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If you want to invest in early-stage technologies, putting a timeframe on it does behold you to Silicon Valley economics. You've got a certain time period where you have to make the money. And you have to invest that money whether you find good companies or not.
With a regular venture fund, you raise, let's say, a billion dollars, and then over the next three or four years, you've got to invest that money; otherwise, the people who invested with you will say, 'What are you doing? You're just collecting fees on our money.'
We actually have the tools in the life sciences to achieve anything that you have the audacity to envision. I just hope to live long enough not to die.
We have this powerful lever at Google Ventures, which is to invest $200 million a year. This is a huge lever. It's not all going into one place; it's going into lots of start ups and founders and entrepreneurs, all of which are levers to try and change the world in one way or another.
We can get much better outcomes from people if we understand the genetic basis of the exact cancer that they have, what interventions might be most effective against it, what's worked in the past and what hasn't.
We are looking for highly technical, enthusiastic and capable entrepreneurs who have a healthy disregard for the impossible, and that's not always easy to find.
When you apply computer science and machine learning to areas that haven't had any innovation in 50 years, you can make rapid advances that seem really incredible.
People talk about the redistribution of wealth a lot, which is a very valid topic. But what about the redistribution of health? That's even more concentrated at the top.
If you're a technology investor, and you decide that you're also going to be a healthcare investor or a green-tech investor, that doesn't usually work out that well. There are reasons why people make their careers studying these things and becoming experts.
Say you have cancer - you have this broad thing we call cancer; we're going to irradiate you and pump this poisonous material into you and hope more of the bad stuff dies than the good. That is going to seem so medieval when we can fix it on a genetic level, and Foundation Medicine is the first step to diagnosing it on a genetic level.
If I were to leave and raise a venture fund, I would have to find 10 or 100 LPs. They would all give me a bunch of money, and I would take a percentage of that to pay myself. They would expect me to invest that over the next three years, and they want that money back in seven or eight years.
I'm interested in the ideas that sound a little crazy, such as radical life extension, curing cancer, being able to create a simulation of the human brain and map every neuron.
I would draw a really big distinction between competition, or potential competition, and a conflict of interest. A conflict of interest implies wrongdoing, whereas competition is really healthy.
I used to be a health-care investor a long time ago in the public markets. One thing I learned that we tried to apply here is that investing in small molecules, trying to invest in the next treatment, there's an element of gambling to that.
I can make it very clear: I get paid if we make good investments. And if we don't, I don't get paid. I have no incentive to sell our companies to Google; the entrepreneurs get to decide that. We are minority shareholders.
Humans are terrible at predicting the future. We really overestimate what we can do in the short term and underestimate what we can do in the long term... If we can glimpse even a couple of years into the future, even that's difficult to do.
Government is really successful when it's willing to make big, bold objectives, like, 'We're going to get to the moon.' But without leaders with big ideas, we get stuck.
Back in the late 1990s, venture capitalists got very excited about the Internet. A whole lot of money was poured into some companies that failed rather spectacularly, and a lot of people lost a lot of money.
As computer intelligence gets better, what will be possible when we interface our brains with computers? It might sound scary, but early evidence suggests otherwise: interfacing brains with machines can be helpful in treating traumatic brain injury, repairing spinal cord damage, and countless other applications.
