Choose your language

Choose your language

The website has been translated to English with the help of Humans and AI

Dismiss

Scrap the Manual: Tech Across APAC

Scrap the Manual: Tech Across APAC

19 min read
Profile picture for user Labs.Monks

Written by
Labs.Monks

Scrap the Manual - Asia Pacific

APAC is not only one of the most populous and diverse regions in the world, it is also leading the way for unique technologies and innovation. In this episode, host Angelica Ortiz is joined with a fellow Media.Monks’ Creative Technologist, Leah Zhao from our Singapore office. Together, Angelica and Leah give a TLDR overview of our newest Labs Report, Tech Across APAC—providing insight into the regions’ emerging AI, AR, automation, and metaverse technologies–along with a sneak peek into the prototype leveraging an upcoming tech from the region.

You can read the discussion below, or listen to the episode on your preferred podcast platform.

00:00

00:00

00:00

Angelica: Hey everyone! Welcome to Scrap The Manual, a podcast where we prompt “aha” moments through discussions of technology, creativity, experimentation, and how all those work together to address cultural and business challenges. My name is Angelica and we have a very special guest host. Yay!

Leah: Hi! It's great to be here, my name is Leah. We are both Creative Technologists with Media.Monks. I specifically work out of Media.Monks’ Singapore office.

Angelica: Today we're going to be giving a quick TLDR of one of our lab reports and deep dive into something that we didn't get to cover in depth in the reports, such as expanding on our prototype we created, a topic that has some interesting rabbit holes that didn't fit neatly onto a slide, you know, that kind of thing. 

Leah: So for this episode, we are going to be covering technology and innovation culture in Asian Pacific region. If you haven't had a chance to read our APAC Lab Report, here's a quick TLDR.

The most influential technologies from the region are AI automation, AR and computer vision, and the metaverse. China and Japan are leading the growth in AI and machine learning together with Singapore and South Korea. If you come to this region, you might be surprised how people are embracing this advanced technology. People accept it because it is just so convenient and thanks to those Super Apps we have. 

Angelica: To clarify for people who may not be familiar, what are Super Apps? 

Leah: Yeah. So Super Apps are mobile applications that can provide multiple services. And you may have heard of some of the Super Apps such as WeChat in China. Kakao from South Korea, Line app from Japan (that's also widely used in Taiwan and Thailand) and Grab from Singapore, which is used in Southeast Asia. On Super Apps, you can use multiple services from online chatting, shopping, food delivery, to car hailing and digital payments. We literally live our social and cultural life on the Super Apps.

Angelica: Is it sort of like if Uber had one app, but not necessarily branded it's more of just, I'm going to go to WeChat, it'll call a ride, rent a scooter, or order in. You just download one app versus having to download five different ones. 

Leah: Yeah, definitely. But actually for WeChat, it's more complicated, I would say, because there is a whole ecosystem on WeChat because WeChat uses mini programs. Just think of as a microsite on WeChat…

Angelica: Mm-hmm. 

Leah: where they can sell their product and they can have these food delivery services. And for other Super Apps like Line app and Grab it's just exactly like you said. One example is that Burberry launched its social retail store in collaboration with Tencent, which integrates its offline store with mini programs on WeChat. It enables some special features in the store, such as earning social currencies, by engaging with the brand and even raising your own animal based avatars. This is pretty cool as it links up our digital and physical experiences. 

Angelica: Yeah. What I really liked about this example was how technology was seamlessly integrated throughout. It wasn't like, “Hey scan this one QR code.” It went a little bit further to say, “Okay, if you interact with this mini program, then you'll have access and unlock particular outfits or particular items for the digital avatar. You'll be able to actually unlock cafe items in the real store.” So it seemed like it was all a part of one ecosystem. It didn't feel tacked on. It was truly embedded within the holistic retail experience. I know with a lot of branded activations within the US specifically, there's always that question of, should it be accessible through a mobile website or is it something that we can use a downloaded app for? And most clients tend to go with the mobile website. 

Leah: Yeah. 

Angelica: Because there's this hesitancy to download just another application, just to do another thing. And then worrying about the wifi strength when on site when asking people to download these apps. But it'd be interesting for brands creating these mini programs within a larger Super App that then consumers won't necessarily have to do anything else other than access that mini program versus having to download something. Then there's a lot more flexibility in what brands can do and they're not limited to what's available on a mobile website. They have the strength of what can be possible with an app. 

Leah: Yeah, agreed. So another observation actually from our report is that the metaverse is on the rise in the APAC region. It might outplay the plans laid down in the West. Some platforms that draw our attention are Zepeto from South Korea and TME land in China. 

Angelica: Yeah, and what's cool about those platforms is we see this emphasis on virtual idols, avatars and influencers. From the research that we did, we noticed that there are certain countries that are a bit more traditional culturally… 

Leah: mm-hmm

Angelica: and are strict in how people can be in their real selves to have this sort of escape of the bounds culturally of what people can and cannot be because it's right or wrong or not necessarily accepted. People are going towards anonymity…

Leah: Yeah. 

Angelica: for being able to express themselves. Sort of like the Finstagram accounts that happen in the US or expressing themselves through these virtual influencers, because then their virtual selves can be much more free to express themselves than their real versions could be.

Leah: And also Asia has a rich fandom culture. So it's not a surprise that we see the emphasis on virtual idols and virtual influencers because it enables the fans to interact with the superstars anytime, anywhere.

Angelica: Yeah. And from a branding aspect of things as well, virtual influencers and avatars can also be much more easy to control. Like all the controversies that happened because someone did something either way back in their past or something recently, that makes brands nervous about being able to endorse real people because people are flawed. With virtual influencers, you can control everything. You have teams of people being able to control exactly what they look like, what their personality is, what they do, and that flexibility and customizability…that's a lot more intense than it would be for a real person that has real feelings.

So there's some limitations on what the brand can do, where it's a lot more flexible with virtual influencers. 

Okay, we've covered quite a lot there. There's a lot of really interesting examples that we see within the APAC region that definitely could be applied within Western countries as well. With this said, we're gonna go ahead and move on to what we did for the Labs Report prototype and expand a little bit more on our process.

Let's start with: what was even the prototype? For the prototype we leveraged Zepeto. Zepeto is a metaverse-like experience world platform…insert all buzzwords here…where it allows users to interact like you would for a Roblox world that you go and experience to, but it has additional social features to it.

So what we would think of as an Instagram feed or something like that, it has that embedded within the Zepeto platform. So instead of going to Instagram to talk about your Roblox experience, those two experiences are integrated within one platform. What we also wanted to achieve with this prototype is leverage a technology that originated from the APAC region, and specifically Zepeto. Zepeto is available globally for the most part, with a few exceptions, but it originated within South Korea. We really wanted to use Zepeto because it's available globally for most audiences and it takes the current fragmented way of how the metaverse worlds are created and integrates them with virtual influencers and social media.

