The debate over the existence of an "AI bubble" intensified recently, with tech leaders like Mark Zuckerberg and Bill Gates acknowledging signs of market instability. However, a more nuanced perspective suggests that the AI landscape isn't a single bubble, but rather a series of distinct bubbles, each with its own trajectory and potential for collapse.

The AI ecosystem can be viewed as three layers, each with different economic characteristics and risk profiles. The most vulnerable layer consists of companies that repackage existing AI models, such as OpenAI's API, with user-friendly interfaces and limited added functionality. These "wrapper companies" are particularly susceptible to market corrections.

While specific financial figures for these wrapper companies are difficult to isolate, the overall investment in AI startups reached record levels in recent years. According to a report by Stanford University, private investment in AI surged to over $93.5 billion in 2021. This influx of capital fueled the growth of numerous AI-powered applications, many of which rely on reselling access to foundation models.

The proliferation of wrapper companies has created a crowded market, where differentiation is challenging and customer loyalty is low. As competition intensifies, these companies face pressure to lower prices, squeezing profit margins and increasing the risk of failure. Furthermore, the underlying AI models are constantly evolving, potentially rendering the wrappers obsolete.

The AI industry has seen rapid advancements in recent years, driven by breakthroughs in deep learning and natural language processing. Companies like OpenAI, Google, and Microsoft have invested heavily in developing powerful AI models that can perform a wide range of tasks, from generating text to creating images. However, the high cost of training and maintaining these models has created a barrier to entry for smaller players.

Looking ahead, the future of the AI ecosystem will likely be shaped by the interplay between these three layers. While wrapper companies may face challenges, companies that develop and own the underlying AI models are likely to remain dominant. The long-term success of the AI industry will depend on its ability to deliver tangible value to businesses and consumers, and to address ethical concerns surrounding bias, privacy, and job displacement.