Investment Insights: Why Investors are Banking on Thinking Machines Lab

This week, Business Insider reporter Ben Bergman reported exciting news in the tech world: Mira Murati is in the process of raising approximately $2 billion for her nascent AI venture, Thinking Machines Lab. Despite being only a few months old and having a small team without any products yet, the startup is already valued at around $10 billion. This raises an interesting question: why are investors willing to allocate such substantial funds to a relatively undeveloped company?

Understanding the Allure: The Power Law in Venture Capital

The stark reality is that early-stage investments are inherently risky. However, in the realm of venture capital, the potential for substantial returns can drive investor interest. Murati’s association with OpenAI—recently valued at $300 billion—exemplifies the high stakes in the generative AI space. If Thinking Machines Lab achieves similar success, the initial $10 billion valuation could skyrocket to $100 billion or even $1 trillion.

This phenomenon aligns with a concept known as the “Power Law.” Many venture capital funds rely on these outlier investments, which yield returns so significant that they effectively compensate for all other less successful ventures within the fund. As noted by Sebastian Mallaby in his book on venture capital, “Each year brings a handful of outliers that hit the proverbial grand slam. The only thing that matters in venture is to own a piece of them.”

Alternative Outcomes: The “Big Tech Put”

Despite the lofty expectations, it’s important to acknowledge that most startups do not succeed as predicted. In scenarios where Thinking Machines Lab doesn’t reach unprecedented heights, investors may still have a fallback option to recoup their investments. This is where the concept of the “Big Tech put” comes into play.

Even if a startup struggles commercially, it may still possess valuable intellectual properties, innovative technologies, or a talented workforce. For example, with Murati’s background at OpenAI, she has attracted several industry experts to her team, enhancing the startup’s appeal.

In the competitive tech landscape, established companies often seek to acquire promising startups struggling to gain traction. Such transactions frequently revolve around acquiring talent or technology and are known as “acqui-hires.”

Recently, high-profile deals such as Google’s $2.5 billion agreement with Character.AI to acquire its technology and founding team illustrate this trend. Similarly, Microsoft and Amazon have pursued comparable strategies with startups like Inflection and Adept, respectively. Although these deals may not generate the staggering returns typical of a runaway success, they often allow venture capitalists to exit investments with minimal losses, effectively cushioning their financial impact.

The Character.AI acquisition, for instance, reportedly provided investors with a return of about 2.5 times their initial investment. Hence, while uncertain outcomes are part and parcel of startup investments, avenues for recovery exist through strategic acquisitions by larger tech firms.

Conclusion: The New Venture Capital Landscape

In summary, the substantial backing for Thinking Machines Lab can be attributed to a dual-pronged strategy rooted in venture capital dynamics. Investors are drawn to the colossal upside potential of early-stage startups, while simultaneously recognizing the safety nets afforded by potential acquisitions from big tech players. As the landscape of venture capital continues to evolve, understanding these mechanisms will be crucial for investors looking to make informed decisions in the burgeoning world of generative AI.