With these gamified interactable experiences, the social aspects are really what makes this particular platform shine. And we are also doing this because the metaverse even a year or so later is still an incredibly popular topic. People are still having a lot of discourse about what the metaverse is, what it can be, discussing how brands have already interacted with their first steps into the metaverse, how they're going to continue to grow.

And this is part of what we do a lot at Media.Monks. We get a lot of client requests for similar types of experiences, whether that be Roblox, Decentraland, Horizon World, Fortnite…and Zepeto is just a great platform that no one's really talking a lot about within the Western dialogue, but it's incredibly powerful and it reaches so many people. We saw that it was an amazing platform that put the promise of what the metaverse can and will be to the next level.

Leah: Yeah. I also like Zepeto because Zepeto not only has Asian style avatars and it enables you to customize your avatar from your head, body, hair, outfits, and even poses and dancing steps you can have. So with Zepeto you can purchase a lot of outfits and decorations with the Zepeto money, which is a currency that you earn by app purchases or being more active on the platform. 

Angelica: Yeah. There's two different types of currencies that Zepeto has. One of which are called Zems…i.e. gems. And then there's another one, which are coins. For creator made items, you can set a price for how many Zems you want them to go for. Anything that's created by users can only be sold by Zems, which are very difficult to get free with an app. That's where, you know, the free to play tends to come in. With a Euro you can get 14 Zems, so then you can buy more digital clothing. There are coins that you start the experience with that you can use to purchase Zepeto-created items. And so that's kind of how they have that difference there. 

Leah: But my favorite part about Zepeto is the social aspect as you mentioned earlier. For me, it's like TikTok in the metaverse because it has the Feed feature.

You know, there are three pages of the feed: For you, following, and popular. Under the feed you can see live streaming by the virtual influencers and you can have your own live stream as well.

Angelica: For the live stream that's using some motion capture as well, because it's either pre-made models and moves that are created or people can actually have their face being recognized in real time...

Leah: Yeah. 

Angelica: to then translate to that virtual avatar. 

Leah: Yeah. Zepeto, they have the Zepeto camera. So with this camera, you can create content with your own avatar and the AR filter, which copies your facial expression quite accurately, and even brings your own avatar to real life. So you can place your own avatar on the table in your room.

Angelica: One part that I also thought was really cool…you had mentioned earlier with the poses. Think about if we see a celebrity on the street, we're gonna take a photo with them. Right. We can't just let that celebrity pass by without being like, “oh yeah, I totally saw JLo in Miami,” you know? The “take a photo or it didn't happen” type of thing, haha. There's a version of that on Zepeto. Fans can take a photo with you with their virtual avatars with your virtual avatar. So it takes the virtual autograph, of sorts, to a different level. You can live vicariously through your avatar by having them take a photo with your, your favorite celebrity or your favorite influencer. So I really love that aspect of being able to build that audience virtually as well. 

Something also that's really cool about Zepeto is within those world experiences, the social aspects are still very much ingrained in there. It's not just, “Okay, you have this separate social feed, you have the separate virtual influencer side, and then you have the world.” They're all integrated.

An example of this is the other day we were testing out the Zepeto world and we were all in the same experience together. When someone would take a selfie, and that's right: there is a selfie stick in this experience and it looks exactly like what you would imagine, but the virtual version of it too. And when someone takes a photo or a video, it automatically tags people that were within that photo.

So it's generating all of this social momentum, like really, really quickly. And soon as you take that photo, you can either download it directly to your device. Or you can go ahead and immediately upload it. What was great for me personally…figuring out how to have, you know, just the right caption... that's something that takes me way too long to figure out what are the right words and the right hashtags. But you don't even need to worry about captions when taking photos within these worlds. As soon as you say, “I wanna upload it,” it automatically captions, tags people, and also gives other related hashtags for how other people could see that experience from you.

So it's very seamless and easy. 

Leah: Yeah. That's amazing. 

Angelica: It's just like the next level of how it makes sharing super, super, super easy, so that's something I really like there too. 

Speaking of the worlds: now, within this next part of the prototyping process, it was up to us to determine the worldscape and interactions. And as a part of the concept, we wanted to create a world that plays into what real life influencers would be looking for when trying to fill their feed. And that is: creating content. Specifically: selfies. And so we created four different experiences that would have the ultimate selfie moment.

One, which is this party balloon atmosphere. Sort of think about these like really big balloons that you can kind of poke with the avatar as you move around, or even like jump on some of the balloons to get a higher view from it as well.

The second was like a summer pool party. You could actually swim in the pool. It would change the animation of the avatar when you're in the water part. And, you know, the classic, giant rubber ducky in the pool and all those things. So definitely brought you in the moment.

The third was an ethereal Japanese garden, so very much when wanting to get away and have a chill moment, that was definitely the vibe we were going for there.

And then lastly, we had the miniaturized city. So what you would think is the opposite of meditation is the hustle and bustle of the big city. And we created that experience as well. There is also a reference to the Netherlands. So you'll just have to keep an eye out for what that is and let us know if you find it.

Leah: Is there a hidden fifth environment?

Angelica: There it is. Yeah. You know, what was interesting is when we were testing out the environment and we were all together. 

Leah: Yeah. 

Angelica: We created our own room. 

Leah: Yeah. 

Angelica: And then we thought it was just gonna be the eight of us that were testing it out and then other people, random people showed up. 

Leah: Wow.

Angelica: I was just like, “where did you guys come from?” There were two people that actually used the chat within the room and they belined directly to where that fifth environment was. 

Leah: Yeah. 

Angelica:  So it was just really interesting that people one were specifically coming to the world to experience it together.

Leah: Mm. 

Angelica: And then two, we saw a lot of random people. There would be dead spots where it’s just like, “okay it's just one of us in the room.” We're just testing it. But as soon as all of us got in there together and started taking photos, there were so many people that showed up. It's just like “What? This is insane!”

Leah: Was it the recommendation system on Zepeto?

Angelica: Yeah. That's what we're thinking. Because the room that was created…we thought it was not, I guess it wasn't a private room. It was probably a public room. 

Leah: Yeah. 

Angelica: But it was interesting that as soon as we started playing around and posting content, then people were like, “Okay, I'll join this room.”

Leah: Yeah. Maybe because of tagging as well.

Angelica: Yeah, exactly. And that goes to our earlier point of how really powerful that platform is and how posting would give that direct result of someone posting something and other people wanting to be a part of it. There was one person that liked my post that had like 65,000 followers.

