Summary AI: Startup Vs Incumbent Value - by Elad Gil - Elad Blog open.substack.com
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One Line
The author explores the distribution of value and profits in the AI industry, highlighting rapid innovation in various areas such as text and image generation, with expectations of expansion into voice transcription.
Slides
Slide Presentation (7 slides)
Key Points
- In previous technology waves, the value captured by startups versus incumbents varied, with some waves favoring startups and others favoring incumbents.
- In the prior wave of AI, the value largely went to incumbents despite a lot of startup activity.
- Possible reasons for the lack of startup value in the prior AI wave include the products not being dramatically better than incumbents, data differentiation being more important, and the presence of hard markets.
- The current wave of AI, particularly in unsupervised learning, is expected to have strong startup success in addition to incumbent value.
- Factors contributing to the potential success of startups in this AI wave include better technology, startups providing valuable infrastructure, and clear app use cases without strong incumbents.
Summaries
44 word summary
The author discusses value distribution, revenue, market cap, and profits between AI startups and incumbents. The current wave of AI is different due to rapid innovation across various areas. AI technology enables text and image generation and is expected to expand to voice transcription
173 word summary
In this article, the author discusses the distribution of value, revenue, market cap, and profits between startups and incumbents in various technology waves. They note that in the prior wave of AI, most of the value went to incumbents despite significant startup
The current wave of AI technology is different from previous innovations in AI. There are several reasons for this. Firstly, there is a rapid pace of innovation across various areas, such as language models, image generation, speech to text, and more. This
AI technology has enabled the generation of text and images, which has proven useful for product applications. ML-driven applications are expected to expand beyond text and images to include voice transcription, robots, and video. To maximize the value of this technology, it will
The blog post discusses the value of AI startups compared to incumbents in the industry. The author argues that the current wave of AI is different from previous iterations, as it involves true intelligence rather than just machine learning. This new wave of AI has the