"The Changing Landscape of AI: Startups and Incumbents"

Kazuki

Hatched by Kazuki

Aug 26, 2023

4 min read

0

"The Changing Landscape of AI: Startups and Incumbents"

Introduction:

In the ever-evolving world of technology, the question of what truly feels like work often leads us to uncover our true passions and strengths. The stranger our interests may seem to others, the more they serve as evidence of what we are naturally suited for. But when it comes to the field of artificial intelligence (AI), the distribution of value between startups and incumbents has been a fascinating phenomenon. In this article, we explore the historical trends, the impact of AI on different industries, and the potential shift in power dynamics between startups and incumbents.

The Historical Distribution of Value:

Looking back at the previous waves of technological advancements, we can observe that the distribution of value from AI has varied significantly. During the first wave of the internet, most of the value went to startups such as Google, Amazon, and Facebook, while incumbents like Microsoft and Apple also managed to extend their franchises onto the internet. This resulted in a relatively balanced split of value between startups and incumbents. The mobile wave, on the other hand, saw a greater capture of value by incumbents like Apple and Google, with startups like WhatsApp, Uber, and Instagram also making significant strides. This resulted in a more skewed split of value, with incumbents taking a larger share. However, the crypto wave witnessed almost exclusive startup capture of value, with existing financial services and infrastructure companies playing a minimal role in value creation.

The Battle between Startups and Incumbents:

To beat an incumbent as a startup in any industry, one usually needs to develop a product that is significantly better or focuses on a brand new customer segment or distribution moat that incumbents cannot serve. In general, a 10X better product is required to overcome the advantages of incumbents. However, incumbents have often prevailed due to their data advantage, which is now diminishing as companies leverage the broader internet as an initial training set and adopt models that work more effectively with smaller data sets. Furthermore, the challenging markets that many prior-wave AI companies entered, such as education and healthcare, posed additional obstacles for startups, as technological innovation in these fields often faces resistance from market structures, regulations, and a lack of focus on end-user needs.

The Rise of AI Startups:

While previous AI innovations were noteworthy, the current wave of AI feels different for several reasons. The speed of innovation across various areas is remarkable, making it easier to create products that are 10X better than what incumbents offer. The "why now" factor may simply be a result of a technology sea change. Although GPT-3, a highly advanced AI model, has shown promise, it has not yet sparked the creation of numerous successful startups. However, a model that is 5-10X better than GPT-3 could potentially create an entirely new startup ecosystem while augmenting existing incumbent products. Moreover, there are now infrastructure-centric companies with widespread adoption and growing usage, such as OpenAI, Stability.AI, Hugging Face, and Weights and Biases. These companies provide startups with access to AI technologies and contribute to the growth of the ecosystem.

The Importance of Identifying User Needs:

To fully capitalize on the potential value of AI, it is crucial to avoid the issue of a "hammer-looking-for-a-nail." Instead, startups must identify actual end-user needs and untapped markets that can benefit from the advancements in AI technology. By focusing on addressing these needs, startups can create products that truly add value and compete with incumbents. The incorporation of AI features into existing workflow tools, the automation of repetitive tasks, and the high-fidelity generation of text and images are just a few examples of how AI can enhance product applications and meet user demands.

Actionable Advice:

  • 1. Embrace the technology sea change: Take advantage of the rapid advancements in AI technology to develop products that are significantly better than what incumbents offer. This will help startups overcome the advantages of incumbents and capture a larger share of the value.
  • 2. Prioritize actual end-user needs: Instead of developing technology for the sake of technology, focus on identifying and addressing the needs of your target users. By understanding their pain points and delivering solutions that truly add value, startups can carve out a niche for themselves in the market.
  • 3. Leverage infrastructure-centric companies: Tap into the resources provided by infrastructure-centric companies that have already established themselves in the AI space. These companies offer valuable tools, technologies, and support that can enable startups to build innovative AI-powered products.

Conclusion:

As AI continues to reshape industries and drive technological advancements, the dynamics between startups and incumbents are evolving. While incumbents have historically captured a significant portion of the value generated by AI, the current wave of AI innovations presents an opportunity for startups to gain a larger share. By leveraging the speed of innovation, identifying user needs, and utilizing infrastructure-centric companies, startups can create products that disrupt existing markets and pave the way for exciting times ahead. The key lies in harnessing the power of AI to deliver solutions that truly make a difference in the lives of end-users.

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