Leah: Whoa. 

Angelica: And I'm like, who are you? What is this? 

Leah: That's definitely a virtual idol. 

Angelica: Yeah, exactly. They only had like six posts though, which was a little weird, but they had so many followers. It was nuts. 

Leah: Actually today I just randomly went into a swimming pool party on Zepeto. I went into the world, people were playing with water guns together.

Angelica: Mm-hmm 

Leah: So I had just arrived. Landed. Then someone just shoot me with a water gown and I was hit. I must lose my block. 

Angelica: Oh no! Haha, that sounds fun though. 

Leah: Yeah, that was fun. 

Angelica:  Was it like a big room? Like how many people were in that environment at once? 

Leah: When I was there, it was around 80 people in the world.

Angelica: Oh, wow.

Leah: Yeah, it's quite a lot actually. 

Angelica: There's definitely something to be said about how there's superfans of Zepeto. Like that's kind of part of the daily aspect of it. Being able to meet people through the social aspects and then hang out with them through these worlds.

But all this to say this entire worldscape and all these interactions that we included within the prototypes were all built within what they call their BuildIt platform.

Leah: It's quite user-friendly. It's very easy to create a world yourself even with zero experience of any 3D modeling software. 

Angelica: Yeah. BuildIt is like a 3D version of website builders. You have the drag and drop type of thing. Where instead of a 2D scrolling website experience, now you have that drag and drop functionality with a lot of different assets into a 3D space. We can also create experiences like this through Unity. The only caveat to Unity is that the experience that we would create there would only be available on mobile devices. And we didn't wanna restrict the type of people that would be able to experience this. So we decided to do it on BuildIt because the end result of those worlds would be able to be accessed on both desktop and mobile. 

Leah: Other than the world space, you can also create some clothes for your avatar to make it look more unique and with its own personality. So in our case, we create a more neutral looking avatar with blue skin. Very cool, they're slightly edgy but approachable. And the process of creating clothes was very friendly. So you just download the template and then add the textures in Photoshop. We chose a t-shirt, jacket, bomber, and wind breaker. And then we touched it up with some Oriental elements such as a dragon and soft pink color, which matches our Shanghai office. Everyone can create their own unique clothes with simple editing of the textures. 

Angelica: Yeah. We really wanted to play within clothing specifically because that's a part of this digital ecosystem of being an influencer. You may have branded experiences that you take part of, or brands sponsor you. Influencers will wear custom clothing either that they design or that they're representing another brand. All those things we wanted to integrate within this. 

So the influencers are visiting this world. They could say, “Hey, I'm in this Media.Monks experience” or “insert brand here” experience. And I'm also wearing their custom clothing. It's sort of a shout out to the clothing as well as the world. So it's at the heart of this larger ecosystem. The world is not exclusive to the clothes…is not exclusive to social. All of those elements are all playing together and this leads to creating social content.

Once we had the world and the merchandise solidified, we continue to build off this virtual influencer style by creating content of our own. What we did is we analyzed popular Zepeto influencers. We even made a list of the types of content they create, which is going to someone else's world, doing an AR feature with their real life self. Being able to do posed photos with other avatars. All those were a part of the social content that we created as a part of this. 

Now that the prototype is ready to go, it's time to think about what the prototype did not yet achieve but that we would really like to see in the future. So one thing that we recommend is: when wanting to create branded fully custom worlds, those should definitely be made within Unity to have the most flexibility. At this time of recording, being able to export worlds means that only is on mobile devices. So, you know, that's something to keep in mind there. 

Leah: For clothing creation, there are some limitations. For example, for the texture, the maximum resolution we can upload is 512 x 512. So it means we can't add detailed patterns or logos onto our clothes. And we can't create physics of our clothing materials. That is another thing that I think the platform can improve. 

Angelica: Yeah. It's not able to show the fuzziness of a sweater or if we're creating a dress or a shirt that needs to be flowy, it won't show that that shirt or that dress is fuzzy or flowy. It'll just be the pattern that's shown, but the texture of how a clothing might feel based on seeing it is not reflected there. So it's a give and take where it's very easy to create clothing items 

Leah: Yeah. 

Angelica: …but it doesn't go so far as to have a realistic look. 

Leah: Yeah, but I think this is something that’s not just Zepeto. Other metaverse platforms can improve with that because I don't see many platforms can have physics of the clothing itself. It would be great if the physics of the clothing could be implemented in the workspace as well as in the AR camera. It would add extra immersion and fidelity to the whole experience. 

Angelica: Yeah. It would also help with making those small micro interactions really fun. Let's say there's a skydiving experience that's in Zepeto and someone is jumping off of the plane and is doing their skydive.

Leah: Yeah.

Angelica: It'd be cool. If the physics of the clothing would react to, like this virtual wind that is happening, or something like that. Or if it's a really puffy sweater, it kind of like blows up because all of the air is kind of getting stuck in it. Those are just the fun things that make people get even more immersed within the environment too. 

Moving forward in creating branded experiences, having a closer relationship with Zepeto’s support team and development team will be really helpful in a lot of the things that the BuildIt platform has a restriction for. But when collaborating with Zepeto and with using the Zepeto plugin for Unity, then we can unlock a lot of interactions that make the experience a lot deeper. 

The other thing to mention here is it'd be really great to see Zepeto integrate with other social media platforms versus the Zepeto specific one. We've talked a lot about how Zepeto is a really powerful platform because it combines social with the virtual experience as well. And it would just be great if let's say there's an experience that happens in Zepeto and we're taking a photo or video, we say we wanna post it. Could that be post, all in one swoop, be posted to Instagram, posted to Twitter, posted to Facebook and all of those things, instead of this Zepeto ecosystem kind of being stuck.

So all the cool stuff that we're saying, it gets left within this platform and they're not necessarily shared outside of it unless you did the repost thing. That's kind of how it would work with Zepeto, but it'd be really great if all those rich features that we get with Zepeto could be extended to other platforms.

And I mean, there's already the platform fatigue of having to keep up five or many more social media platforms. So auto captioning for Instagram would be great or having an experience in Zepeto and then moving that on to what I wanna post on Twitter that would just make the process so much easier. 

Leah: The full integration of that might take some time…

Angelica: Mm-hmm 

Leah: since there are more things to consider such as data privacy. 

Angelica: Yep. 

Leah: But we might say it's coming faster in APAC. If one day the metaverse platform is integrated into the Super Apps. Just imagine by then it would be truly one ecosystem. 

