Meet the Woman Who’s Created the 21st Century Finance Model for Emerging Technologies
This piece is an excerpt from the forthcoming book The Internet of Women: Accelerating Culture Change to be published on June 30th:
Riva-Melissa Tez is the CEO and co-founder of Permutation in San Francisco. A London native, she runs an artificial intelligence platform and incubator. In her spare time, she works on The Longevity Cookbook, alongside Maria Konovalenko and Steve Aoki, which is a book that distills academic research into practical measures for slowing the aging process. This is an edited transcript of a recorded interview.
I learned important lessons about money at a very early age.
At 10, I moved into a homeless shelter after my father left my mother. My mother is severely schizophrenic — which can be both chaotically fun and devastatingly traumatic — and was not well enough to look after herself, let alone me at the time. Amongst other things, she used to make me drink the milk in the morning first to check if it had poison in it. A few years later, at 14, we moved into social housing. We lived in this horrible apartment that had no curtains or carpets. At one point I realized, “Oh, money is how the world works.” It’s a lesson you don’t learn at school.
I received a scholarship to attend a prestigious all-girls school. The girls at my school came from quite wealthy families, so I never told anyone where I lived. I would take different routes walking home so that no one knew where I was going.
Once I realized that money was the key to an escape, I started reading books on consumer psychology. Edward Bernays, who was the nephew of Sigmund Freud, was a great inspiration for me. At 15, I managed to get a job selling outdoor sinks at a furniture trade show. The job initially belonged to my older sister, but on her first day of work she humorously fell asleep on the job and was promptly fired. The company told her to find a replacement, so I begged her to let me do it.
My sister lied and said I was 16. I ended up selling these sinks at a trade show from 9am to 9pm for three weeks straight. I developed my own strategy to improve my learning: I would read books on sales and then go test theories out when I was working. Later, I would update my model of consumer psychology, which I kept track of in a notebook. In this way, I used very rapid AB testing to learn about sales.
I sold more at that trade show than the entire management team, earning £15,000 in commission, which was more money than I could even fathom at the time considering my mother and I lived on £60 a week. I had truanted school to accommodate the job and was in a lot of trouble, but my grades were good and, to be honest, I didn’t really care much about school at the time. I saved the money and was able to eventually move my mother out of our awful apartment into a beautiful one-bedroom place in West London, where she still lives today. I have paid her rent every month since then. I owe her for a lot of my thinking, so I could never abandon her. Those struggles she put me through gave me a high tolerance for risk and stress, which I am extremely grateful for.
People sometimes ask what made me ambitious at a young age. The motivation was simple: we were literally so poor that I had to find a way to make money for my mother. There’s no secret sauce; it was just pure desperation. There were times when we couldn’t even afford to eat.
I attended University College London and switched from a joint honors to straight Philosophy, with a focus on epistemology and logic. My mother’s condition got me hooked on trying to understand how humans justify their beliefs.
Whilst at University, I was living above an empty shop in Notting Hill, which is an affluent area in London. During my time there, I noticed there were many families living in the neighborhood. One day, I suggested to my boyfriend at the time that we should open a pop-up toy store in the empty store below. We followed through, and surprisingly we did very well — so much so that we launched a permanent store. Eventually our shop expanded, taking over the two stories. Our toy store still stands today. It just celebrated its sixth birthday.
At 21, I got more serious — I thought, “wait, but I don’t want to run a toy store for the rest of my life…” I wanted to learn how to do things digitally. I used to get into trouble for hacking stuff off computers- I was very much the kind of teenager who would stay up all night on a computer. This was all inspired by my father- he is a Professor of Electrical Engineering. Before he left my mother and I, he used to make me build computers and watch him code when I was very young.
After I left the toyshop, I moved to Berlin with a mission to further my software skills. After a few months into this endeavor, I had the idea of building a creative social network for kids. I worked on it with an American co-founder and ended up staying in Germany for over two years. At one point, I read Kevin Kelly’s What Technology Wants and got really interested in emerging technologies. I wanted to find people to discuss ideas with, so I started a nonprofit called Berlin Singularity which hosted talks and events. I also started teaching as a lecturer at two business schools, mainly on consumer psychology but also on entrepreneurship. Some friends and I entered and won the LinkedIn Hackathon, which is still one of my favorite memories from Berlin.
Michael Vassar, who at the time was running the Singularity Institute for Artificial Intelligence in San Francisco came to give a talk for Berlin Singularity. After his talk, I complained to him that I had this sense of imposter syndrome. What I meant by this was- the idea that people were regarding me as some sort of European expert on emerging technology horrified me. I remember seeing myself in this magazine listed as one of the top influential people in technology in Germany and I kept thinking, ‘But I’m only 21 and don’t know anything!’ I remember Michael telling me that I would enjoy the intellectual climate in San Francisco.
