Uber’s engineering blog has just posted an interesting piece[1] on the company’s web-based tool for exploring and visualizing data from self-driving car research. It’s a smart look at an impressive platform, and definitely has nothing to do with a long piece published last week lauding a similar platform in use by one of Uber’s most serious rivals, Waymo.
Okay, maybe it has a little to do with that. The piece, over at The Atlantic[2], is quite interesting, but seemed rather to suggest that Waymo is unique in its approach to improving its autonomous cars’ AI. In fact, it’s likely that every company working on this stuff has a pretty similar approach, at least if they’re keeping pace with the state of the art.
The cool secret technique that in fact all the companies in question know about is the possibility of using and learning from data that’s been hoarded over a million miles of test driving. Once you’ve driven that far, you have so much data that you can mix and match it in a virtual environment and let the AI navigate it just as if it were real. The computer doesn’t know the difference! Meanwhile you can tweak the data, watch for unusual events or compare multiple models.
The Uber post just focuses on visualization of this data, and with details on its tools, which are wisely web-based, leading to easy collaboration and quick turnaround on new features. These days web apps can access the GPUs, communicate in real time and so on — no need for a local client any more for many things. It makes for cool GIFs.
What the post doesn’t really get into, but is pretty much a foregone conclusion...