Angelica: Exactly. It'd be a really powerful way to have things all within one place. Meta has tried with this “connecting what you do virtually and connecting it to other social media platforms” specifically within its own ecosystem of Facebook, but it's had mixed success. There's just not as much of, “Okay. I'm posting what I'm doing in VR to Facebook.” There's not as much of that traction happening as with going in Zepeto, having this experience, posting it, and people randomly show up because of the social stuff. You could see that immediate interaction. It'd be really great to see this integration outside of just Zepeto social into other social media experiences to really expand its reach. Also particularly because of the virtual influencer aspect of things. Just imagine having this facial mocap that you do within Zepeto and that livestream could go to Instagram, Facebook, and multiple platforms at once. That would really increase the visibility of that virtual influencer and the social clout. 

So we're getting towards the end. Let's go ahead and think about what are some concrete takeaways that the audience can implement and use within their daily lives, as they're considering Zepeto. And then also just in general, the APAC trends that we're seeing here.

Something that I think of is: gaming and social media don't have to be separate anymore. Like when playing online experiences, traditionally, it'll be either playing Warhammer on Steam and having the voice app within there, or opening up Roblox and a Discord channel. But those are two separate platforms: one to connect and one to play. With Zepeto, it's really inspiring to think about how those interactions can be in one. And not just voice, but the social aspect and everything that comes with that. It's really the next level of getting closer to what we talk about the metaverse can be. And Zepeto is really inspiring in that way. 

Leah: Yeah. To your point about this social aspect: Zepeto is actually what we need right now. We can't expect everyone directly dive into virtual without connecting them with the social life in the real world. And Zepeto has this potential to bridge the gap between our social life in the physical world and the digital one. 

Angelica: Yeah, Zepeto is a sleeping giant of sorts where it could have huge potential for a global audience. It is accessible in other countries outside of the APAC region, like we mentioned, but there's just not as much buzz around it as the platform definitely deserves. There are platforms that have tried to have the integration that Zepeto has within those three categories of virtual influencers, social media and experiences. But there just hasn't been as much from those other platforms as Zepeto has been able to succeed in.

So like Decentraland, Sandbox Roblox, Fortnite, Horizon Worlds…all those platforms have tried to get this integration, but it just has not been as successful. Something also to keep in mind and why Zepeto is just a really great platform is that there have been brand activations that have happened on Zepeto already.

There have been concerts and virtual representations of BTS or even Selena Gomez going into those concerts. Like what we applauded a few years ago with the Fortnite concert, Zepeto has already been within those realms already. There's a Samsung activation. There's a Honda activation, and a Gucci one as well.

And those are definitely getting a lot of traction and movement with people who are actually part of those experiences. And because it's integrated within its own social media ecosystem with purchasing items with virtual influencers, there's just so much potential for when brands are getting into these spaces, the type of impact and interaction they can have with consumers.

Leah: Yeah. The last thing we learned from this region: currently the West and the East still feel very distinct technologically and also culturally, with some crossover happening, but it's not as much as we would like to see. Things like virtual influencers, technology in retail, Super Apps, increased use of digital payments, those have been used to deepen collections with consumers and enhance ease of use. It would be amazing to see that more widely integrated within the West.

Angelica: Yeah, exactly. There's a lot of cultural and technological crossover to Eastern countries in terms of, you know, the US culture and colloquialisms always make their way around the globe. And it would be really great to see the really impactful technological and cultural innovations that are happening within the East, make their way more holistically towards the West. Not just here or there, but how Google has been embraced within APAC. It'd be great to have some of those APAC platforms integrated in the west. There's a lot that each can learn from each other and build up on each other. It's not necessarily let's distinguish the West from the East, because we talked about that quite a bit, but what is the way that globally we can improve experiences for consumers. And there's a lot of ways technology can empower people to have those deeper connections and how brands can also be a part of that story.

Leah: Yeah. 

Angelica: So that's a wrap! Thanks everybody for listening to the Scrap The Manual Podcast. Be sure to check out our blog post for more information, references, and also a link to our prototype. Remember to check out the Netherlands references and also the hidden fifth world within that prototype. If you like what you hear, please subscribe and share! You can find us on Spotify, Apple Podcasts and wherever you get your podcasts.

Leah: If you want to suggest topics, segment ideas, or general feedback, feel free to email us at scrapthemanual@mediamonks.com. If you want to partner with Media.Monks Labs, feel free to reach out to us at that same email address. 

Angelica: Until next time!

Leah: Bye.

Our Labs.Monks provide insight into APAC’s emerging AI, AR, automation, and metaverse technologies–along with a sneak peek into the prototype leveraging an upcoming tech from the region. artificial intelligence AR augmented reality technology emerging technology

For Creatives and AI, It Takes Two to Tango

For Creatives and AI, It Takes Two to Tango

4 min read
Profile picture for user Labs.Monks

Written by
Labs.Monks

For Creatives and AI, It Takes Two to Tango

Chances are, you’ve seen the meme before: “I forced a bot to watch over 1,000 hours of [TV show] and then asked it to write an episode of its own. Here is the first page,” followed by a nonsensical script. These memes are funny and quirky for their surreal and unintelligible output, but in the past couple of years, AI has improved to create some incredible work, like OpenAI’s language model that can write text and answer reading comprehension questions.

AI has picked up a handful of creative talents: making original music in the style of famous artists or turning your selfie into a classical portrait, to name a few. While these experiments are very impressive, they’re often toy examples designed to demonstrate how well (or poorly) an artificial intelligence stacks up to human creativity. They’re fun, but not very practical for day-to-day use by creatives. This led our R&D team, MediaMonks Labs, to consider how tools like these would actually function within a MediaMonks project.

This question fueled two years of experimentation and neural network training for the Labs team, who built a series of machine learning-enhanced music video animations that demonstrate true creative symbiosis between humans and machines, in which a 3D human figure performs a dance developed entirely by (or in collaboration with) artificial intelligence.

The Simulation Series was built out of a desire to let humans take a more active approach to working creatively with AI, controlling the output by either stitching together AI-created dance moves or by shooting and editing the digital performance to their liking. This means you don’t have to be a pro at animation (or choreography) to make an impressive video; simply let the machine render a series of dance clips based on an audio track and edit the output to your liking.

“Once I had the animations I liked, I could put it in Unity and could shoot them from the camera angles that I wanted, or rapidly change the entire art direction,” says Samuel Snider-Held. A Creative Technologist at MediaMonks, he led the development of the machine learning agent. “That was when I felt like all these ideas were coming together, that you can use the machine learning agent to try out a lot of different dances over and over and then have a lot of control over the final output.” Snider-Held says that it takes about an hour for the agent to generate 20 different dances—far outpacing the amount of time that it would take for a human to design and render the same volume.

