On the evening of September 13, 2026, the Schwartz Reisman campus in Toronto will gather not just tech enthusiasts, but people whose decisions determine where millions of venture dollars will flow. Mohammad Norouzi from Ideogram, a University of Toronto graduate, will share how an academic lab turns into a company whose valuation is already measured in the hundreds of millions. Alongside him is investor Eva Lau from Two Small Fish Ventures, whose new 30 million dollar fund is aimed specifically at generative AI and semiconductors.
Behind the shiny exterior lies a simple economic mechanism: universities like U of T have long been factories not just for knowledge, but for capital. Geoffrey Hinton, whose work earned him a Nobel Prize, attracted talent to the campus, who are now founding startups. Norouzi, who worked at Google on Imagen, is now building Ideogram — an image generation tool capable of competing with the giants. For investors, this is a signal: early access to such teams offers a chance for a multiple return, but the risks here are also higher than in traditional industries.
The four startups that will present their projects illustrate different facets of this economy. CentML promises to reduce the costs of running large models by 65 percent — direct savings for companies spending millions on cloud computing. Private AI helps comply with privacy regulations, turning regulatory barriers into a competitive advantage. BioBox and Xatoms work at the intersection of AI and biotechnology or quantum chemistry, where one successful contract with a pharmaceutical giant can change the fate of a fund.
For the average investor or professional thinking about their career, such events are not just networking. They show how the structure of wealth is changing: yesterday's graduate students are becoming co-founders of companies with billion-dollar valuations, and venture funds like TSFV are actively looking for exactly such stories. At the same time, success depends not only on the technology but also on the ability to attract capital, build connections with alumni, and find niches where AI solves real, expensive problems.
The paradox is that the most promising opportunities are often hidden not in loud names, but in the details: exactly how a startup reduces client costs or bypasses regulatory risks. Eva Lau, who went from Wattpad to her own fund, emphasizes exactly this — practical advice for those who want not just to watch the AI boom, but to participate in the distribution of the capital it creates.
Ultimately, the meeting in Toronto is not just about the future of technology, but also about how wealth is being redistributed today. Those who understand the logic of such ecosystems get a chance to enter the game before the market sets the final price.
