The discussion surrounding the viability of AI companies, particularly those focused on large language models (LLMs), highlights the significant financial and operational challenges they face. Building these models is an expensive endeavor, with companies like OpenAI reportedly burning through billions annually to fund their research and development. As the technology evolves, the costs associated with creating new models are expected to rise, making it increasingly difficult to maintain a competitive edge. The analogy of climbing Mount Everest is used to illustrate this point: as one ascends, the challenges become greater, and the resources required to push further become more demanding. Despite these challenges, there is a strong belief in the potential of LLMs as the next big technological breakthrough. Companies are motivated by the prospect of creating artificial general intelligence and the financial rewards that could follow. However, the rapid pace of innovation means that the value of existing models diminishes quickly. For instance, if a new and improved model is released, users can easily switch to it, making it essential for companies to consistently deliver top-tier models to remain relevant. The article also contrasts the AI industry with traditional cloud service providers. While building a cloud infrastructure requires significant time and investment, creating an AI model can be achieved relatively quickly, especially if a team of skilled researchers decides to leave an established company and start anew. This creates a precarious environment for AI vendors, as their competitive advantages can be eroded swiftly. The question of what constitutes a sustainable competitive advantage for LLM vendors remains open. Brand loyalty, inertia, and the development of superior applications are potential factors, but the ongoing need for substantial investment in model improvement poses a significant risk. Smaller companies, in particular, may struggle to survive without a steady revenue stream or the ability to secure continuous funding. As the market evolves, timing becomes crucial. The current hype surrounding AI may not last indefinitely, and the companies that succeed will likely be those that can adapt to changing market conditions rather than simply being the fastest to innovate. The discussion raises important considerations about the future of AI companies and the sustainability of their business models in a rapidly changing landscape.