Snider-Held isn’t an animator, but his tool gives anyone the opportunity to organically create, shoot and edit their own unique video with nothing but a source song and Unity. He jokes when he says: “I spent two years researching the best machine learning approaches geared towards animation. If I spent two years to learn animation instead, would I be at the same level?” It’s tough to say, though Snider-Held and the Labs team have accomplished much over those two years of exhaustive, iterative development—from filling virtual landscapes with AI-designed vegetation to more rudimentary forms of AI-generated dances in pursuit of human-machine collaboration.

Enhancing Creative Intelligence with Artificial Intelligence

Even though the tool fulfills the role of an animator, the AI isn’t meant to replace anyone—rather, it aims to augment creatives’ abilities and enable them to do their work even better, much like how Adobe Creative Cloud eases the creative process of designing and image editing. Creative machines help us think and explore vast creative possibilities in shorter amounts of time.

It’s within this process of developing the nuts and bolts that AI can be most helpful, laying a groundwork that provides creatives a series of options to refine and perfect. “We want to focus on the intermediate step where the neural network isn’t doing the whole thing in one go,” Snider-Held says. “We want the composition and blocking, and then we can stylize it how we want.”

Monk Thoughts The tool’s glitchy aesthetic sells the ‘otherness’ to it. It doesn’t just enhance your productivity, it can enhance the limits of your imagination.
Samuel Snider-Held headshot

It’s easy to see how AI’s ability to generate a high volume of work could help a team take on projects that otherwise didn’t seem feasible at cost and scale—like generating a massive amount of hand-drawn illustrations in a short turnaround. But when it comes to neural network-enhanced creativity, Snider-Held is more excited about exploring an entirely new creative genre that perhaps couldn’t exist without machines.

“It’s like a reverse Turing test,” he says, referencing the famous test by computer scientist Alan Turing in which an interrogator must guess whether their conversation partner is human or machine. “The tool’s glitchy aesthetic sells the ‘otherness’ to it. It doesn’t just enhance your productivity, it can enhance the limits of your imagination. With AI, we can create new aesthetics that you couldn’t create otherwise, and paired with a really experimental client, we can do amazing things.”

Google’s Nsynth Super is a good example of how machine learning can be used to offer something creatively unprecedented: the synthesizer combines source sounds together into entirely new ones that humans have never heard before. Likewise, artificial intelligence tools like automatically rendering an AI-choreographed dance can unlock surreal, new creative possibilities that a traditional director or animator likely wouldn’t have envisioned.

In the spirit of collaboration, it will be interesting to see what humans and machines create together in the near and distant future—and how it will further transform the ways that creative teams will function. But for now, we’ll enjoy seeing humans and their AI collaborators dance virtually in simpatico.

A dancing AI from MediaMonks Labs goes beyond enhancing productivity–it supercharges creative thinking and imagination, too. For Creatives and AI, It Takes Two to Tango A dance-designing AI made by MediaMonks Labs does more than just the robot.
Ai artificial intelligence machine learning ml neural network neural network training creative machines creative AI

When Speed is Key, MediaMonks Labs Enables Swift, Proactive AI Prototyping

When Speed is Key, MediaMonks Labs Enables Swift, Proactive AI Prototyping

4 min read
Profile picture for user Labs.Monks

Written by
Labs.Monks

When Speed is Key, MediaMonks Labs Enables Swift, Proactive AI Prototyping

As the COVID-19 pandemic spreads throughout the world and people retreat into their homes to practice social distancing, ingenuity and the need to digitally transform have become more apparent now than ever. Always looking for ways to jump-start innovation, the MediaMonks Labs team has experimented with ways to speed up the development of machine learning-based solutions from prototype to end product, cutting out unnecessary hours of coding to iterate at speed.

“Mental fortitude and being used to curveballs are skills and ways of working that come to the foreground now,” says Geert Eichhorn, Innovation Director at MediaMonks. “We see those eager to adapt come out on top.” Proactively aiming to solve the challenges faced by brands and their everyday audiences, the team recently experimented with a faster way to build and iterate artificial intelligence-driven products and services.

Fun Experiments Can Lead to Proactive Value

The idea behind one such experiment, the Canteen Counter, may seem silly on the surface: determine when the office canteen is less busy, helping the team find the optimal time to go and grab a seat. But the technology behind it provides some learnings for those who aim to solve challenges quickly with off-the-shelf tools.

Here’s how it works. The Canteen Counter’s camera was pointed at the salad bar, capturing the walkway from the entrance to the dishwashers—the most crowded spot in the canteen. The machine learning model detects people in the frame and keeps a count of how many are there to determine when it’s busy and when it isn’t—much like how business listings on Google Maps predict peak versus off-peak hours.

CC Screen2

Of course, now that the team is working from home, there’s little need to keep an eye on the canteen. But one could imagine a similar tool to determine in real time which spaces are safe for social distancing, measured from afar. Is the local park empty enough for some fresh air and exercise? Is the grocery store packed? Ask the AI before you leave!

“I would like to make something that is helpful to people being affected by COVID-19 next,” says Luis Guajardo, Creative Technologist at MediaMonks. “I think that would be an interesting spinoff of this project.” The sentiment shows how such experiments, when executed at speed, can provide necessary solutions to new problems soon after they arise.

Off-the-Shelf Tools Help Teams Plug In, Play and Apply New Learnings

Our Canteen Counter is powered by Google’s Coral, a board that runs optimized TensorFlow models using an Edge TPU chip. To get the jargon out of the way, it essentially lets you employ machine learning offline—a process that typically connects to a cloud, which is why you need a data connection to interact with most digital assistants. The TPU chip (which stands for tensor processing unit) is built to handle the neural network-trained machine learning directly on the hardware.

This not only allows for faster processing, but also increased privacy because data isn’t shared with anyone. Developers may simply take an existing, off-the-shelf machine learning model to quickly optimize to the hardware and the goals of a project. While the steps behind this process are simpler than training a model of your own, there’s still some expertise required in discovering which model best suits your needs—a point made clear with another tool built by Labs that compares computer vision models and the differences between them.

Monk Thoughts What is a canteen counter today could become a camera that tells you something about your posture tomorrow. Anything goes, and it changes by the day.
Portrait of Geert Eichhorn

What the team really likes about Coral is how flexible it is thanks to the TPU chip, which comes in several different boards and modules to easily plug and play. “That means you could use the Coral Board to build initial product prototypes, test models and peripherals, then move into production using only the TPU modules based on your own product specs and electronics and create a robust hardware AI solution,” says Guajardo.

