Advancing Mac-native
intelligence.
MacPaw Research is a research department at MacPaw, focused on LLM efficiency, AI memory, and human–computer interaction - turning findings into the Mac products people use every day. Papers, tech notes, and highlights, published as we go.
Research highlights
Recent publications
Explore all publicationsEvaluating the Applicability of LLM Inference Optimizations on Apple Silicon
On-Device Intelligence: Foundation Models under Real-World Constraints (ODI) @ NeurIPS 2026
Rigid 3D Object Alignment: Optimization vs. Feed-Forward Prediction
7th Workshop on Open-World 3D Scene Understanding and Representations (OpenSUN3D) @ ECCV 2026
GenRA: End-to-end Framework for LLM-Driven Animation of Rigged 3D Models
7th Workshop on Open-World 3D Scene Understanding and Representations (OpenSUN3D) @ ECCV 2026
Memory Belongs to the User: Portable Memory, an Open Standard Proposal for Cross-Vendor AI Memory
Research partners
University collaborations driving co-authored work, internships, and our long-term talent pipeline.
- Cambridge, MA
MIT
Internships and joint research with CS students on efficient on-device inference and applied ML.
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- Kyiv
Kyiv-Mohyla Academy
Faculty of Informatics - joint applied-AI research, summer schools, and a steady stream of Kyiv-rooted ML engineers.
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- Lviv
Ukrainian Catholic University
Faculty of Applied Sciences - joint research, internships, and a steady talent pipeline.
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- Kyiv
KPI Igor Sikorsky Polytechnic
Home of the MacPaw AI Lab "Bilka Space" and a MacPaw-funded scholarship for applied-ML students.
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Open to collaboration
Build Mac‑native intelligence together
We partner with universities, research labs, and industry teams on frontier AI - on-device runtimes, LLM efficiency, AI memory, and human–computer interaction. If your work intersects with ours, we'd love to hear from you.
Email the team [email protected]