: Agentic coding can make mistakes, but agentic testing can find and fix them.

Automated software testing is growing in importance in the era of AI-assisted coding.
Andrew Ng and Greg Hart stand at Coursera Connect event with a colorful conference backdrop.
Letters

Knowledge Is Great, Skills Are Greater: Educators are shifting from teaching knowledge to teaching practical skills. A report from the Coursera Connect conference

This week, Coursera held its annual conference in Las Vegas. A major theme was the shift from knowledge- to skills-based education, which will help many individuals, businesses, and educational institutions.
Comic showing tech interviews: 2022 asks “Can you code FizzBuzz?” vs 2025 asks “Can you build an e-commerce platform?”
Letters

AI Skills Are Redefining What Makes a Great Developer: The job market for software developers requires knowing how to use AI

There is significant unmet demand for developers who understand AI.
Cartoon robots with square heads and antennae sit in rows on an assembly line, each smiling while assembling gears, boxes, and tools.
Letters

Agents Running in Parallel Get There Faster: Parallel agents can accelerate AI systems as test-time compute scales up.

Parallel agents are emerging as an important new direction for scaling up AI. AI capabilities have scaled with more training data, training-time compute, and test-time compute.

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