Search What You See: The Tech Behind The Magic | Made by Google Podcast S9E4

Search What You See: The Tech Behind The Magic | Made by Google Podcast S9E4

Google

0:00 Welcome to the Made by Google Podcast,

0:03 where we meet the people who work on the Google products you love.

0:06 Here's your host, Rachid Finge- Circle.

0:09 to Search is getting a huge upgrade,

0:10 making it even more powerful to find out what

0:13 you're looking at on your Pixel 10 or Galaxy S26.

0:17 And if you're into fashion, it has a mind blowing trick up its sleeve

0:21 that will help you find a beautiful new look.

0:24 Let's learn more today from Director of Product Management, Harsh Kharbanda.

0:29 This is the Made By Google Podcast,- Harsh.

0:32 Welcome to the Made By Google Podcast.

0:34 Uh, we're talking circle to search today.

0:36 Do you remember the very, very,

0:38 very first time you came across Circle to Search?

0:41 So, I've worked on Lens since Google Lens,

0:43 since the beginning of Google Lens, um, since 2018.

0:46 And, um, at some point during as Lens,

0:50 as Lens was growing up, we, like, our main focus was the camera.

0:54 And you know, like how users can take a picture

0:56 of things in front of you and then get,

0:58 get question, uh, uh, their questions answered.

1:00 And at some point we realized a lot of the value is, uh,

1:04 for people to be able to search things that they see on their computer,

1:07 on their phone screens.

1:09 Uh, and so because what we started notice

1:11 was users take a lot of picture screenshots,

1:14 um, and then they just upload that to Google Lens.

1:18 Um, and so, uh, a part of our team started working with Android

1:21 and trying to figure out how to make this whole slo a lot, a lot more seamless.

1:26 And that's where the Circle Gesture came around.

1:28 And the first time I used it, it just felt so intuitive, um,

1:32 that, that I was like, oh yeah, I'm going to use this like 10 times a day.

1:36 Uh, 'cause there's so many different questions, uh,

1:38 on my phone screen that I come across every single day.

1:41 And then, yeah, from then on I was just hooked.

1:43 So as the Lens and the Circle to Search products merged over time,

1:47 I ended up owning more and more Circle to Search, uh, product as well.

1:49 And yeah.

1:50 And here we are.

1:52 So- I guess in order to understand where we are today,

1:54 it might be useful to back up a little.

1:56 Of course, the search engine started with typing in queries in the search box.

2:00 Then at some point we got voice search,

2:02 and then we got something as you mentioned already called Google Lens.

2:06 So why did we come up with Google Lens back, uh, a few years ago, I guess?

2:11 Uh, great question.

2:12 So the concept of a visual search has been around for a very long time.

2:16 If you remember, I think Google Goggles was something that we- Oh, right.

2:20 Google worked on,- Goggles, worked on in 2012 or 2014.

2:22 I, I forget exactly when, but Google invested in this, this concept

2:26 of being able to search for things visually,

2:28 very long time, uh, very early on, but the technology was just not there.

2:34 Um, you know, early on Google Lens could, could only do QR codes,

2:38 maybe some objects, um, and some translation and so forth.

2:42 Um, and so the, the key thing with Lens was,

2:45 uh, you know, like we knew that there is,

2:48 there is demand because we see that there's a lot of questions that are very

2:53 hard to articulate just verbally and for users

2:56 to actually express via text or voice.

2:58 Like how do you describe a very unique

3:01 dress that you come across on social media?

3:03 There's so many different words.

3:05 And even if you use those words,

3:07 you're still not capturing the essence of that dress.

3:10 Um, or like what people use Lens a lot for like plants.

3:13 How do you describe a plant that is in your house that somebody gifted to you

3:17 and you don't know the name of, and it's dying in a very specific way.

3:21 And it has these like spots on it, how, like, it's just really,

3:25 really hard and you can give clothes where it'll take you a long time and then,

3:29 you know, you lose a bunch of fidelity in doing that.

3:32 And so the impetus of like, Hey,

3:34 users have so many questions that are hard to describe,

3:36 was something that Google saw very early on.

3:40 So we had Lens Visual Search, as you call it as well.

3:43 And then at some point came circle to search.

3:46 So for, for people who have never used Circle to search,

3:49 how is that different from just using the camera to search something?

3:53 When we started Lens,

3:55 a lot of the focus was on things that you see in front of you, right?

3:59 Um, but what we quickly realized was,

4:02 you are in stimulus in, in your daily life is not that much.

4:06 Uh, and so you're seeing your same plan, your same dog,

4:09 your, you know, same office location and, and work desk and so forth.

4:12 And so you don't have that many opportunities to ask new questions.

4:16 And phones have gotten better and better.

4:18 Pixel is an amazing product, and people just spend a lot,

4:21 many number of hours on social media

4:24 and on different parts of, of, of their phone.

4:26 And as they scroll through and as they browse their phones,

4:30 they come across the stimulus where they have these questions.

