if you want a machine learning challenge, go work at apple
Apple has recently joined the machine learning and deep learning craze. They are hiring at an accelerated pace and competing to hire form the same talent pool as all the other Silicon Valley companies.
They have a unique set of challenges compared to companies like google. Apple has championed privacy as one of their core beliefs. That means building out the same features as many other companies, but without sharing data back to apple or other 3rd party services. Services like recommendations, search, and voice assistant need to work from the device as opposed to over the cloud. That affords the end user access to these helpful services, while not comprising their privacy by sending all the data to the cloud.
This probably presents a challenge for apple when hiring as software developers want access to as much data as possible when building their models. That is part of the allure of working at google, unlimited access to all their data. I wonder how often their copy of the internet is processed to test out new models.
I would say that working at apple is an ambitious and worthy challenge. For their machine learning models to work, they need to get their models to run fast and efficiently directly on their devices. That means these algorithms have access to less resources and less data compared to a company like google. In the long term, it could mean the creation of newer and better algorithms that can run on their constrained devices. Working at apple on these machine learning problems could mean breakthroughs as they are coming at these same problems as everyone else, but from a completely different angle.
What I find innovate about apple is they are masters of creating efficient hardware to solve current real world needs. Their A series chips that power all their iOS devices are always the best in class ARM chips. Every time they release new iOS devices, their chips outperform all the other devices. I would wager that apple will develop dedicated chips to power their deep learning initiates if they haven’t done so already. To do efficient deep learning, you currently need fast concurrent floating point calculations which means graphic cards. There is one company currently who provides graphic cards that are great for deep learning applications and that is NVIDIA. And even with NVIDIA chips, efficient still means weeks of training to build their machine learning models. Right now NVIDIA basically has a monopoly on deep learning hardware. Working at Apple could foster more competition and innovation in deep learning hardware.