As we shift gears to launch the GenInnov Innovation fund in the coming days, we are often asked about the track record. GenAI is a new beast. Like in the case of the blind men and the elephant parable, an insistence on basing conclusions on past patterns, habits, and experience leads to wrong analysis and an aversion to not knowing the new field for what it could be. When markets like cryptos or sectors like carbon trading emerged from nowhere, it was important to learn them primarily without preconceptions rather than through experience elsewhere.

Stock market veterans from various fields and sectors are competing to have their spaces anointed as GenAI winners. Their efforts are increasingly no more charming than those of company spokespeople trying to squeeze a re-rating by claiming, “We use AI.” What is worse, however, is not the frenzy but an aversion to even attempting to understand GenAI’s countless facets and implications.

The most straightforward examples are from the semiconductor sector experts. They view GenAI as the thing to buy everything in various subsectors, including packagers, design tool makers, etchers, ASIC players, and everything else where there is no innovation. They have little time to understand the rapid progress in compute and inference optimizations, particularly those that may threaten the GPU/HBM prominence theories.

The self-serving stubbornness takes different forms with cloud enthusiasts (no appetite to consider the rising unsustainability of the cloud ways in many GenAI applications), chatbox cheerleaders (a complete disregard for the segments’ commoditization), and now nuclear power analysts (lack of scalability even assuming the demand surge estimates are correct).

In its explosive growth (the Super Moore era, as we call it at https://bit.ly/493F6Xg, where some things double every 2-3 months) and instant copiability, the GenAI era is without precedence. Viewing it without preconceptions or narrow interests is perhaps the best way to appreciate its myriad applications (https://lnkd.in/g9w7f-kx checking the list that keeps growing almost daily) while preparing for evidence-based, sensible, all-sector, global investing.

Please feel free to connect, if you want any information on GenInnov funds. We thank the talented Ms. Pallavi Santhosh (https://bit.ly/3IGmL7S), a student at NIFT Chennai, for the excellent sketch.