On Growing Up

I fell in love with music early in life. Born and raised in London, I started playing piano when I was five years old, and added the cello four years after. By high school, I switched to jazz piano and split my Spotify playlist between Chopin, Oscar Peterson and Freddie Mercury. I still have posters of the latter two on my bedroom wall.

On Shifting from Math to Engineering

I always knew I’d go to school for math, but I didn’t know how to turn it into a career. I attended a talk on Shane Legg and Marcus Hutter’s AIXI my sophomore year and immediately fell in love with artificial intelligence. That Christmas, I read Goodfellow’s Deep Learning and knew I’d found my vocation.

It’s different for college students in the UK, in that it’s a lot harder to just sign up for courses whenever you want to learn something new. You’re pretty much stuck studying the subject you picked as a 16-year-old! So I ended up teaching computer science and AI through NVIDIA for a couple of years, where I helped people in London make the career shift into tech.

On Moving to California and Finding Venture

When I was at Imperial College, I was always aware there was a bigger world out there. The few AI initiatives that existed in London, like DeepMind, kept getting acquired by companies in Silicon Valley. So I said to myself, “I can either stay here and watch this technology Renaissance happen from afar, or I can go there myself and actually be a part of it.” I decided to apply to Stanford for my masters in computer science.

I didn’t expect to end up in venture. But I’ve always believed the contours of the future are already laid out, we’re just waiting for the right people to fill it in. And I obsessively talk to people, read and write to figure out those contours. In hindsight, venture was the only career for me.

On Working with Founders

I love people who are passionate about their work and the odd one out. It doesn’t matter if it’s theoretical machine learning or baking gingerbread monstrosities. Their enthusiasm is infectious and the more they press on fissures in their corner of the world that others overlook, they might just make something new. Whether that happens tomorrow or ten years from now is a separate question, but I’d always bet on that person.

On Working with Amplify

My focus is on AI and blockchain, which I understand has become a horrible cliche! I think blockchain technology has been misconstrued. People like to use lots of hyped-up adjectives to try to explain it, but really, all great tech is about making something better, cheaper and faster. Blockchains are a revolutionary platform for conducting political-economic experiments. It remains to be seen which experiments garner most traction, but in the meantime I am interested in making them cheaper and easier to run. I think the journey has only just begun in AI research, and whether it’s better learning algorithms, model architectures or reverse engineering neural nets to learn a periodic table of universal circuits, there will be lots of exciting breakthroughs over the next few years. 

On Life Outside of Work

It takes the lunatic fringe to find the lunatic fringe. You’ll find me researching democratic capitalism, the death of money, why verbalized latent space models are the transistor of AI and active inference.