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The New New Moats | Greylock
Source: greylock.com
Article summary:
1. The development of open source AI models has disrupted traditional economic moats, shifting power back to startups that can leverage foundation models in their products.
2. The critical components to building worthwhile AI products are foundation models and the computing resources needed to power them, which can potentially shift value from big cloud providers to startups.
3. Startup founders who succeed tend to execute a dual-pronged strategy: attacking legacy player moats while simultaneously building their own defensible moats that ride the wave of platform shifts like AI.
Article analysis:
The article "The New New Moats" by Greylock discusses the potential for startups to build defensible moats using AI. The author revisits their previous framework from six years ago and updates it based on recent developments in AI, particularly the use of transformer models like GPT-4, PaLM2, and LlaMA. The article explores traditional economic moats such as economies of scale, network effects, deep tech/IP/trade secrets, high switching costs, and brand/customer loyalty. The author argues that startups need to build systems of intelligence powered by AI applications to create new moats.
Overall, the article provides a comprehensive overview of the potential for AI to create new moats for startups. However, there are some potential biases and missing points of consideration. For example, the article focuses primarily on the benefits of open source AI models but does not explore any potential risks or drawbacks associated with this approach. Additionally, while the article acknowledges that existing companies and startups have been able to add generative AI into their applications, it does not address any potential ethical concerns or challenges associated with this technology.
Furthermore, the article presents a one-sided view of the potential for AI to disrupt traditional economic moats without exploring any counterarguments or alternative perspectives. While it is true that AI has the potential to disrupt existing moats and create new ones for startups, there may be other factors at play that could limit its impact or effectiveness.
In terms of promotional content, the article does mention several startups that are building their own models to produce applications and provide them as a service to others. However, it is unclear whether these companies have any affiliation with Greylock or if they are simply being used as examples.
Overall, while "The New New Moats" provides valuable insights into how startups can leverage AI to build defensible moats in today's rapidly changing business landscape, readers should be aware of its potential biases and limitations.
Topics for further research:
Ethical concerns with AI in business
Risks of open source AI models
Limitations of AI in disrupting traditional economic moats
Alternative perspectives on the impact of AI on business moats
Challenges of integrating generative AI into applications
Examples of startups building AI-powered systems of intelligence