Overvaluing assets in a new tech wave is common and leads to corrections, as seen with mobile and cloud. This differs from a systemic collapse, which requires fundamental weaknesses like the massive debt and fraud that fueled the dot-com crash. Today's AI buildout is funded by cash-rich companies.
The first internet live stream was a coffee pot, which seemed like a silly toy. This pattern repeats: transformative technologies begin with seemingly trivial applications. Skeptics consistently confuse this initial silliness with a lack of serious potential, failing to see how these "toys" foreshadow massive future industries.
The abundance of private capital means the most successful companies no longer need to go public for growth funding. This disrupts the traditional VC model, where IPOs are a primary exit path, forcing firms to re-evaluate how and when they achieve liquidity for their limited partners, even for their best assets.
Public focus on capital-intensive LLMs from companies like OpenAI obscures the true market landscape. A bigger opportunity for venture investment lies in the "long tail"—a vast ecosystem of companies building specialized generative models for specific modalities like images, video, speech, and music.
For decades, AI only offered incremental improvements (e.g., 20% better fraud detection), which benefited large incumbents. Generative AI is a step-change, enabling entirely new user behaviors like creativity and emotional connection, creating the "1000x better" disruption needed to build new, iconic companies.
Critics argue AI revenue must grow exponentially to justify investment. However, for incumbents like Meta, this isn't net-new revenue. It's a massive internal budget shift from established products to new AI features, redirecting existing user engagement and spend rather than creating a market from scratch.