In December 2008 Nilesh Jasani had put out an insightful report on why India was poised for a multi-decade compelling rural India theme. At the peak of the global financial crisis when investor confidence was at its Nadir, the-then Credit Suisse India strategist, who had shifted to India from Taipei in 2006, struck a very confident note. "The theme is not popular now because investors do not have too many stocks to play in the market. But over the years as more and more companies expose them- selves to rural markets, perceptions will change." How well the prediction turned out is evident in the way the theme eventually played out in the coming decade and continues to be the bulwark of India's consumption story.
Two years later, Jasani moved over to Jefferies as the head of research and eventually climbed the ladder before stepping down as the vice-chairman last August. In doing so, Nilesh capped a career that spanned Jefferies, Credit Suisse, HSBC, CLSA across Hong Kong, Taiwan, Korea, Singapore, and India. It was a rather unconventional move as Jasani went on to set up an artificial intelligence (AI) fund GenInnov, focused on investment opportunities in innovative companies leveraging generative AI across sectors, including healthcare and robotics.
Reflecting on his transformation from a sell-side strategist to a fund manager, Jasani says, "I've always searched for variety in life and starting afresh." When he took the helm at Credit Suisse in India, he was tasked with building a team without the benefit of a large budget. "I had to be resourceful, hiring people who were completely new to the industry," he explains. This strategy not only proved effective but also transformative for the careers of his team members, many of whom have now ascended to leadership roles across prestigious financial institutions like Bank of America, JP Morgan, and UBS.
However, after reaching a significant milestone as the vice-chairman of Jefferies and heading Asian equities, Jasani found himself at another pivotal moment. His innate curiosity and early interests—sparked during his engineering days at IIT Bombay where he delved into semiconductor manufacturing and neural networks—were rekindled. "Those early experiences were not just hobbies; they were a prelude to my deeper engagement with technology," says Jasani.
The year 2022, for Jasani, stood out as a monumental year, not just for him but for society at large. "It's a pivotal moment akin to post-World War II," he suggests, adding "This is when we began to truly understand the implications of manufacturing intelligence, an event I believe will be more significant in history than even the advent of the internet."
Jasani's vision led him to set up an AI fund, focusing on sectors ripe for transformation through generative AI technologies such as healthcare and robotics. In December, Lighthouse Canton, another Singapore-based investment institution, roped in Jasani on its advisory board.
"It's an incredible time to be alive," Jasani remarks. "To witness and participate in the era where we're not just users of technology but creators of intelligence. The opportunities and challenges this presents are monumental, shaping everything we know about industries and the very essence of human capacity."
Jasani's career has indeed been a mosaic of technological and cultural experiences, beginning with IBM in Bangalore, traversing through innovative tech landscapes in Korea and Taiwan, and navigating diverse teams in Japan and China. "My entire class is in Palo Alto—I've been fortunate enough to see technology in its many different forms," he muses.
Exciting, but disruptive
Though the tech pack is at the forefront of investing in AI, there is no certainty about their permanence as represented in the way constituents of Dow Jones has changed over the years. Jasani is skeptical about the permanence of their dominance. "We're witnessing a period of hyper change," he says, "where the norms of competition and innovation are being rewritten." The rapid evolution of technology sectors often leads to unexpected challenges and shifts in market dynamics.
Jasani delves into the nuances of technological evolution, emphasising that initial stages often focus on rudimentary aspects before moving towards transformative applications. When discussing the early internet era, he points out that the predominant emphasis was on hardware specifications such as modem speeds and connectivity solutions—elements that were critical during the internet's nascent stages.
For instance, In the 1990s, the tech discourse was dominated by the requirements of telecom infrastructure, which significantly influenced how the internet was initially perceived and used. Technologies such as AOL, Cisco routers, and modems were seen as the backbone of internet connectivity, dictating the pace at which digital communication and information sharing could evolve. The excitement around these technologies wasn't just about the potential of the internet but was tightly coupled with how fast data could travel through physical networks.
However, Jasani argues that this focus on the physical infrastructure of the internet—while crucial—was just the beginning. The real transformation, he suggests, came from how these technologies were applied beyond their basic functions. For instance, the adoption of the internet led to the creation and rise of companies such as Amazon and Uber, which completely redefined retail and transportation sectors, respectively. This shift was not merely about improving internet speeds but about leveraging the internet to create new business models and customer interactions. "In a tech revolution, the real thing is never about creation. It's about its application. If you don't find the applications and, at the moment, we are all like in a bit like the internet era which was hijacked by the semiconductor folks," feels Jasani.
The critique that the internet era was "hijacked by semiconductor guys" refers to the initial focus on the technological underpinnings—such as faster processors and more efficient routers—which, while crucial, did not represent the full scope of the internet's potential. Instead, the real value emerged as diverse industries found innovative applications for the technology, thus driving more profound changes across sectors and economies.
Jasani touches on the shift from simple utilities such as email—which was one of the earliest and most straightforward applications of the internet—to more complex platforms such as Google and Facebook, which not only transformed the web landscape but also created new social dynamics and economic models. This evolution from basic communication to complex social interactions and commerce platforms illustrates how initial technological investments can set the stage for broader societal changes.
That being the case, the current enthusiasm for Nvidia and other AI-focused companies is akin to the early days of the internet. “The simple reality is that we are just in on page one of a mega revolution and the best way to imagine this revolution is you have to ask this question: what happens in a world where suddenly you have hundreds of millions of super Einsteins?” says Jasani. In such a world, the applications of AI could range from mundane tasks such as managing emails or building websites, to profoundly changing the landscape of scientific inquiry and innovation. This shift isn't just about automating tasks but about enhancing the capacity to solve complex problems far beyond the current human capability.
