How to Build a Defensible AI Startup in 2023: Examining Emergent Abilities in Large Language Models

How to Build a Defensible AI Startup in 2023: Examining Emergent Abilities in Large Language Models

Introduction:
The year 2023 has seen a surge in the development of innovative AI startups that are capturing the public's imagination. Companies like Midjourney, Runway, and Stable Diffusion have emerged as frontrunners in the AI industry. Interestingly, the most delightful innovations are not coming from established companies but from startups that are embracing the power of AI. In this article, we will explore the key strategies to build a defensible AI startup in 2023, while also examining the concept of emergent abilities in large language models.

The Power of Speed and Creative Thinking:
When it comes to startups, speed is a definitive advantage against incumbent companies. Midjourney, for instance, has gained a competitive edge through quick product execution. This highlights the importance of being agile and proactive in the AI industry. Additionally, startups should focus on exploring new product paradigms and interfaces made possible by AI. By creating unique and innovative products, startups can establish a more defensible position compared to existing software companies who may easily add AI tools to their product suite.

The Rise of Consumer AI Companies:
Successful products in the AI space often start out resembling consumer companies. The largest Discord communities, such as Midjourney, Open AI, Blue Willow, and Leonardo.ai, are all consumer AI companies today. To grow mindshare within the AI community, it is crucial for startups to develop an online personality and engage with relevant issues such as development and regulation. Offering perks to existing community members, such as gated access to beta users through Discord, can foster customer evangelism and attract new members. The appointment of power users as moderators in branded community spaces can also enhance engagement and create a sense of community.

Building Long-term Moats:
While startups can initially win by moving quickly, it is essential to build long-term moats that set them apart from big tech and incumbents. Verticalized solutions, based on a deep understanding of a target persona, can be one of the best defensible ways to build in AI. By catering to specific industries or niches, startups can establish themselves as experts and create barriers to entry for competitors. Moats can be further strengthened by prioritizing collaboration, integrations, permissioning, and workflow. These factors contribute to cementing a startup's position in the market.

Examining Emergent Abilities in Large Language Models: The concept of emergence, popularized by Nobel laureate Philip Anderson in his 1972 essay "More is Different," suggests that quantitative changes in a system can result in new behavior. This idea applies to large language models, where emergent abilities have been observed. An emergent ability is one that is present in larger models but not in smaller ones. As language models scale up, their behavior can either predictably improve or unexpectedly surge from random performance to above random at specific scale thresholds. These emergent abilities have sparked scientific interest and should drive future research in the field of large language models.