AI Investment Lags Research by Years, warns Former OpenAI Researcher
The current excitement surrounding artificial intelligence investment is significantly behind the cutting edge of AI research, according to Jenny Xiao, cofounder of Leonis Capital and a former researcher at openai. xiao points to a growing disconnect between the perceptions of AI’s capabilities in the investment world and the actual advancements being made in research labs,with the gap estimated at three to five years.
The Disconnect Between Research and Investment
Xiao highlighted this discrepancy in a recent appearance on the Fortune Magazine podcast, stating, “There is a massive disconnect between what researchers are seeing and what investors are seeing.” This isn’t simply a matter of differing opinions; Xiao asserts that discussions at major AI conferences are already 3-5 years behind the thought leadership emerging from research circles. She believes bridging this gap is crucial for fostering genuine innovation and responsible investment in the AI space.
A New Generation of AI Investors Needed
This lag, according to Xiao, necessitates a shift in the venture capital landscape. Having transitioned from research at OpenAI to founding Leonis Capital in 2021, she aims to connect deep academic AI research with the world of venture funding. “With AI, there needs to be a new generation of founders. There needs to be a new generation of VCs,” she emphasized.
Unlike previous technological waves, such as the rise of SaaS (Software as a Service), AI progress is characterized by rapid, non-linear progress. SaaS companies, she explains, were built upon relatively “stable tech stacks,” while AI is in a constant state of flux. This demands a new type of investor – one who possesses a deep technical understanding comparable to the AI founders they are backing. Investors can no longer rely on simply assessing market potential; they must grasp the underlying technology to make informed decisions.
AI progress: not Linear, But in “Lumps”
Xiao cautions against evaluating AI progress through a linear lens. The common questions of whether AI is “speeding up” or “slowing down” don’t accurately capture the nature of the field’s development. Rather, progress happens in “lumps” – periods of rapid advancement followed by consolidation and refinement. Acknowledging this non-linear pattern is vital for realistic expectations and appropriate investment strategies.
The Implications for the AI Landscape
The implications of this investment lag are far-reaching. It suggests that current funding might potentially be misdirected towards areas that are already becoming obsolete, while truly promising, but less-hyped, research may be overlooked. This can stifle innovation and delay the realization of AI’s full potential.
The need for technically proficient investors also extends to evaluating the feasibility and scalability of AI projects. A deeper understanding of the technology allows for more accurate risk assessment and a more nuanced approach to due diligence. Investors must be able to identify truly groundbreaking work from mere hype, and this requires expertise.
Looking Ahead: A Call for Technical Acumen
Xiao’s insights serve as a wake-up call for the investment community. The AI landscape is evolving at an unprecedented pace, and a failure to keep pace with the latest research could lead to missed opportunities and poor investment choices. The future of AI investment relies on a new breed of venture capitalists who are not just financially savvy, but also deeply knowledgeable about the technical complexities of this transformative technology.
Leonis Capital did not respond to a request for comment from Business Insider regarding this matter.
