I have just been reminded of the days when I was a fledgling entrepreneur going door to door on Sand Hill Road seeking funding. I remember how VCs would make me wait for hours and try to look smart in front of their partners by finding petty faults in my business plan. They were the kings and kingmakers and treated entrepreneurs as beggars. Fortunately, the cost of starting software companies soon fell to the point that crowdfunding and angel capital provided a better alternative. This shift in the power balance forced VCs to suck up to entrepreneurs instead.
However, this shift was only in the software space. In capital-intensive fields such as biotechnology, little has changed. Moreover, because of the spectacular failure of Theranos, VCs are more risk-averse than ever–literally traumatized.
With exponential advances in technologies such as artificial intelligence, computing, sensors, and synthetic biology, not only have costs dropped, but cutting-edge innovation has now been globalized.
Today, there are many better places to build world-changing technologies than Silicon Valley. One of these places is India, where you can hire top-notch talent for less than 10% of what it costs in the Valley, and pathology data needed to train machine-learning algorithms is available in abundance.
While San Francisco is the global center of AI development due to positive network effects, technology leaders such as Sam Altman say that India cannot build complex AI technologies. However, what I have seen in India leads me to believe that Silicon Valley’s advantage will not last long–and that its insularity, arrogance, and overconfidence may be its downfall. As AOL founder Steve Case has long been arguing, the rest of the world is rising.
What I am trying to build with my startup, Vionix Biosciences, is far more ambitious than what Theranos pretended to achieve. I believe that in India, I can build early versions of the technology for just $1 million, which is less than 0.1% of the $1.4 billion that Elizabeth Holmes raised (and squandered).
I am approaching medical diagnostics in a completely new way, taking advantage of basic science breakthroughs made by a Chilean company that I had invested in over a decade ago, not just throwing money at the problem as the Valley often does. And rather than being secretive about my devices and do everything myself, I am planning on making the devices available to researchers at several universities so they can validate the technology and do things with it that even I can’t imagine.
The technology modifies the molecular structure of water by converting it into non-thermal plasma and back into water using the same amount of energy as a hairdryer. It enables the real-time spectral analysis of organic matter. Just as DNA sequencing opened up a new dimension in medical research by converting biology into letters, this technology can convert biological matter into a light spectrum that AI can decipher. It’s similar to techniques used in the gold standard for material analysis, mass spectrometry, but without any consumables, sample preparation, and mass-to-charge ratio measurement. The technology can analyze not only water, but also human fluids such as blood, urine, saliva, and breath. It can do this in less than five minutes for just the cost of electricity.
The catch is that this requires complex AI training to understand light patterns that are as complex as genomic data, which have taken decades to decipher. Training this AI will require tens of thousands of medical samples for each disease or cancer marker, something that would be practically impossible for a Silicon Valley startup to obtain in the U.S. However, India has an advantage with its population of 1.4 billion people. With informed patient consent and privacy protection, it is not difficult to inexpensively obtain access to hundreds of thousands of bio-samples at the many pathology labs that are already analyzing these samples with advanced medical diagnostics equipment.
Recruiting quality AI talent is another challenge. In Silicon Valley, entry-level salaries are often more than $150,000 per year and employees expect fancy perks and 35-hour work weeks, as well as the right to moonlight and hold two or more jobs.
In India, hundreds of thousands of computer science graduates earn $4,000 to $7,000 per year. I interviewed several soon-to-be graduates and found them to be far more motivated and willing to learn than their peers in the Valley. I hired one student on the spot when he told me that he wanted to work for me as an intern without salary, learn whatever machine learning tools I plan to use, and then work 70 hours a week when he graduates in June. Of course, I am going to pay him far more than this and let him have a life, but you don’t see this attitude in Stanford or UC Berkeley graduates.
The Indian government is also supportive of the AI ecosystem. Rather than creating hurdles with regulation, restricting immigration, and suffocating the tech industry, India is establishing a new fund to support its AI ecosystem. Prime Minister Narendra Modi’s principal scientific advisor, Ajay Sood, told me that his mission is to do whatever it takes to facilitate entrepreneurship and support startups and that the government would do whatever it could to welcome foreign companies like mine.
With all these factors in mind, it became clear to me that India is the ideal location for my startup’s research and development. I have decided to forgo several scheduled meetings with Silicon Valley investors in favor of the vibrant and supportive ecosystem that is India.
Vivek Wadhwa is an academic, entrepreneur, and author. His book, From Incremental to Exponential, explains how large companies can see the future and rethink innovation.
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