The Future of Everything: Trevor Blackwell

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Trevor Blackwell is a Co-Founder of YC. He is also a roboticist who in 2007 built the first dynamically balancing biped robot. He has published papers on congestion control in high speed wide area networks, signaling protocol architecture, and file system performance. He has a BEng from Carleton, and a PhD in Computer Science from Harvard.

Since 2005, Y-Combinator has funded over 1,588 startups, creating a community of more than 3,500 founders. Their companies have a combined valuation of over $80B.

Here are some of their most notable investments:

1.How did you get started in the wonderful world of VC, What was it like founding YC?

Paul Graham and I had some bad experiences finding and working with investors for our first startup. So when he pitched me the idea of being a better kind of investor, I knew firsthand how much we could improve founder’s lives.

When we started YC, most other investors thought it was too risky to fund young technical people with no business experience. But it turns out that, while you eventually need some business experience to grow a huge company, that’s not the most critical ingredient at the beginning.

And by the time your businesses gets big, you’ll have gained a lot of experience.

We ran YC like a startup, without the teak-paneled offices and bevy of assistants that most institutional investors had.

Paul cooked the dinners himself, Robert set up the web servers, I fixed the Wi-Fi, Jessica filed the startups’ incorporation paperwork, Kate made the furniture out of plywood. So there wasn’t a big culture clash between us and the startups we were funding.

2. What is your methodology for defining and selecting the companies and entrepreneurs who are going to create the future?

In every tech field, people have a lot of choices in what company to work for. They want to work for someone that understands what they do and can build a business around it that’s good for the world. So when I talk to founders, I try to imagine the best people in the field wanting to work for them. That’s a high bar. It requires an inspiring vision, a deep understanding of what’s required to achieve it, and empathy for the day-to-day challenge of making it happen.

3. From an investors standpoint, being the one who gets to invest in the “future of everything”, what can we expect to see in a 5–10–15 year timeline? What are you most excited about?

Self-driving cars are going to work soon, and they’ll cut traffic fatalities by a factor of 10 or more. They’ll also make it faster to get around cities, and allow millions of people who can’t drive to be more a part of society.

People often don’t behave in their own best interest. Substance abuse and social media addiction suck vast amounts of human potential out of the world. Smartphone apps that help people behave the way they truly want, whether that’s avoiding addictions or practicing meditation, are going to improve a lot of lives.

It’s good that there will be people living on Mars, even if there’s no practical benefit for people on earth. I think it’s psychologically important to know that there’s an actual frontier somewhere, even if you’re not on it.

Being able to computationally model how molecules interact with cells means we’ll be able to develop new medical treatments orders of magnitude faster. In fact, we’ll be able to develop treatments specific to individual people. There are some big hurdles to deploying the technology safely, but eventually it’ll work and a huge amount of human suffering will end.

4. How has your background in CS and robotics informed your approach to investing? What about robotics and CS applies to entrepreneurship more broadly?

Robotics is a field where all kinds of great things ought to be possible, except that it’s so hard to write the software. There’s no physics problem in developing a household butler/chef/cleaner robot or self-driving cars. The mechanical engineering problems are hard but solvable. The unsolved problems are all software, and the solutions can probably be explained in a few pages. When those solutions appear, things will change quickly.

I’m not discouraged by slow progress. Some of the best opportunities are in fields where progress seemed to have stalled, but then suddenly started again. In the last few years we’ve seen that with deep learning, photovoltaics, supersonic aircraft, and self-driving.

5. What moonshot are you most excited to see solved?

We need this soon, because continuing to burn fossil fuels is likely to break the planet. Wind and solar power is improving rapidly in cost-effectiveness, but it still needs a lot more investment in order to completely take over from coal. Technologies like clean nuclear and carbon capture will need to be part of the solution too.

When we have carbon-free energy, we’ll no longer have to feel guilty about using it! Energy will still cost money, but you won’t feel like you brought our planet a little closer to disaster every time you leave the lights on. People will find all kinds of creative things to do when they have more energy to play with.

6. What problem or challenge is under-funded and why? What sector needs more attention?

New massively parallel computing architectures are going to be a key enabling technology for just about everything over the next 10 years.

Supercomputing companies were a bad investment until recently. Starting in the mid-90s, consumer PC hardware became nearly as fast as anything you can buy and much cheaper, so most of the supercomputer makers failed. Lately, commodity hardware improvement has slowed while new applications keep demanding more. So there’s a big opportunity to build specialized parallel hardware for applications like training deep learning models and simulating biology.

Another reason that it’s easier to start a supercomputer company today is that they can be delivered as a cloud service instead of shipping truckloads of hardware to the end users.

7. What is the role of venture capital in creating the future? What responsibility does VC have to help improve the lives of others, and ultimately the world?

Building the future always takes money. Some things require only a tiny bit to get started, and then they can grow from revenues. Some things require a lot. VC is essential for the second.

I feel the obvious responsibility: to fund things that are good for the world and not fund things that are bad for the world. Simple enough, but most technologies have both positive and negative consequences and it’s hard to predict early-on which will dominate. For example, we now know that social networks have some fairly harmful effects on society, but it wasn’t obvious 10 years ago whether this would outweigh the benefits of connecting people. The harm/benefit ratio will continue to change in the future as social networks, users, advertisers and trolls all adapt to each other, so it’s still too early to say.

We also have a responsibility to fund upstanding founders. Since any technology is a double-edged sword, it makes a difference when the swords are wielded by sincere, thoughtful people.

8. What decision or investment most impacted your life and why? (financial or otherwise)

I moved from Canada to the US for grad school and ended up settling in Silicon Valley. Although this area has its flaws and housing is expensive, there’s no substitute for living where the future is being made. (A few other cities would also qualify.) Most people who changed the world didn’t do it from the city they were born in, so I encourage ambitious people to go live wherever is the epicenter of their field.

9. What was your biggest miss and why did you say no?

I’m surprised how few big misses we’ve had, if you just count the ones that we said no to (we do keep track of these so we can learn from our mistakes.) But there’s room in the world for 1000 or more successful startups every year, if only people would start them. So the biggest challenge is reaching out to smart, energetic people and getting them to start their own thing instead of taking a job as a cog in an existing machine.

10. What’s next? What does the future hold for you?

I’m working on the problem of making robots do useful things in unstructured environments. When you see videos of robots walking around and picking things up and opening doors, those are the result of teams of control theory PhDs spending years tuning software to make each individual task work in each individual environment. I’m working on applying machine learning techniques to get robots doing a wide range of things things in a wide range of environments much faster.