Letters from Andrew Ng
Personal messages to the AI community
Letters
We Iterate on Models. We Can Iterate on Evals, Too: Building automated evals doesn’t need to be a huge investment. Start with a few quick-and-dirty examples and iterate!
I’ve noticed that many GenAI application projects put in automated evaluations (evals) of the system’s output probably later — and rely on humans to manually examine and judge outputs longer — than they should.
Letters
The Benefits of Lazy Prompting: You don’t always need to provide context when prompting a large language model. A quick prompt can be enough.
Contrary to standard prompting advice that you should give LLMs the context they need to succeed, I find it’s sometimes faster to be lazy and dash off a quick, imprecise prompt and see what happens.
Letters
Wait Your Turn! Conversation by Voice Versus Text: Text interactions require taking turns, but voices may interrupt or overlap. Here’s how AI is evolving for voice interactions.
Continuing our discussion on the Voice Stack, I’d like to explore an area that today’s voice-based systems mostly struggle with: Voice Activity Detection (VAD) and the turn-taking paradigm of communication.
Letters
The Difference Between “AI Safety” and “Responsible AI”: Talk about “AI safety” obscures an important point; AI isn't inherently unsafe. Instead, let’s talk about “responsible AI.”
At the Artificial Intelligence Action Summit in Paris this week, U.S. Vice President J.D. Vance said, “I’m not here to talk about AI safety.
Letters
How to Cool a Warming Planet: The only plausible path to keeping climate change in check is geoengineering.
Greetings from Davos, Switzerland! Many business and government leaders are gathered here again for the annual World Economic Forum to discuss tech, climate, geopolitics, and economic growth.
Letters
AI Product Managers Will Be In-Demand: As the cost of building AI products falls, demand for people who know what to build will rise. Get ready for an explosion in AI Product Management!
Writing software, especially prototypes, is becoming cheaper. This will lead to increased demand for people who can decide what to build. AI Product Management has a bright future!
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