Letters from Andrew Ng

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Letters

Everyone Can Benefit From Generative AI Skills: Announcing “Generative AI For Everyone,” a new course that requires no background in coding or AI.

I’ve always believed in democratizing access to the latest advances in artificial intelligence. As a step in this direction, we just launched “Generative AI for Everyone” on Coursera.

Letters

Exaggerated Fear of AI Is Causing Real Harm: AI isn't likely to cause human extinction, but worry that it might is scaring away young people from the field.

Welcome to the Halloween special issue of The Batch, where we take a look at fears associated with AI. In that spirit, I’d like to address a fear of mine: Sensationalist claims that AI could bring about human extinction will cause serious harm.

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Letters

Why AI Will Move to Edge Devices: AI will continue to run in data centers, but technology and economics are pushing it to the edge as well.

I wrote earlier about how my team at AI Fund saw that GPT-3 set a new direction for building language applications, two years before ChatGPT was released. I’ll go out on a limb to make another prediction

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Letters

Horror and Heartbreak: It's time for people of conscience to condemn Hamas’ attack on Israel.

Over the weekend, Hamas launched a surprise terrorist attack on Israel, slaughtering and kidnapping civilians. The images in the media are horrifying, and over 1,000 people...

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Coding Skill is More Valuable Than Ever: Don't let the ease of prompting large language models discourage you from learning to code.

Andrej Karpathy, one of the Heroes of Deep Learning who currently works at OpenAI, quipped, “The hottest programming language is English.” While I appreciate the sentiment...

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Better Relationships Through AI: Doctors say there’s an epidemic of loneliness. Here's how large language models can help.

Improvements in chatbots have opened a market for bots integrated with dating apps. I’m concerned that AI romantic partners create fake relationships that displace, rather than strengthen, meaningful human relationships.

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Letters

Which AI Applications Should You Build? Here's How to Decide: AI isn't ideal for everything. How can you decide which use cases to build? Think about tasks, not jobs.

While AI is a general-purpose technology that’s useful for many things, it isn’t good for every task under the sun. How can we decide which concrete use cases to build? If you’re helping a business figure out where to apply AI, I’ve found the following recipe useful as a brainstorming aid…

Letters

Where Are the Opportunities in AI? Here's Where to Look: Generative AI opens the way to create valuable products, especially in the application layer.

I recently spoke about “Opportunities in AI” at Stanford’s Graduate School of Business. I'd like to share a few observations from that presentation, and I invite you to watch the video (37 minutes).

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Unlocking AI's Potential for Positive Impact: AI can make a difference when stakes are high and lives hang in the balance. Learn how in our new specialization, AI for Good.

Amidst rising worry about AI harms both realistic (like job loss) and unrealistic (like human extinction), It’s critical to understand AI’s potential to do tremendous good. Our new specialization is designed to empower people to identify, scope, and build impactful AI projects.

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The Unlikely Roots of Large Language Models: U.S. military funding helped build the foundation for ChatGPT and other innovations in natural language processing.

I’d like to share a part of the origin story of large language models that isn’t widely known. A lot of early work in natural language processing (NLP) was funded by U.S. military intelligence agencies that needed machine translation and speech recognition capabilities.

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The Hidden Value of Deep Technical Knowledge: What's the best way to prompt a large language model? Understand the technology.

Machine learning development is an empirical process. It’s hard to know in advance the result of a hyperparameter choice, dataset, or prompt to a large language model (LLM).

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Tips for Taking Advantage of Open Large Language Models: Prompting? Few-Shot? Fine-Tuning? Pretraining from scratch? Open LLMs mean more options for developers.

An increasing variety of large language models (LLMs) are open source, or close to it. The proliferation of models with relatively permissive licenses gives developers more options for building applications.