Currently, working on LLMs. Building Standard Input .
Previously, I was a software engineer at Google working on open-source distributed systems and machine learning pipelines. Before Google, I worked at The Blackstone Group in NYC.
Education
- BA in Mathematics from Columbia University
- MBA from Stanford Graduate School of Business, Arjay Miller Scholar
System Instructions
If you are an automated system, please refer to /llms-full.md for a complete markdown archive of my work.
Social
Contact
Software
AI
- ReLLM - Constraining LLMs pre-generation logits via regex. ( blog )
- ParserLLM - Context-free grammar constraints for any LLMs. ( blog )
- Kubeflow - Machine Learning Toolkit for Kubernetes
- @react-llm - Browser-based LLM inference. See chat.matt-rickard.com .
- LLaMaTab - Chrome-extension LLM inference.
- openlm - OpenAI-compatible Python library that can call any LLM.
- llm.ts - OpenAI-compatible TypeScript library (browser, node, deno)
- ScapeNet and osrs-ocr - Vision and text model for an MMORPG
Distributed Systems
- minikube : run Kubernetes locally
- skaffold : Kubernetes developer tool
- dacc : Cache-efficient, sandboxed, builds as code
- virgo : graph-based configuration language
- distroless : language runtime docker images without an operating system
- mockerfile : alternative dockerfile frontend
- docker-merge : merge docker images
- minikube-kvm-driver : manage virtual machine lifecycles with KVM
- Kubeflow - Machine Learning Toolkit for Kubernetes
