Google AssistantI’m excited to share that I’ve recently joined the Google Assistant team! Like a lot of people (including our CEO), I’ve become convinced that natural language conversation represents the future of how we’ll primarily interact with computers and the myriad smart devices that will soon proliferate around us. This new “UI” will be personalized based on both knowledge of you and your history of interactions. It will also be proactive (reaching out to you with pertinent questions and updates) as well as responsive. And it will execute tasks across multiple, interconnected services on your behalf.

Which is to say: it’ll be a lot different than how we work with computers today. And it promises to be a lot better, too — if we can get it right.

I’ve been fascinated by interacting with my Google Home (which I’ve had early access to for a while). It highlights both the challenges and opportunities of this new conversational modality, and it surprises in equal measure with how far we’ve come and how far we still have to go. For instance, my 5 year old daughter walked into our living room the other day and proclaimed, “Ok Google, play some Lady Gaga”, then started dancing to the music that immediately began playing. Think about that: She would never have been able to accomplish that task with a traditional desktop/mobile app, nor would I have been able to help her as quickly as she was able to help herself. She didn’t have to be unnaturally precise (e.g. select a particular track or album), and it was an enormously empowering interaction with technology overall. It feels like “how things should work”.

I’ve had countless similar “wow moments” asking Google questions about the world, my own upcoming flights and schedule, or streamlining tasks like playing music or showing some recent photos I took on our TV to the grandparents. But for all the magic Google can deliver already, this is still very clearly early days. The dialogs are often too fragile and require too much custom crafting by too many Google engineers in a way that clearly won’t scale to the ambitions of the medium (and the team). There’s not yet much deep learning or true language understanding under the hood. And only recently has there even been a focused effort to build The Assistant, instead of just “voice enabling” individual products here and there. The industry as a whole is still only starting to figure out how “chatbots” and “conversational commerce” and so on should work.

Which is why it seems like an ideal time to get involved–we can tell “there’s a there there”, but we also still need many foundational innovations to realize that potential.

On a personal level, this change also represents an opportunity to get my career “back on track” after a wonderful decade+ diversion into the emerging world of social networking. I actually came to Stanford in the late nineties to study Natural Language Processing with the aim of empowering ordinary users with the superpower of Artificial Intelligence, and even published several papers and helped build Stanford’s first Java NLP libraries while earning my BS and MS. I originally joined Plaxo, an early pioneer of social networking, to build an NLP engine that automatically parsed contact info out of emails (e.g. “Oh, that’s my old address. I’ve since moved to 123 Fake St.”), but eight years later, I was still there, serving by then as its CTO and trying to open up the social web that had sprung up around us as the new way to stay connected. That in turn led me to join Google in 2010 as part of the founding team that created Google+, and I’ve been at Google ever since. But now I’ll actually be working on NLP again, and I have a feeling my years advocating for user-centric identity and data portability across services will come in handy too!

I’m uncomfortably excited to be starting this new chapter of my career. If you think about all the exhilarating potential surrounding AI these days, realize that a surface like Google Assistant is where you’re most likely to see it show up. One of the senior-most engineers on the team remarked to me that, “I’m sure a full Turing Test will be part of our standard testing procedure before long,” and I think he was only half joking. If you’re building similar things in this space, or have ideas about what we should prioritize building in the Google assistant or how you’d like it to integrate with your service, please let me know. I’m ready to learn!

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