The Future of Generative AI and Information Organization

The Future of Generative AI and Information Organization

Introduction:

The rapid growth of generative AI applications and the overwhelming abundance of information have raised questions about the ownership and organization of these emerging technologies. This article explores the current landscape of generative AI platforms and the challenges faced by different players in the industry. It also delves into the need for better curation and organization of information in the digital age. By examining common points and unique insights, we can gain a deeper understanding of the future direction of these technologies.

Generative AI Platforms: Winners and Challenges:

Infrastructure vendors have emerged as the biggest winners in the generative AI market, capturing the majority of revenue flowing through the stack. On the other hand, application companies experience rapid revenue growth but struggle with retention, product differentiation, and gross margins. Model providers, while responsible for the existence of this market, have not yet achieved large-scale commercial success. However, the growth of generative AI applications continues to be staggering, driven by novelty and diverse use cases.

The Role of Differentiation and Hosting:

In the absence of strong technical differentiation, both B2B and B2C apps create long-term customer value through network effects, data retention, and complex workflows. Vertically integrated apps have an advantage in driving differentiation, but it remains unclear whether selling end-user apps is the best path to sustainability in the generative AI business. Model providers are increasingly recognizing the importance of hosting, with growing demand for proprietary APIs and hosting services for open-source models. Some model providers have also incorporated public good explicitly into their mission, without hindering their fundraising efforts.

The Influence of Infrastructure Companies:

Infrastructure companies, particularly Nvidia, have become significant beneficiaries in the generative AI market. Running the majority of AI workloads, these companies hold a lucrative and seemingly defensible position in the stack. They leverage various moats such as scale, supply-chain, ecosystem, algorithmic, distribution, and data pipeline advantages. However, the durability of these moats remains uncertain, and it is too early to determine if direct network effects will dominate any layer of the stack.

The Need for Information Organization:

As information becomes increasingly abundant, the challenge lies in organizing trustworthy and relevant content. The current focus on monetizing clicks and supporting advertisers has led to ethically dubious design choices and trust gaps on platforms like Google. Vertical search aggregators work well when users know exactly what they want, but they fail to address the needs of overwhelmed consumers seeking better discovery and curation. The conversation around curation should shift towards structuring content feeds and creating goal-oriented interfaces.

The Pitfalls of Curation Sites:

Curation sites often start with high-quality recommendations but struggle to maintain the same level of quality as they scale. Crowdsourcing and scraping become common practices, leading to a decline in content quality. Vertical search aggregators like Yelp then offer more utility, leaving curation sites feeling like marketing blogs. Ad-driven models create a competition for attention between advertisers and content producers, compromising the user experience.

Towards Better Information Organization:

The solution lies in filtering, organizing, curating, and indexing the vast amount of information being created. Curation sites should move away from a never-ending-now orientation and focus on more goal-oriented interfaces. Ben Evans aptly states that all curation grows until it requires search, and all search grows until it requires curation. Token-based business models show promise by giving ownership to stakeholders and allowing subscribers to benefit from future upside, ensuring sustainable growth.

Actionable Advice:

• 1. For generative AI businesses, focus on technical differentiation and explore alternative paths to commercial success beyond selling end-user apps.

• 2. Invest in hosting services and proprietary APIs to meet the growing demand for generative AI models.

• 3. Prioritize curation that is structurally focused and goal-oriented, placing user experience and trust at the forefront.

Conclusion:

The future of generative AI and information organization is still evolving. While infrastructure companies currently dominate the market, the landscape remains uncertain, with both horizontal and vertical approaches showing potential. The key lies in addressing the challenges faced by application companies, model providers, and curation platforms to create sustainable and user-centric solutions. By incorporating actionable advice and fostering innovation, the potential of generative AI and information organization can be harnessed for the benefit of society.