Jasani points out that, historically, the capacity to address complex scientific problems has been limited by human cognitive abilities—what he refers to as "30-watt biological neural networks," or the human brain. However, with AI, problems can be tackled at a significantly higher level of complexity, which could lead to breakthroughs in fields such as physics, medicine, and engineering. "In life, the quality of solutions or answers is often determined by the level of complexity used to address a problem. This is particularly true for scientific challenges," explains Jasani.
Consider the motion of a projectile: the understanding and explanation can vary significantly depending on the complexity of the approach. For instance, a dolphin catching a ball represents a basic level of complexity, while Newton explaining the laws of gravity as an apple falls, or Einstein discussing the relative motion between two light beams, involves much more sophisticated levels of thinking. "Depending on which level of complexity you choose, the solutions you derive can vastly differ. For example, only with the insights similar to those provided by Einstein can one develop technologies like GPS. Up until now, every problem humanity has faced has been tackled with the limited capacity of our '30 watt biological neural networks,' or human brains," says Jasani
More importantly, he believes this era of "machine creation" might lead to the emergence of a fourth macroeconomic sector, following agriculture, manufacturing, and services. He predicts that the economic impact of machine creations could surpass the combined GDPs of major economies such as India and China within a few decades, illustrating the potential scale and influence of this new sector. "Our creations are not only addressing every problem at a higher level of complexity, but their ability is rising exponentially, and they are working on themselves. We are creating various circularities." This advancement is not limited to simple applications; it extends into complex fields such as robotics, drug discovery, and quantum physics.
Jasani emphasizes that the current developments transcend traditional computing technologies such as GPUs and AI chatbots. He asserts, "We are not talking about GPUs and co-pilots in chat boxes; what we are talking about is the arrival of the innovation era." This distinction is critical in understanding the focus of his fund, Generative Innovation, or GenInnov. It is specifically an innovation fund, not just an AI or technology fund. "One of the things that we always talk about is the need to really differentiate that tech is not AI and AI is not innovation," explains Jasani.
Currently, AI frontier is experiencing an unprecedented pace of change, so rapid that it's challenging to predict what will come in the next few weeks or months. Just last year, large language models (LLMs) could only handle prompts of about 700 words, but now, they can process code consisting of a million lines. Tasks that once required months for teams of engineers can now be done almost instantaneously by these models. The advancements in model sizes, parameters, and context windows are pushing what machines can do to levels previously unimaginable.
"The pace of change is so frantic that none of us know exactly what's coming a few weeks and few months down the line," says Jasani. This transformation began in earnest around 2022 when machines started to decipher human languages—a monumental shift from the centuries-old practice of training our brightest minds in engineering to interact with machines. Now, machines are beginning to communicate in human language, signalling a profound change in the software industry, from BPOs to major software companies, making software increasingly commoditised.
Illustrating the point further, Jasani says: "The history of civilisation is mind over matter, ideation over materialism and suddenly now for the first time, ideation is getting commoditised." This shift is upending traditional business models, moving from first-mover advantage to last-minute advantage.
In robotics, the advancements are equally transformative. Machines are now able to learn from observation, much like human children, which has suddenly made the concept of humanoid robots a feasible reality. This could potentially revolutionise industries, scaling them to multiple times the size of the smartphone industry in just a decade.
What’s revolutionary is that machines are beginning to unravel complex systems such as genomic codes and quantum entanglement, areas where traditional tools have fallen short. “Machines have begun to really understand, potentially, some of the connections within," says Jasani, emphasising on the promising nature of these advancements.
The implications of these technologies extend beyond individual sectors such as robotics or biotech, influencing everything from drug discovery to quantum computing and the development of new materials, such as synthetic peptides and solid-state batteries. “This era is characterised by a rapid identification of new materials, vastly outpacing anything achieved by humanity before,” says Jasani.
Articulating his unique investment strategy, Jasani says: "Our motto is to investigate as private investors, invest as public investors." He explains that investigating as private investors involves a deep focus on business fundamentals, product innovations, and transformative business models—areas ripe for exponential growth.
The future is not very far where AI becomes integrated into every aspect of human lives, changing every gadget and piece of hardware around us. "Embodiment of AI is going to really lead to its own kind of forces and winners and losers," Jasani states, underscoring the transformative impact AI will have on how businesses operate and thrive in this new era.
Though AI is at the cusp of a revolution, Jasani is all for evidence-based investing by drawing a parallel to cricket strategies, comparing long-term investing to playing a steady game as former Indian cricketer Rahul Dravid. “The fund will focus on consistent, reliable gains (compounders), rather than seeking quick wins in every move,” says Jasani. This methodical approach seeks to invest in companies and sectors showing real, measurable progress and potential for sustained growth, similar to Warren Buffett’s delayed but highly successful investment in Apple.
Jasani also stresses the importance of diversification across different sectors and regions, maintaining a balance between various investment themes, from biotech and environmental tech to robotics and traditional tech. This strategy ensures a broad exposure to innovation while mitigating risks associated with high internal correlation in investments.
Currently, Jasani is running the fund with a four-member team.” We are looking to hire some notable individuals in various capacities in the coming days,” says Jasani, who has already got commitments from UHNIs and family offices in India.
While it’s still early days, what is clear to him is that AI is in a growth investment space, where premiums are a given. "Clearly, the approach to valuing growth-focused companies differs significantly from valuing traditional value investing, which often depend on slower-moving factors such as demographic shifts, changes in market share, or modest industry growth rates of 6% to 8%. This isn't about value investing; it's about growth and innovation investment. Companies that are innovating and growing their revenues by 20%, 30%, or even 40% will naturally command higher premiums," says Jasani.
Guess, some things never change in the world of investing!