Quicken the Pace of Development to Stay Ahead of Challenges

For the Labs team, tools like Coral have quickened the pace of experimentation and developing new solutions. “The off-the-shelf ML models combined with the Coral board and some creativity can let you build practical solutions in a matter of days,” says Eichhorn. “If it’s not a viable solution you’ll find out as soon as possible, which prevents you from wasting any valuable time and resources.” Eichhorn compares this process to X (formerly Google X), where ideas are broken down as fast as possible to stress test viability.

“At Labs, we jump on new technologies and apply them in new creative ways to solve problems we didn’t know we had, so any project or platform that has as much flexibility as the Canteen Counter is very much up Labs’ alley,” says Eichhorn. “What is a canteen counter today could become a camera that tells you something about your posture tomorrow. Anything goes, and it changes by the day.” He notes that more is being worked on behind the scenes as the team ponders the trend toward livestreaming, the need for showing solidarity, play and interaction while working from home.

It’s worth reflecting on how dramatically the world has changed since we settled on the idea to keep an eye on our workplace canteen through a fun, machine learning experiment. But Eichhorn cautions that in a rush for much-needed solutions, “innovation” can often begin to feel like a buzzword. “What we do differently is that we can actually build, be practical, execute, and make it work.”

Extraordinary times call for extraordinary solutions.

Focused on solutions that are both useful and practical, the MediaMonks Labs team shares its approach to rapidly prototyping machine learning-based solutions. When Speed is Key, MediaMonks Labs Enables Swift, Proactive AI Prototyping By cutting out unnecessary coding hours, MediaMonks Labs builds solutions at speed.
Machine learning artificial intelligence mediamonks labs prototyping innovation google coral coral board

MM Labs Uncovers the Biases of Image Recognition

MM Labs Uncovers the Biases of Image Recognition

4 min read
Profile picture for user Labs.Monks

Written by
Labs.Monks

MM Labs Uncovers the Biases of Image Recognition

Do you see what I see? The game “I spy” is an excellent exercise in perception, where players take turns guessing an object that someone in the group has noticed. And much like how one player’s focus might be on an object totally unnoticed by another, artificial intelligences can also notice entirely different things in a single photo. Hoping to see through the eyes of AI, MediaMonks Labs developed a tool that pits leading image recognition services against one another to compare what they each see in the same image—try it here.

Image recognition is when an AI is trained to identify or draw conclusions of what an image depicts. Some image recognition software tries to identify everything in a photo, like a phone automatically organizes photos without the user having to tag them manually. Others are more specialized, like facial recognition software trained to recognize not just a face, but perhaps even the person’s identity.

This sort of technology gives your brand eyes, enabling it to react contextually to the environment around the user. Whether it be identifying possible health issues before a doctor’s visit or identifying different plant species, image recognition is a powerful tool that further blurs the boundary between user and machine. “In the market, convenience is important,” says Geert Eichhorn, Innovation Director at MediaMonks. “If it’s easier, people are willing pick up and try. This has the potential to be that simple, because you only need to point your phone and press a button.”

Monk Thoughts With image recognition, your product on the store shelf or in the world can become triggers for compelling experiences.
Portrait of Geert Eichhorn

You could even transform any branded object into a scavenger hunt. “What Pokemon Go did for GPS locations, this can do for any object,” says Eichhorn. “Your product on the store shelf or in the world can become triggers for compelling experiences.”

Uncovering the Bias in AI

For a technology that’s so simple to use, it’s easy to forget the mechanics of image recognition and how it works. Unfortunately, this leads to an unequal experience among users that can have very powerful implications: most facial recognition algorithms still struggle to recognize the faces of black people compared to white ones, for example.

Why does this happen? Image recognition models can only identify what it’s trained to see. How should an AI know the difference between dog breeds if they were never identified to it? Just like how humans draw conclusions based on their experiences, image recognition models will each interpret the same image in different ways based on their data set. The concern around this kind of bias is two-fold.

First, there’s the aforementioned concern that it can provide an unequal experience for users, particularly when it comes to facial recognition. Developers must ensure they power their experience with a model capable of recognizing a diverse audience.

Screen Shot 2019-10-30 at 4.53.04 PM

As we see in the image above, Google is looking for contextual things in the event photo, while Amazon is very sure that there is a person there.

Second, brands and developers must carefully consider which model best supports their use case; an app that provides a dish’s calorie count by snapping a photo won’t be very useful if it can’t differentiate between different types of food. “If we have an idea or our client wants to detect something, we have to look at which technology to use—is one service better at detecting this, or do we make our own?” says Eichhorn.

Seeing Where AI Doesn’t See Eye-to-Eye

Machine learning technology functions within a black box, and it’s anyone’s guess which model is best at detecting what’s in an image. As technologists, our MediaMonks Labs team isn’t content to make assumptions, so they built a tool that offers a glimpse at what several of the major image recognition services see when they view the same image, side-by-side. “The goal for this is discovering bias in image recognition services and to understand them better,” says Eichhorn. “It also shows the potential of what you could achieve, given the amount of data you can extract from an image.”

Here’s how it works. The tool lists out the objects and actions detected by Google Cloud Vision, Amazon Rekognition and Baidu AI, along with each AI’s confidence in what it sees. By toying around with the tool, users may observe differences in what each model responds to—or doesn’t. For example, Google Cloud Vision might focus more on contextual details, like what’s happening in a photo, where Amazon Rekognition is focused more on people and things.

Monk Thoughts With this tool, we want to pull back the curtain to show people how this technology works.
Portrait of Geert Eichhorn

This also showcases some of the variety of things that can be recognized by the software, and each can have exciting creative implications: the color content of a user’s surroundings, for example, might function as a mood trigger. We collaborated DDB and airline Lufthansa to build a Cloud Vision-powered web app, for example, which recommends a travel destination based on the user’s photographed surroundings. For example, a photo of a burger might return a recommendation to try healthier food at one of Bangkok’s floating markets.

The Lufthansa project is interesting to think about in the context of this tool, because expanding it to the Chinese market required switching the image recognition from Cloud Vision to something else, as Google products aren’t utilized in the country. This gave the team the opportunity to look into other services like Baidu and AliYun, prompting them to test each for accuracy and response time. It showcases in very real terms why and how a brand would make use of such a comparison tool.

“Not everyone can be like Google or Apple, who can train their systems based on the volume of photos users upload to their services every day,” says Eichhorn. “With this tool, we want to pull back the curtain to show people how this technology works.” With a better understanding of how machine learning is trained, brands can better envision the innovative new experiences they aim to bring to life with image recognition.

