Sonya Huang
Growth
Backstory
I’m a Silicon Valley kid at heart. I was born in Mountain View and grew up in the gravity well of innovation that was 1990s Silicon Valley. It was a fascinating time, from learning to code in third grade to witnessing blockbuster IPOs and the dotcom bubble burst.
I come from a semiconductor family. Growing up in the Valley made me believe deeply in the American Dream and technology’s role in creating a better future. My parents are immigrant engineers, and technology and entrepreneurship gave them the vehicle to create something lasting. I see venture capital as a conduit to amplify the best founders and the best ideas and give them every possible unfair advantage.
I worked at Goldman Sachs and in private equity before joining Sequoia. But I don’t really think of myself as a “finance person.” I’m much more comfortable reading a technical paper or talking to a researcher than going to an industry conference. I like technical people who are precise and can ship.
I love technology and hold an optimistic view. I spend a lot of my spare time vibecoding and still pinch myself every time the agent impresses me (all the time!). It’s easy to take this moment for granted; I don’t. I still can’t believe this whole AI miracle is happening right before our eyes.
I’ve always been very interested in AI, dating back to my college days where I trained computer vision neural nets on brain scans and astrophysics data. It’s awesome, exhilarating, and disorienting just how rapidly the field is accelerating. (PS, I’m very AGI-pilled). I also love talking to friends building the newer frontier that is now appearing on the horizon: brain-computer interfaces, alignment, physical AI, and more.
I’m lucky to count some of the top founders and researchers in AI as friends. I’m documenting many of these conversations through Sequoia’s AI podcast (Training Data) and our annual AI event (AI Ascent). I believe we are living through a historical moment in time that deserves to be explored and preserved with great curiosity and care.
On the Lookout for
I met the OpenAI team more than a year before ChatGPT launched, when they were still a pre-product research lab. It became clear in our first meeting with Sam that scaling the transformer was equivalent to the discovery of fire for the modern world. If you deeply believe that AI is as fundamental as the discovery of fire and the scaling laws will continue to hold, then the investing job really becomes very simple.
Thesis #1: Scaling intelligence. Or, training. OpenAI and Anthropic are the vanguards of this race, and I am lucky to work with both of these companies at Sequoia. But intelligence is not single faceted, and small teams armed with racks of compute can push forward the frontier. Ineffable Intelligence is building a superlearner that learns from experience with no pre-training or LLMs, led by the giant of reinforcement learning David Silver on the world’s first Vera Rubin cluster. Standard Intelligence is a team of precocious, hardcore 19-21 year olds who care greatly about alignment and are scaling an alternate path to general intelligence: the Tesla FSD approach applied to knowledge work on computer screens.
Thesis #2: Maximizing the units of intelligence that can be delivered to humanity. Or, inference. Fireworks was founded by Lin Qiao, former leader of Pytorch, and has quickly become the leading “own your intelligence” platform, allowing companies to build and own their intelligence rather than renting that capability from the model labs. Today, Fireworks serves 1 Quintillion tokens per month – how’s that for a new word! Etched was founded by an ambitious and dogged trio of Harvard dropouts who saw the magic of ChatGPT and realized the “inference singularity” was coming – that the world would fundamentally be compute-constrained, and that a specialized system maximizing the production of intelligence per watt would be both an incredibly fun engineering task AND an incredibly noble mission for humanity.
Thesis #3: Diffusion. Or, deployment. Harnessing this newfound fire and bringing it to the world isn’t always straightforward. I respect the founders who are taking AI and bringing it deep into different industries and communities, from hospitals to public safety to education to cybersecurity. AI is a hated technology outside Silicon Valley. The profound customer centricity and care it takes to win customers’ trust in these domains is remarkable, and incredibly important. All industries deserve the responsible diffusion of AI.
Much of my work today centers on one belief: we’re living through a singular moment in time. We’re entering a takeoff moment where systems that learn continuously will outstrip those that don’t. I’m looking for teams who know how to wield that power in building the companies of the future.
Personal Side
Art & Design / Vibe Coding / Sci-Fi / Techno Optimism / Museums / Vintage Shopping / Dog Watching
