Letters from Andrew Ng

Letters

Agentic Design Patterns Part 4, Planning: Large language models can drive powerful agents to execute complex tasks if you ask them to plan the steps before they act.

Planning is a key agentic AI design pattern in which we use a large language model (LLM) to autonomously decide on what sequence of steps to execute to accomplish a larger task.

Letters

Agentic Design Patterns Part 3, Tool Use: How large language models can act as agents by taking advantage of external tools for search, code execution, productivity, ad infinitum

Tool use, in which an LLM is given functions it can request to call for gathering information, taking action, or manipulating data, is a key design pattern of AI agentic workflows.

Letters

Agentic Design Patterns Part 2, Reflection: Large language models can become more effective agents by reflecting on their own behavior.

Last week, I described four design patterns for AI agentic workflows that I believe will drive significant progress this year: Reflection, Tool use, Planning and Multi-agent collaboration.

Letters

Agentic Design Patterns Part 1: Four AI agent strategies that improve GPT-4 and GPT-3.5 performance

I think AI agent workflows will drive massive AI progress this year — perhaps even more than the next generation of foundation models. This is an important trend, and I urge everyone who works in AI to pay attention to it.

Letters

Life in Low Data Gravity: With generative AI, data is bound less tightly to the cloud provider where it’s stored. This has big implications for developers, CIOs, and cloud platforms.

I’ve noticed a trend in how generative AI applications are built that might affect both big companies and developers: The gravity of data is decreasing.

Letters

The Dawning Age of Agents: LLM-based agents that act autonomously are making rapid progress. Here's what we have to look forward to.

Progress on LLM-based agents that can autonomously plan out and execute sequences of actions has been rapid, and I continue to see month-over-month improvements.

Illustration of a Python inside a cardboard box

Letters

The Python Package Problem: Python packages can give your software superpowers, but managing them is a barrier to AI development.

I think the complexity of Python package management holds down AI application development more than is widely appreciated. AI faces multiple bottlenecks — we need more GPUs, better algorithms, cleaner data in large quantities.

Letters

Three Themes for AI Entrepreneurs: Starting an AI company? Three keys to AI entrepreneurship emerged at AI Fund’s annual co-founder and CEO summit.

Earlier this month, my team AI Fund held its annual co-founder and CEO summit, where many of our collaborators gathered in California for two days to discuss how to build AI companies.

Letters

How to Think About the Privacy of Cloud-Based AI: How private is your data on cloud-based AI platforms? Here's a framework for evaluating risks.

The rise of cloud-hosted AI software has brought much discussion about the privacy implications of using it. But I find that users, including both consumers and developers building on such software

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What If Large Language Models Become a Commodity?: Large language models are proliferating. What are the prospects for Amazon, Google, Meta, Microsoft, OpenAI, and LLM startups?

On the LMSYS Chatbot Arena Leaderboard, which pits chatbots against each other anonymously and prompts users to judge which one generated a better answer...

Letters

The World Needs More Intelligence: Human intelligence is expensive, artificial intelligence is cheap. To solve big problems like climate change, it makes sense to double down on AI.

Last year, a number of large businesses and individuals went to the media and governments and pushed the message that AI is scary, impossible to control, and might even lead to human extinction. Unfortunately they succeeded: Now many people think AI is scary.

World Economic Forum, January 16, 2024: "The Expanding Universe of Generative Models" panelists

Letters

AI On the Agenda at the World Economic Forum: The World Economic Forum at Davos felt like an AI conference, with big takeaways for business and regulation.

Last week, I attended the World Economic Forum, an annual meeting of leaders in government, business, and culture at Davos, Switzerland.