A few months later, I was in a near-death car accident on the autobahn. I got admitted into hospital with a bad concussion and kept thinking about how much I wanted to learn about the world. A few days later, I left my house, start-up, and boyfriend behind in Berlin and flew to San Francisco.
An interest furthered by the near-death experience, my original plan was to study how I could contribute towards life extension and regenerative medicine. To begin, I started profiling all of the biotech companies I found interesting. Trying to fulfill the challenge I set myself in the hospital to learn about the world, I also picked up a hobby of reading a lot of physics papers. To this day, I find them very humbling.
Eventually I began to work with investors who wanted to put their money in emerging biotech opportunities. As I started to undertake technical due diligence on different companies, I realized that solving scientific challenges depended on the strength of tools and resources that researchers have at their disposal. It was then that I really hit on machine learning and artificial intelligence. I kept thinking, well, if you could improve AI resources, you could use it to solve complex problems — such as those in biotech and energy provision, among other industries. AI has the potential to make the scientific process cheaper and better. It has the power to reduce complexity, which is an idea I think about all the time.
Once I hit on AI, I knew what I had to work on. I believe AI is fundamental to improving humanity’s odds of survival because humans are limited in their scope of skills for problem-solving. The only other option would be intelligence-amplification en masse.
Women in Science
The subjects that we work with tend to all fall under the STEM (Science, Technology, Engineering and Math) categories that already have poor gender rates. I think the disparity is improving today, because there are more opportunities to learn about engineering for children.
Today, there are so many children’s toys that promote engineering for girls. This is in sharp contrast to 10 or 20 years ago. Today, we’re at a point where we are just ahead of the curve in getting women into STEM subjects. I believe the ratios will balance — it’s just a matter of time.
Frequently, I’m the only woman speaker at an event or on a panel. I recently shot an ad campaign for Microsoft where I was the only female. People ask me what that’s like all the time, but most of the time I don’t even notice. Sometimes I get spoken down to, but I just play into it. At this one high-profile investment event, guys kept asking me where my husband was, I guess it was impossible for them to believe a 26 year old female could be an invited guest. I told them that he had stepped outside to make an important business call and made a note to never work with those people. I don’t feel a need to justify myself.
Creating a 21st Century Finance Model
When I first came to the Bay Area, I was working with two kinds of groups: investors who wanted to put their money in biotech, and startups that wanted help raising money for their projects. As a philosophy graduate, I didn’t know a lot about fundraising.
I spent a great deal of my time learning about how venture capital funds work. The traditional fundraising model didn’t make much sense to me. I saw it this way: as a VC, you’re basically a kind of middleman who invests in startups. You represent other people’s money, which means you have to answer to their particular interests. But, at the same time, you also need to negotiate the interest of startups and their entrepreneurs. I was pretty open about telling people in asset management that I didn’t entirely understand some of their models, and that some of them might be more imperfect than others. Then, someone rightly challenged me on how I would do it differently. I told him I would learn everything I could about venture capital and attempt to create a new model.
I left America and spent nearly three months in France reading about venture capital, including all of the venture capital reports from the Kauffman Foundation for the last few decades. At the beginning, I didn’t even know what a Limited Partner was. At the end, I could breakdown the IRRs of the top VC funds for the last ten years. I just studied everything I could and concluded that the model of traditional venture capital didn’t work for the kind of projects that interested me. It works well for consumer tech, but it doesn’t work as well if you want to do anything long term.
I wrote a few posts about how we should reshape finance. My posts got over 250,000 views. As a result, a couple of big investor groups were interested in hiring me. I found that ironic, but then again everyone loves a contrarian. Among those who reached out to me was Peter Bruce-Clark, who was working at Stanford looking at innovative investment models. I ended up spending much of my time talking to him. He walked me through some papers, including research on new models for investment funds that he himself had been building, which were very impact-focused. I decided I wanted to do the same thing for AI and began working with two others on fleshing out that model- which was a hybrid impact investment fund.
My original goal was to raise these funds to specifically invest in artificial intelligence. This was about 18 months ago. During this time, a very smart investor and mentor said to me, “The bottleneck in solving problems like the advancement of AI isn’t a lack of capital. The problem is a lack of valuable deal flow.” Essentially, he told me that I wasn’t tackling the real problem. It was a major shape-shift for me.
I decided to take another six months to model the AI ecosystem. I wanted to learn about where talent goes, the flows of capital between companies and investors, why certain companies are built, and why some ideas don’t get off the ground.
One of the problems is investors don’t understand much about research-driven machine intelligence since it’s extremely technical. I saw a market gap for better due diligence tools as well as a gap in the provision of services geared to assist early-stage development of AI companies. It’s a much better, more valuable use of my time to ensure we have lots of smart AI investors rather than trying to launch a standalone fund.
