Letters from Andrew Ng

It’s time to move beyond the stereotype that machine learning systems need a lot of data. While having more data is helpful, large pretrained models make it practical to build viable systems using a very small labeled training set — perhaps just a handful of examples specific to your application.

A few weeks ago, I wrote about my team at Landing AI’s work on visual prompting. With the speed of building machine learning applications through text prompting and visual prompting, I’m...

My team at Landing AI just announced a new tool for quickly building computer vision models, using a technique we call Visual Prompting. It’s a lot of fun! I invite you to try it.

Last week, the tech news site The Information reported an internal controversy at Google. Engineers were concerned that Google’s Bard large language model was trained in part on output from OpenAI’s ChatGPT, which would have violated OpenAI’s terms of use.

Generative AI is taking off, and along with it excitement and hype about the technology’s potential. I encourage you to think of it as a general-purpose technology (GPT, not to be confused with the other GPT: generative pretrained transformer).

Here’s a quiz for you. Which company said this? “It’s always been a challenge to create computers that can actually communicate with and operate at anything like the level of a human mind...

Landing AI, a sister company of DeepLearning.AI, just released its computer vision platform, LandingLens, for everyone to start using for free. You can try it now.

As you can read in this issue of The Batch, Microsoft’s effort to reinvent web search by adding a large language model snagged when its chatbot went off the rails. Both Bing chat and Google’s Bard...

Recent successes with large language models have brought to the surface a long-running debate within the AI community: What kinds of information do learning algorithms need in order to gain intelligence?

In late December, Google reportedly issued a “code red” to raise the alarm internally to the threat of disruption of its business by large language models like OpenAI’s ChatGPT. Do large language models (LLMs) endanger Google's search engine business?

As we enter the new year, let’s view 2023 not as a single year, but as the first of more in which we will accomplish our long-term goals. Some results take a long time to achieve, and even though...

What should be AI’s role in moderating the millions of messages posted on social media every day? The volume of messages means that automation is required. But the question of what is appropriate moderation versus inappropriate censorship lingers.

One of the dangers of large language models (LLMs) is that they can confidently make assertions that are blatantly false. This raises worries that they will flood the world with misinformation. If they could moderate their degree of confidence appropriately, they would be less likely to mislead.

On Monday, the European Union fined Meta roughly $275 million for breaking its data privacy law. Even though Meta’s violation was not AI specific, the EU’s response is a reminder that we need to build AI systems that preserve user privacy...

Last week, Facebook’s parent company Meta released a demo of Galactica, a large language model trained on 48 million scientific articles. Two days later, amid controversy regarding the model’s potential to generate false or misleading articles, the company withdrew it.