MediaMonks Labs built a tool to better understand image recognition services by uncovering their biases. MM Labs Uncovers the Biases of Image Recognition Just like people, no two artificial intelligences are alike—even when they aim to do the same thing.
artificial intelligence machine learning mediamonks labs AI bias bias in ai image recognition computer vision

Hey Google, Fix My Marriage

Hey Google, Fix My Marriage

5 min read
Profile picture for user mediamonks

Written by
Monks

Hey Google, Fix My Marriage

There’s no denying that Google Assistant is useful for simple, everyday needs that keep users from having to reach for a phone. But what if it could provide more value-added experiences, becoming more intuitive and human-like in the process? Are we that far away from the kind of assistant depicted in Spike Jonze’s Her?

One of the greatest inhibitors of adoption of voice is that natural language isn’t ubiquitous, and functionality is typically limited to quick shortcuts. According to Forrester, 46% of adults currently use smart speakers to control their home, and 52% use them to stream audio. Neither of these use cases are necessities, nor are they very unique. Looking beyond shortcuts and entertainment value, we sought to experiment with Google Assistant to highlight a real-world utility that offers more human-like interactions. Think less in terms of “Hey Google, turn on the kitchen lights,” and instead something more like “Hey Google, fix my marriage.”

That’s not a joke; by providing a shoulder to cry on or a mediator who can resolve conflicts while keeping a level head, our internal R&D team MediaMonks Labs wanted to push the limits of Google Assistant to see what kind of experiences it could provide to better users’ lives and interpersonal relationships.

Who would have thought that a better quality of conversation with a machine might help you better speak to other humans? “Most of the stuff on the Assistant is very functional,” says Sander van der Vegte. “It’s almost like an audible button, or something for entertainment. The marriage counselor is neither, but could be implemented as a step before you look for an actual counselor.”

Why Google Assistant?

Google Assistant is an exciting platform for voice thanks to its ability to be called up anytime, anywhere through its close integration with mobile. “Google Assistant is very much an assistant, available to help at any moment of time,” says Joe Mango, Creative Technologist at MediaMonks.

GOOGLEVID2

But still, the team felt the platform could go even further in providing experiences that are unique to the voice interface. “Right now, considering the briefings we get, most of the stuff on the assistant is very functional,” says Sander van der Vegte, Head of MediaMonks Labs. “It’s designed to be a shortcut to do something on your phone, like an audible button. This marriage counselor has a completely different function to it.”

The Labs team took note when Amazon challenged developers to design Alexa skills that could hold meaningful conversations with users for 20 minutes, through a program called the Alexa Prize. It offered an excellent opportunity to turn the tables and challenge the Google Assistant platform to see how well it could sustain a social conversation with users, resulting in a unique action that requires the assistant to use active listening and an empathetic approach to help two users see eye to eye.

Breaking the Conversation Mold

As you might imagine, offering this kind of experience required a bit of hacking. To listen and respond to two different people in a conversation, the assistant had to free itself from the typical, transactional exchange that voice assistant dialogue models are designed for. “We had to break all the rules,” says Mango—but all’s fair in love and war, at least for a virtual assistant.

A big example of this is a novel use of the fallback intent. By design, the fallback intent is a response the assistant provides to users when they make a query that isn’t programmed to a response—usually something as simple as asking the user to try to state their request in another way.

But the marriage counselor uses this step to pass the query along to sentiment analysis with Google Cloud API. There, the statement is scored on how positive or negative it is. Tying this score to a scan of the conversation history for applicable details, the assistant can pull a personalized response. This allows both users to speak freely through an open-ended discussion without being interrupted by errors.

Screen Shot 2019-09-18 at 9.55.26 AM

What does such an interaction look like? When a couple tested the marriage counselor action, one user mentioned his relationship with his brothers: some of them were close, but the user felt that he was becoming distant from one of them. In response, the assistant chimed in to remind the user that it was good that he had a series of close relationships to confide in. Its ability to provide a healthy perspective in response to a one-off comment—a comment not even about the user’s romantic relationship, but still relevant to his emotional well-being—was surprising.

The inventive use of the platform allows the assistant to better respond to a user’s perceived emotional state. Google is particularly interesting to experiment with thanks to its advanced voice recognition models; it built the sentiment analysis framework used within the marriage counseling action, and Google’s announcement of Project Euphonia earlier this year, which makes voice recognition easier for those with speech impairments, was a welcome sight for those seeking to make digital experiences more inclusive. “At MediaMonks, we’re finding ways to creatively execute on these frameworks and push them forward,” said Mango.

Giving Digital Assistants the Human Touch

But the marriage counselor action is more focused on listening rather than speaking, allowing two users to hash it out and doling out advice or prompts when needed. A big part of this process is emotional intelligence. Humans know that the same sentence can have multiple meanings depending on the tone used—for example, sarcasm. Another example might be the statement “Only you would think of that,” which could be viewed as patronizing or a compliment given the tone and context.

Monk Thoughts At MediaMonks, we’re finding ways to creatively execute on these frameworks and push them forward.

While the assistant currently can’t understand tone of voice, a stopgap solution was to enable it to parse meaning with through vocabulary and conversational context—helping the assistant understand that it’s not just what you say, but how you say it. This is something that humans pick up on naturally, but Mango drew on linguistics to provide the illusion of emotional intelligence.

“If the assistant moves in this direction, you’ll get a far more valuable user experience,” says van der Vegte. One example of how emotional intelligence can better support the user outside of a counseling context would be if the user asks for directions somewhere in a way that indicates they’re stressed. Realizing that a stressed user who’s in a hurry probably doesn’t want to spend time wrangling with route options, the action could make the choice to provide the fastest route.

Next Stop: More Proactive, Responsive Assistants

“There’s always improvements to be made,” says Mango, who recognizes two ways that Google Assistant could provide even more lifelike and dynamic social conversations. First, he would like to see the assistant support emotion detection through more ways than examining vocabulary. Second, he’s like to make the conversation flow even more responsive and dynamic.

Sentiment

“Right now the conversation is very linear in its series of questions,” he says. But in a best-case scenario, the assistant could provide alternative paths based on user response, customizing each conversation to respond to different underlying issues that the marriage counselor might identify is affecting the relationship.

But for now, the team is excited to tinker and push the envelope on what platforms can achieve, inspired by a sense of technical curiosity and the types of experiences they’d like to see in the world. “It speaks a lot to the mission of what we do at Labs,” said Mango. “We always want to push the limitation of the frameworks out there to provide for new experiences with added value.”

As assistants become better equipped to listen and respond with emotional intelligence, their capabilities will expand to provide better and more engaging user experiences. In a best-case scenario, an assistant might identify user sentiment and use that knowledge to recommend a relevant service, like prompting a tired-sounding user to take a rest. Such an advancement would allow brands to forge a deeper connection to users by providing the right service at the right place in time. While Westworld-level AI is still far off in the distance, we’ll continue chatting and tinkering away at teaching our own bots the fine art of conversation—and we can’t wait to see what they’ll say next.

