ServerlessConf Paris is in full swing this week, and I had the chance yesterday to participate in a workshop with my colleague Frank, to cover building apps for voice, chat, web and mobile, using Google’s serverless solutions. In particular, for voice & chat, I spoke about Dialogflow and Google Assistant / Actions on Google, using Cloud Functions for my business logic, while in the afternoon we covered Firebase un more depth.

If you want to have a quick look at the deck, here are the slides that I presented:

Today, there were some interesting announcements for Actions on Google, for building your conversational interfaces for the Google Assistant. Among the great news, one item particularly caught my attention: the improved SSML support:

Better SSML: We recently rolled out an update to the web simulator which includes a new SSML audio design experience. We now give you more options for creating natural, quality dialog using newly supported SSML tags, including <prosody>, <emphasis>, <audio> and others. The new tag <par> is coming soon and lets you add mood and richness, so you can play background music and ambient sounds while a user is having a conversation with your app. To help you get started, we’ve added over 1,000 sounds to the sound library. Listen to a brief SSML audio experiment that shows off some of the new features here.

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A few weeks ago, my buddy Wassim and I had the chance to present again on the topic of chatbots, with API.AI and Cloud Functions, at the DevFest Toulouse conference.

Here’s the latest update to our slide deck:

There’s also a video (in French) of the same content from Devoxx France, where I was showing how to build a conference chatbot:

Chatbots, per se, are not really new, in the sense that we’ve been developing bots for things like IRC for a long time, but back in the day, it was simply some regular expression labor of love, rather than the natural language that we use today. The progress in machine learning, in both speech recognition (for when you use devices like Google Home) and natural language understanding (NLU), is what led us to being able to speak and chat naturally to those chatbots we encounter now.

In two weeks, I’ll be flying east, much further east than I’ve ever been! I’ll visit Singapore! And I’ll have a pretty busy week with several events: conference, meetup, user groups, brown bag lunch… and I’ll talk about Groovy, Machine Learning, and chatbots!

First of all, on Wednesday 31st, I’ll participate to the Singapore Java User Group, where I’ll give an update on Apache Groovy (the latest improvements, new features, the roadmap).

That’s Devoxx France this week, and I’ve had the pleasure of delivering today another talk on the theme of chatbots, using Cloud Functions for the business logic, API.AI for the bot cleverness, with a bonus of a demo through Google Home and the Google Assistant platform.

I’ll post the YouTube video recording once it’s online, but in the meantime, I wanted to share my slides here:

And the video in French:

Last week, in San Francisco, took place the Google Cloud Next 2017 conference, and I had the pleasure to co-present a session on “Extending the Google Assistant with Actions on Google”, with Brad Abrams, product manager on the assistant technology at Google.

The Google Assistant is the conversational user interface that helps you get things done in your world. Actions on Google let you build on this assistance, while your integrations can help you engage users through Google Home on Pixel, Android and many other devices that connect with Google Assistant. In this session, we’ll share the latest innovations behind the Google Assistant and how you can leverage those technologies and best practices for Voice User Interface design to build your own custom extensions to Google Assistant.

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For Google Cloud Next and Devoxx France, I’m working on a new talk showing how to build a conference assistant, to whom you’ll be able to ask questions like “what is the next talk about Java”, “when is Guillaume Laforge speaking”, “what is the topic of the ongoing keynote”, etc.

For that purpose, I’m developing the assistant using API.AI. It’s a “conversational user experience platform” recently acquired by Google, which allows you to define various “intents” which correspond to the kind of questions / sentences that a user can say, and various “entities” which relate to the concepts dealt with (in my example, I have entities like “talk” or “speaker”). API.AI lets you define sentences pretty much in free form, and it derives what must be the various entities in the sentences, and is able to actually understand more sentences that you’ve given it. Pretty clever machine learning and natural language process at play. In addition to that, you also have support for several spoken languages (English, French, Italian, Chinese and more), integrations with key messaging platforms like Slack, Facebook Messenger, Twilio, or Google Home. It also offers various SDKs so you can integrate it easily in your website, mobile application, backend code (Java, Android, Node, C#…)