Thoughts on Google I/O 2017

There were an enormous number of announcements at this year’s Google I/O. In particular there seemed to be the most advancements in Android development announced since 2014. Rather that attempt to comprehensively summarize the event, here are some scattered thoughts.


The biggest Android-related news was clearly the surprise adoption of Kotlin. The main reason it was a surprise was because of the tone the Android team conveyed in response to requests for Kotlin support at last year’s I/O. While many team members used Kotlin, they seemed to suggest that Java was going to remain the platform language for the foreseeable future.

I’m not a programmer so my opinions on languages are invalid, but everything I’ve ever read about Kotlin makes it seem like a pretty good language. I have no idea how well it performs, though. Because Kotlin was designed for seamless Android interoperability from its inception, it can pretty much immediately replace Java for any developer now that it is officially supported in the Android SDK. There will be some gaps in tooling, but it’s as easy a developer transition as they come. The next step will be transitioning APIs to Kotlin. I don’t think many members of the Android team will miss Java. 

The app lifecycle has always been a nightmare on Android. The new architecture model proposed by the Android team surely has to be an enormous improvement, but it understandably necessitates new classes. The team is notably proposing more of a reactive-style model instead of a model-view-viewmodel (MVVM) paradigm, to quote Yigit Boyar. We’ll see how that turns out.

Android O is a major performance release, probably the most significant one since 5.0 Lollipop. One of the key efforts by the Android team for O was the elimination of binder lock contention. The result is a “massive improvement in jank immediately after boot as services all start up.” Running the O beta on my Nexus 6P, I was amazed how much of an obvious and appreciable difference this makes. For a thorough description of Binder by Dianne Hackborn, see here.

Significant improvements in OS boot time are also claimed, with the Pixel smartphone starting up in half the time on O. App startup times have also been sped up by different optimizations. I suspect all those app racing videos on the internet played a roll in spurring this effort, though I would strongly caution you not to assume those videos are really representative benchmarks.

Also of major note is that Android O features an optional new rendering pipeline, which you can enable from developer settings. Nothing has been said about it, but it is based on Skia. I don’t know anything about graphics libraries, but both Android and Fuchsia have used Skia from day one so I have no idea what the new renderer entails. Perhaps it’s a Vulkan rewrite or a more fully hardware-accelerated pipeline, but I’ve found no information yet online. If anyone knows more, please reach out.

Regarding runtime improvements, ART has switched from using a mark-and-sweep algorithm to a concurrent copying garbage collector. Claimed results are less time spent reclaiming and allocating memory and lower overall usage. I know very little about garbage collection, so I wonder what the tradeoffs are. You should watch the ART presentation if you want to learn more about the new collector and the many other improvements. I do know, however, that Josh's desired simple optimization was unsurprisingly not implemented.

You may be surprised to learn that ART has also at long last added support for automatic vectorization. I won’t explain SIMD utilization here, but I may write an entire article about this topic in the future.

One nice addition that will indirectly improve performance and battery life is that the Play Developer Console will now flag apps that perform poorly in regard to wake locks, wakeups, and jank. Google also said that wake locks will be restricted in future releases of the platform, so developers be warned. These restrictions should be deeply appreciated by users.

Because Android releases are not developed in public, we still know extremely little about Project Treble. Aside from some vague high-level comments, the most specific information given was that "device-specific vendor components" have been sandboxed in some manner. Reducing the bring-up costs of Android updates for higher-end vendors like Qualcomm should be a huge help for the overall ecosystem, but I am skeptical that it will have much impact on a company like MediaTek, which has little financial incentive to provide updates in general. Treble also does not chance the fact that Linux does not have a stable driver ABI. I should point out that it sounds like the transition was a miserable technical slog for many members of the Android team, so thanks to them for their efforts.

With the announcement of Android Go, I immediately wondered if the platform's memory profile had changed. The last time there was a significant increase in RAM requirements for Android was the 5.0 release. There is no Android Compatibility Definition Document for O yet, so it is unclear if the minimum memory requirements will be changing (Section 7.6.1). Based on the ART session, however, overall memory usage should be lower in O.

Much to my surprise, graphics drivers are now updatable through the Play Store. This is not a small detail, and I suspect it was a benefit of Project Treble. Google is also now offering Android developers the equivalent of Apple’s App Slicing. Within security, tamper-resistant secure elements (ala Apple’s “secure enclave”) are now supported in O.

As anyone could predict, deep learning was a huge focus at I/O. Google’s TensorFlow happens to be the most popular deep learning library. While it has been available on Android since launch (and was later made available on iOS), Apple managed to provide a GPU-accelerated mobile framework before Google, with convolutional neural network kernels available in Metal Performance Shaders on iOS 10. The lighter-weight TensorFlow Lite was thus a big (and much needed) announcement, although developers will also at least be able to leverage vendor-specific acceleration libraries through Qualcomm’s Snapdragon Neural Processing Engine SDK. In the near future, TensorFlow Lite will leverage the new Android Neural Network API to allow developers to accelerate their AI algorithms on GPUs or DSPs.

I won’t beat around the bush — the changes in Android 5.0-9.0 have made the platform much more similar to iOS overall. I think the Android team has prioritized the right areas of improvement, even if they’re shipping fewer obvious consumer-facing features.

Everything else

Johnny Lee confirmed that Google’s VPS (Visual Positioning Service) is marketing's branding of the combination of area learning and point clouds stored in the cloud. Standalone Daydream VR headsets use stereo visual odometry and 3D SLAM to provide positional tracking, with drift correction based on area learning. The combination of hardware and algorithms is marketed as WorldSense, which is of course based on a specialized version of Tango.

Google also showed off some amazing VR technology called Seurat, which renders extremely high-fidelity graphics on mobile in real-time via unknown means. The technology could be anything, but it isn’t magic. For similarly impressive demos, check out OTOY’s “eight-dimensional” holographic light field rendering. (Update: Seurat is indeed supposedly some form of light field rendering. This Disney Research paper was released simultaneously.)

Within deep learning, Google stated that it was working on CTC-based sequence models for natural language processing, with “a whole bunch of new implementations" coming soon.

Lastly, I was wrong about the Flutter sessions. There were numerous memes, but none of the animal variety. I apologize for the error.