That’s how Permutation ended up being developed. I created a suite of tools– which we’re launching soon- which helps investors with some tricky decisions. I’m also trying to introduce investors to more hardware-based projects. People focus on top layer innovation- such as algorithms- without recognizing that the very thing that sets the parameters for improvement is the hardware. I’m lucky that I can call up my father when I need some help understanding a quantum computing paper.
The second thing we’re doing is investing in and incubating early stage AI companies. It’s a very compelling message when you go back to investors and can demonstrate how you’ve built tools to measure your returns and your ecosystem impact. Typically, you raise a fund and then you try to do that (or perhaps at least pretend you care about impact). We did all of the research first and remain extremely research-driven in our investment model and thesis. Nobody we’ve approached for funding thus far has said no.
Peter, who helped me learn about measuring impact returns, left Stanford and is now my business partner and closest friend.
There’s a lot of hype right now around AI, so while there are many interested investors, we’re seeking smart ones that pass different integrity tests. It’s the same for the people we hire. I’m looking for impact-driven individuals and groups who genuinely care about making the world better. Making money isn’t as hard as creating a positive global impact, although capital can certainly fuel the strength of impact. Unfortunately, I think most people realize this in life when it’s far too late and wish they had done more with their time-slice of existence. I’ll retire when I die- and I’m not really planning on doing that either.
Incentives and Collaboration
Last year, I went through a bout of depression because it bothered me to see how little people in power didn’t collaborate to solve some of our grandest challenges. There’s too much ego and opposing forces, not to mention incentive structures that work against us. I kept thinking: how can you make collaboration easier without losing the value you have as a company or the impact you have as an individual?
We haven’t quite worked out how the human mind works well enough to understand how to manage incentives. The problem is, we incentivize people not to collaborate with others. You collaborate within your own group or within your company, but if someone does something similar to you, you want to deliberately withhold information from them. It restricts everyone and restricts innovation. This kills research progress.
Things I would like to see:
The reshaping of incentive structures: We really need to improve incentive structures between groups. How can we give other people access to fundamental research? When you read academic papers, researchers are incentivized to keep private the exact details that would explain the breakthrough. I’m opposed to people being private about discovery, even though I understand it would be suicide to do the opposite. I love today’s emphasis on being open source, but we need more incentives for following through. Right now, you need to be altruistic or charitable to be open source. There is no cost benefit. We don’t live in a world where individuals get rewarded for contributing to society. Instead, the message is, contribute to your own thing and you’ll be rewarded for it. Then use that money to contribute to society. That process is too slow in my mind.
For many companies, their value lies in their intellectual property. If you give that away, you’ve given away the value of your company. Imagine if everyone shared datasets. And… what if you had people doing it to benefit humanity? That would take global coordination and a redistribution of power, and I think that’s probably the biggest challenge of the next 100 years. I also believe AI will help with solving this, but that’s a whole another topic.
Supporting other women: Maria Konovalenko is one of my closest friends and one the most famous faces of regenerative medicine. I met her whilst I was working in biotech a few years back and to be honest, originally I found her to be very intimidating. She used every opportunity to publicly advocate for life extension. When we first met, I was much more timid and didn’t know what to make of this. As I spent more time with her when she moved to the Bay Area, I came to find she’s vocal because she cares so much about wanting to solve aging.
She’s working on a PhD now and spends her days in a lab dissecting flies to test out ideas. She wakes up at 5 a.m., goes to the gym, and dissects flies all day. At night, she’s advocating for life extension. In her spare time, she’s working on a book with Steve Aoki, called The Longevity Cookbook, that I’m also helping with. It’s a user-friendly book that people can read to learn more about the topic. I’m writing a chapter on how artificial intelligence will revolutionize biotech research, such as the use of neural networks to simulate drug discovery. I live for that kind of development.
What I’ve learned from my friendship with Maria, is the best thing we can do is speak up. I used to publish articles under a pseudonym. Now, I write under my own name as a female in the space in the hope that people can relate to me in some way.
I also want people to realize that you can be interested in these naturally academic areas and still have a lot of fun. I refuse to play up to the false idea that you have to be boring to be professional. The environment in our office is extremely fun. By that, I don’t just mean we have a table-tennis table. If I think a brainstorming session would be better held at the Zoo, then I’ll hold it there. Life’s too precious to not enjoy every day that you get.
The next century will be critical for humanity’s progress. Doing my bit and speaking up about the challenges ahead is a responsibility that gets me out of bed every morning. At night, I think about all the future people of the world and the opportunities and risks ahead, how big the universe is and about different spectrums of time.
It makes trivial matters seem very small indeed.