Voice assistants have been life changing for some users, but they can go to even further lengths in providing rich, valuable conversational experiences. The next big leap in conversational AI may be emotional intelligence, and MediaMonks Labs set out to achieve just that. Hey Google, Fix My Marriage Checking the weather or a sports score is nice, but can a smart speaker save your marriage? We’re working on it.
Google Assistant Alexa skills Google actions sentiment analysis emotional intelligence AI artificial intelligence conversational interface

Transitioning Voice Bots from ‘Book Smart’ to ‘Street Smart’

Transitioning Voice Bots from ‘Book Smart’ to ‘Street Smart’

5 min read
Profile picture for user Labs.Monks

Written by
Labs.Monks

Interest has grown significantly in voice platforms over the years, and while they have proved life-changing for the visually impaired or those with limited mobility, for many of us the technology’s primary convenience is in saving us the effort of reaching for a phone. Yet we anticipate a future in which voice platforms can provide more natural experiences to users beyond calling up quick bits of information. This ambition has prompted us to look for new ways to provide added value to conversations, making smart use of the tools readily available by organizations leading the charge in consumer-facing voice assistant platforms.

The primary challenge in unlocking truly human-like exchanges with virtual assistants is that their dialogue models are best fit for transactional exchanges: you say something, the assistant responds with a prompt for another response, and so on. But we’ve found that brands that are keen on taking advantage of the platform are looking for a more than a rigid experience. “There are plenty of requests from clients about assistants, who are under the impression that the user can say whatever,” says Sander van der Vegte, Head of MediaMonks Labs. “What you expect from a human assistant is to speak open-ended and get a response, so it’s natural to assume a digital assistant will react similarly.” But this conversation structure goes against the grain for how these platforms typically work, which means we must find new approaches that better accommodate the experiences that brands seek to provide their users.

Giving Digital Assistants the Human Touch

One way to make conversations with voice assistants more human-like is to empower them with a distinctly human trait: emotional intelligence. MediaMonks Labs is experimenting with this by developing a Google Assistant action that serves as a marriage counselor that uses sentiment analysis to draw out the intent and meaning behind user statements.

Monk Thoughts This is the first step down an ongoing path for deeper, richer conversation.

“If the assistant moves in this direction, you’ll get a far more valuable user experience,” says van der Vegte. One example of how emotional intelligence can better support the user outside of a counseling context would be if the user asks for directions somewhere in a way that indicates they’re stressed. Realizing that a stressed user who’s in a hurry probably doesn’t want to spend time wrangling with route options, the action could make the choice to provide the fastest route.

As assistants become better equipped to listen and respond with emotional intelligence, their capabilities will expand to provide better and more engaging user experiences. In a best-case scenario, an assistant might identify user sentiment and use that knowledge to recommend a relevant service, like prompting a tired-sounding user to take a rest. Such an advancement would allow brands to forge a deeper connection to users by providing the right service at the right place in time. While Westworld-level AI is still far off in the distance, we’ll continue chatting and tinkering away at teaching our own bots the fine art of conversation—and we can’t wait to see what they’ll say next.

Monk Thoughts We can learn to speak more effectively to an AI, just like how AI learns to speak to us.

To better understand what this looks like, consider how two humans effectively resolve a conflict. Rather than accuse someone of acting a certain way, for example, it’s preferable to use “I messages” about how others’ actions make you feel, so the other party doesn’t feel attacked. So whether you begin a statement with “you” (accusatory) or “I” (garnering empathy) can have a profound impact on how others invested in a conflict will respond. Likewise, our marriage counseling action analyzes the vocabulary and inflection in two users’ statements to dole out relationship advice to them. Responses are focused not just on what they say but how they say it.

“We can learn to speak more effectively to an AI, just like how AI learns to speak to us,” says Joe Mango, Creative Technologist at MediaMonks. According to him, users have been conditioned to speak to bots in, well, robotic ways through their experience with them. “When we had someone from our team test the action by simply speaking to it, he wasn’t sure what to say at first.”

Sentiment

Speaking a New Language

The action takes a large departure from the standard conversational setup with a voice bot. Rather than have a back-and-forth chat with a single user, the action listens attentively as two users speak to one another. Allowing Google Assistant to pull off such a feat gets at the heart of why so few actions provide such rich conversational experiences: the inherent limitations of the natural language processing platforms that power them. For example, the Google Assistant breaks conversation down into a “you say this, I say that”-style structure that limits the amount of time it opens the microphone to listen to a user response.

Monk Thoughts We always want to push the limitation of the frameworks to provide new experiences and added value.

Conventional wisdom surrounding conversational design shies away from “wide-focus” questions, encouraging developers to be as pointed and specific as possible so users can answer in just a word or two. But we think breaking out of this structure is not only feasible, but capable of providing the next big step in richer, more genuine interactions between people and brands. “It speaks a lot to the mission of what we do at Labs,” said Mango. “We always want to push the limitation of the frameworks out there to provide for new experiences with added value.”

What does such an interaction look like? When a couple tested the marriage counselor action, one user mentioned his relationship with his brothers: some of them were close, but the user felt that he was becoming distant from one of them. In response, the assistant chimed in to remind the user that it was good that he had a series of close relationships to confide in. Its ability to provide a healthy perspective in response to a one-off comment—a comment not even about the user’s romantic relationship, but still relevant to his emotional well-being—was surprising.

Screen Shot 2019-01-31 at 10.23.54 AM
Screen Shot 2019-01-31 at 10.35.13 AM

Next Stop: More Proactive, Responsive Assistants

While the action is effective, “It’s just the first step down an ongoing path to support more dynamic sentence structures and deeper, richer conversation,” says Mango. While the focus right now is on inflection and vocabulary, future iterations of the action could draw on users’ tone of voice to glean their sentiment even more accurately. From there, findings from this experiment aid in providing other voice apps a level of emotional intelligence that helps organizations engage with their audience in even more human-like ways.

Voice assistants have been life changing for some users, but they can go to even further lengths in providing rich, valuable conversational experiences. The next big leap in conversational AI may be emotional intelligence. Transitioning Voice Bots from ‘Book Smart’ to ‘Street Smart’ Checking the weather or a sports score is nice, but can a smart speaker save your marriage? We’re working on it.
Google Assistant Alexa skills Google actions sentiment analysis emotional intelligence AI artificial intelligence conversational interface

Choose your language

Choose your language

The website has been translated to English with the help of Humans and AI

Dismiss