Zoa Research YC 지원서

Summer 2024Active

Zoa Research은(는) Summer 2024 배치에서 B2B 회사로 Y Combinator를 거쳤습니다. 아래에는 회사의 사업 내용, 창립자, 그리고 실제 YC 양식에 맞춰 재구성한 YC 지원서가 있습니다.

YC 배치: Summer 2024
산업: B2B
팀 규모: 5
상태: Active
출시됨: 2024

창업자

Greg VolynskyFounder
Sam DamashekFounder

Zoa Research의 사업 내용

Historically, quantitative models are domain specific. Brilliant people spend their best years testing features, tuning hyperparameters, and iterating architectures within a narrow domain. But scale is the panacea: large models will find patterns people, and specialized models, could not. Forecasting generalizes. Zoa trains cross-domain event forecasting engines. *Automating Iteration* LLMs - embedded in multi-agent optimization loops and evaluated against fixed policies - can automate the build-test-improve modeling cycle. Think AlphaEvolve for forecasting problems. *Sample-Efficient General Models* Today’s forecasting models are narrowly crafted with deep human priors. But larger models will outperform state-of-the-art specialized models. Unlike existing event models, our models leverage data from across contexts and rely less on human intuition. And compared to LLMs, our models are built with more inductive priors and rely more heavily on inference-time compute - improving sample efficiency. *Why It Matters* In the real economy, our models could be useful for forecasting supply chain volatility, energy supply and demand, even earthquake risk. Science is, Ian Hacking writes, the taming of chance. It is the process of iteratively updating priors (something like: identify uncertainty, conceive experiment to reduce uncertainty, execute, update). If science is uncertainty-reduction, forecasting is a critical measure of progress. Better forecasting improves our ability to select interesting experiments (roughly those with greatest expected uncertainty reduction) and update priors. Our models will be used by labs and academics in data-heavy domains. Sam's ex-girlfriend introduced him to Greg back at Carnegie Mellon in 2017, and while that relationship didn't last, their friendship has. After college, Greg went to Harvard Law School, while Sam worked for three years at Jane Street on their Options desk, building & leading a satellite dev team.

Zoa Research의 YC 지원서, 재구성됨

Y Combinator 지원

Zoa Research, Summer 2024 기수. 공개 데이터를 기반으로 작성된 실제 지원 질문.

Founders2
Company7
Progress7
Idea4
Equity3
Curious2
Batch Preference1

Company

Company name

Zoa Research

Describe what your company does in 50 characters or less.

Powerful quantitative forecasting models

What is your company going to make? Please describe your product and what it does or will do.

We build generalizable event forecasting models that train across diverse domains rather than specializing narrowly. Our models automate the build-test-improve cycle by embedding LLMs in multi-agent optimization loops. This extends forecasting beyond traditional domain-specific models, making predictions about supply chains, energy, and risk using data integration and sample-efficient inference.

Where do you live now, and where would the company be based after YC?

We live in New York, NY, and the company is based here now and would remain so after YC, at least initially.

Explain your decision regarding location.

Most of our experience and network is in New York. We don't see a pressing reason to relocate; YC is remote-friendly and we can engage with the network while continuing to build where we are.

전체 지원서에서 21개의 추가 답변

Founders, Progress, Idea, Equity, Curious, Batch Preference는 전체 버전에 있습니다. 무료 계정을 만들어 YC Insights에서 모든 YC 배치 옆에 열어보세요.

전체 지원 보기

자주 묻는 질문

Zoa Research의 실제 YC 지원서인가요?

아닙니다. Y Combinator는 제출된 지원서를 비공개로 유지합니다. 이것은 재구성된 것입니다. 실제 YC 양식 질문에 Zoa Research의 공개 데이터(출시 노트, 창업자 배경, 제품 설명)를 기반으로 답변했습니다. Zoa Research과 같은 회사가 YC에 어떻게 자신을 소개하는지 보여주며, 그들이 제출한 텍스트는 아닙니다.