The camera ready version of my paper "iOS as Acceleration" at the Efficient Reasoning NeurIPS 2025 Workshop has been released publicly and can be found at this link:
https://openreview.net/forum?id=gYL59Z8KQe
Note: the discrepancy between the ResNet-34 acceleration percentage figure in the Program Chair review summary and the CR-paper version is due to a experimental figure that had been incorrectly reported in the initial submission but was corrected post-acceptance.
The camera ready version also includes an added thermal throttling experiment and more data figures from new experimentation using an iPhone 16.
I am in the process of making an arXiv submission (as I'm a first time author) and will post the link once the paper is on the archive.
Meanwhile, I wanted to write down some comments about what inspired this project and thoughts I had throughout developing it, and how I intend to continue my research journey.
Project Motivation:
Before starting this project, I had practically zero experience with AI-research (only some toy CNN & chatbot projects), though I had completed a couple of years of SWE and competitive programming.
Last summer however, I became more interested in understanding why and how AI actually works, and similar to how I had developed my general C.S. skills I started reading deeper and more complex papers, blogs, forum chains, etc.
I would say the paper that inspired the first thought connected to my iOS project was De-DLOC (
https://github.com/yandex-research/DeDLOC) - a milestone distributed training paper which had performed incredible volunteer internet training experiments using consumer desktops.
I was really drawn to the idea of collaborative computing as a solution for making ML more accessible, especially as I personally was severely limited in terms of hardware I could use for local ML experimentation.
My 2013 Intel Xeon ThinkServer desktop home setup. Everything is on the floor because we were moving tables around in our house.
The engineer within me also was greatly interested in the cross-device parallelism papers, as I saw they might be able to open the doors for me to engage with more powerful AI locally. As the only other device I had was an iPhone 11 Pro (the MacBook mentioned in the paper was my mother's work computer, the iPhone 16 we received from an internet provider deal), I wondered how much benefit I could squeeze out of it if I could somehow hook it up to my desktop, almost like an external GPU. Thus, the "iOS as Acceleration" project began. You can find more details about what I did in my paper linked at the top. Writing a paper myself was a new (scary at first) yet entertaining and very beneficial experience for me.
Future Work:
The main end goal I had planned for this project was to enable any user to "plug-and-play" their mobile phone into a computer and make everything go faster, with a stretch goal being an over-the-internet phone-based network (like a phone De-DLOC). Right now, the project is in the proof-of-concept stage, but I can see impacts being made in the future, especially in less privileged, resource-constrained environments e.g. local classrooms. There are still quite a few steps that need to be taken to reach the final goals (see future work suggestions in the paper), but I have a growing interest for other research questions, specifically regarding neuro-symbolic reasoning models and what it means for machines to "think". This project has been a very fruitful introductory experience to the AI research world for me, and I will still continue development on the idea, but it most likely won't be my primary focus moving forward. Though the spirit of the project remains with me: I want to continue exploring novel, unseen approaches to the problems we face.
Again, a big thanks to workshop organizers and reviewers for hosting the event and providing valuable feedback, and I'm looking forward to engaging with the community in San Diego!