# Andrew-ng

Published articles for Andrew-ng.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## Andrew Ng Launches LearnVector: AI-Native One-to-One Learning with $100M from Coursera

DevFeed: [Andrew Ng Launches LearnVector: AI-Native One-to-One Learning with $100M from Coursera](<https://devfeed.tech/articles/andrew-ng-launches-learnvector-ai-native-one-to-one-learning-with-100m-from-coursera-56196.md>)

Original publisher: [Read original article](<https://www.developersdigest.tech/blog/learnvector-andrew-ng-ai-native-learning-hn-analysis>)

Author: Developers Digest

Published: 2026-07-29T00:00:00Z

Content type: article

Language: en

Sources: [Developers Digest](<https://devfeed.tech/sources/developers-digest.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Agentic AI](<https://devfeed.tech/topics/what-is-agentic-ai.md>), [Learning](<https://devfeed.tech/topics/learning.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-ai](<https://devfeed.tech/tags/agentic-ai.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-education](<https://devfeed.tech/tags/ai-education.md>), [ai-native](<https://devfeed.tech/tags/ai-native.md>), [andrew-ng](<https://devfeed.tech/tags/andrew-ng.md>), [hacker-news](<https://devfeed.tech/tags/hacker-news.md>), [learning](<https://devfeed.tech/tags/learning.md>), [learnvector](<https://devfeed.tech/tags/learnvector.md>), [news](<https://devfeed.tech/tags/news.md>)

### AI overview

Andrew Ng's LearnVector aims to create one-to-one learning experiences powered by agentic AI, with $100 million in backing from Coursera. The article examines the company's vision, Hacker News reaction, and implications for the future of learning.

### Source excerpt

Andrew Ng's new AI company LearnVector aims to build one-to-one learning experiences powered by agentic AI, backed by $100M from Coursera. A look at the vision, the HN reaction, and what it means for the future of learning.

## Andrew Ng on Data-Centric AI, Foundation Models, and Small-Data Solutions

DevFeed: [Andrew Ng on Data-Centric AI, Foundation Models, and Small-Data Solutions](<https://devfeed.tech/articles/andrew-ng-unbiggen-ai-50926.md>)

Original publisher: [Read original article](<https://spectrum.ieee.org/andrew-ng-data-centric-ai>)

Author: Eliza Strickland

Published: 2022-02-09T15:31:12Z

Content type: article

Language: en

Sources: [IEEE Spectrum](<https://devfeed.tech/sources/ieee-spectrum.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Computer vision](<https://devfeed.tech/topics/computer-vision.md>), [Deep learning](<https://devfeed.tech/topics/deep-learning.md>), [AI Research](<https://devfeed.tech/topics/ai-research.md>), [AI Foundation Models](<https://devfeed.tech/topics/ai-foundation-models.md>), [Natural language processing](<https://devfeed.tech/topics/nlp.md>), [Scalability](<https://devfeed.tech/topics/scalability.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [andrew-ng](<https://devfeed.tech/tags/andrew-ng.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [compute](<https://devfeed.tech/tags/compute.md>), [computer-vision](<https://devfeed.tech/tags/computer-vision.md>), [deep-learning](<https://devfeed.tech/tags/deep-learning.md>), [efficiency](<https://devfeed.tech/tags/efficiency.md>), [foundation-models](<https://devfeed.tech/tags/foundation-models.md>), [type-cover](<https://devfeed.tech/tags/type-cover.md>)

### AI overview

An interview with Andrew Ng examines data-centric AI, the continued scaling of deep learning and foundation models, and the role of smaller datasets in improving efficiency, accuracy, and bias. Ng also discusses computer vision and the challenges of building foundation models for video.

### Source excerpt

Andrew Ng has serious street cred in artificial intelligence. He pioneered the use of graphics processing units (GPUs) to train deep learning models in the late 2000s with his students at Stanford University, cofounded Google Brain in 2011, and then served for three years as chief scientist for Baidu, where he helped build the Chinese tech giant's AI group. So when he says he has identified the next big shift in artificial intelligence, people listen. And that's what he told IEEE Spectrum in an exclusive Q&A. Ng's current efforts are focused on his company Landing AI, which built a platform called LandingLens to help manufacturers improve visual inspection with computer vision. He has also become something of an evangelist for what he calls the data-centric AI movement, which he says can yield "small data" solutions to big issues in AI, including model efficiency, accuracy, and bias. Andrew Ng on... What's next for really big models The career advice he didn't listen to Defining the data-centric AI movement Synthetic data Why Landing AI asks its customers to do the work The great advances in deep learning over the past decade or so have been powered by ever-bigger models crunching ever-bigger amounts of data. Some people argue that that's an unsustainable trajectory. Do you agree that it can't go on that way? Andrew Ng: This is a big question. We've seen foundation models in NLP [natural language processing]. I'm excited about NLP models getting even bigger, and also about the potential of building foundation models in computer vision. I think there's lots of signal to still be exploited in video: We have not been able to build foundation models yet for video because of compute bandwidth and the cost of processing video, as opposed to tokenized text. So I think that this engine of scaling up deep learning algorithms, which has been running for something like 15 years now, still has steam in it. Having said that, it only applies to certain problems, and there's a set