This week’s podcast is about SenseTime, which is a leader in computer vision in China / Asia. It’s a fascinating company for looking at the evolving business models of AI software. The two big questions are:
- What are the unit economics of large AI companies?
- What types of scale advantages and network effects do large AI companies?
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- Moats and Marathons (Part 1): How to Build and Measure Competitive Advantage in Digital Businesses Kindle Edition
I break the network effects question into three sub-questions:
- Do existing AI models get better the more they are used?
- How much? Does it flatline? Does it keep increasing?
- Do existing AI models make each other smarter and better?
- Do existing AI models and the data they collect make additional AI models smarter? Do they make them faster and cheaper to train?
My working for conclusions are:
- This is mostly an integrated software bundle going for global scale.
- It’s a learning platform with a new type of network effect.
- It is building an innovation platform, with another network effect.
- SenseTime and an Introduction to AI Software Economics (1 of 3) (Asia Tech Strategy – Daily Article)
- 3 Lessons in China AI/ML from Artefact (Data Consultants and Digital Marketers)
- Adobe Inc. and the Power of Old School Software Economics (Asia Tech Strategy – Podcast 81)
From the Concept Library, concepts for this article are:
- Learning Platforms
- Integrated Bundles
- Artificial Intelligence
- Computer Vision
From the Company Library, companies for this article are:
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