4:33 And so the whole, the goal was how to bridge the gap between,

4:36 okay, we have visual search,

4:38 we're really focused on things in front of you, and it doesn't really,

4:41 you know, like it's not a thing that people do all the time.

4:44 How do we bring it closer to the device?

4:45 How do we bring it where the user's questions are?

4:48 And that's what led to Search.

4:51 And for those who never had the chance to use Circle to Search,

4:54 can you explain to me as a user, like how, how do I use it and, and what,

4:59 what is maybe your favorite example of a situation where it's super useful?

5:04 Uh, sure.

5:05 So, um, it's very simple, uh, on any, on your new Pixel device, uh,

5:10 you just have to, uh, long press the nav handle, um, on any app that you're on.

5:15 That's that bar at the bottom, right?

5:16 Correct.

5:17 Yes.

5:17 Uh, the bar at the bottom.

5:18 Uh, and that just takes, uh,

5:20 the freezes your screen, and then you can tap anywhere.

5:24 Or the best part is you can draw a circle

5:26 around exactly what you want, and then you get, uh, you know, like, uh,

5:30 we will show you and most likely an AI answer of what you're looking at.

5:34 And then you can ask questions like very specific questions about the thing,

5:37 uh, things that, that you, that you're looking at as well.

5:40 Um, one of my favorite examples, so, uh,

5:43 I get a lot of spam from my mom on WhatsApp,

5:48 uh, like, she sends me a ton of, uh,

5:51 like messages that are definitely fake, at least in my opinion.

5:55 Uh, or like videos of like, I'm like, this, this cannot be true.

5:59 Um, and I use Circle to Search a lot to verify a lot of this information.

6:03 So all I do is just long press, uh, you know, the, the nav handle,

6:06 and then I circle and it just tells me, Hey, this thing is not true.

6:10 Here's the reasons why.

6:11 And it actually searches the web figures out like, what,

6:14 what's, what's, uh, actually true, what's not where the nuance is.

6:18 And often I would screenshot that and send it back to her.

6:21 Although, you know, that has gotten me in trouble many times.

6:24 But, you know, that's one of my favorite personal use cases of Circle to Search.

6:28 And I guess what I use it a lot for, if, if there's something on my screen, uh,

6:32 in a, in, in a language that I don't,

6:35 that I cannot read, I can also circle text Right.

6:38 And get a translation.

6:39 Yeah,- Exactly.

6:41 And that, that happens to me too,

6:41 like in Family Chats sometimes somebody would forward a message

6:44 that's like in a, in a different Indian Language,

6:46 uh, dialect, uh, that I don't speak,

6:49 or it's, I, I, I might even speak, but it's hard for me to read,

6:52 and I would just circle it and it can read it out to me, it contrast it for me.

6:55 Uh, so it's, it's a pretty nifty, uh,

6:57 feature that I, a lot of our users use a lot.

7:01 Harsh.

7:01 I'm curious, like when did, because that's of course, you know, we're,

7:04 we're going to talk about the new

7:05 update for Circle To Search that recently launched.

7:08 And I guess at some point you probably had the insight,

7:11 and I'm not sure if you expected it,

7:13 that people are using Circle to Search in sort of a fashion sense as well.

7:18 Yeah, actually.

7:19 So, uh, this was very early on in Circle to Search.

7:22 We realized that this would be, this would be a thing.

7:24 So one thing we learned from Google Lens was,

7:28 uh, especially during COVID users, uh,

7:30 spent a lot of time on their phones and a lot of time on social media,

7:35 and they would come across, uh, videos or, you know,

7:39 like, uh, social media posts of influencers,

7:41 and they be like, oh, I love that jacket,

7:44 but obviously I'm not gonna buy a $5,000 jacket.

7:46 And so they would take screenshots and then upload

7:49 it and bring it to Google Lens and upload it,

7:51 uh, to Google Lens to find something similar

7:53 that is in their price range and so forth.

7:55 Um, and so with Circular Search,

7:57 we knew very early on that if we reduce the friction of, you know,

8:01 the user not having to take screenshot and then, you know,

8:04 closing the app, then opening Google Lens and uploading the screenshot,

8:08 if they can just, you know,

8:09 on the screen without leaving Instagram or TikTok or whatever you're watching,

8:13 and just, you know, ask the question right then and there,

8:16 it would actually lead to growth.

8:17 And so we did see this very early on.

8:20 Um, you know, users as they were like when we launched Circular Search,

8:23 they, they used it very naturally for shopping.

8:26 In fact, younger users use circular research for shopping a lot more,

8:30 um, because they're all,

8:32 all obviously budget conscious and, and they have a sense

8:35 of style and aesthetic that they want to like recreate.

8:38 Um, and so, uh, younger users, female users is very,

8:41 like this, this is a population that ends up using shop,

8:44 like visual shopping using Circle to Search a lot.

8:48 And, um, what we started to see is a lot of times they're not actually

8:53 circling or wanting a single jacket or like

8:57 a single product that they're looking at, right?

8:59 Um, they actually wanted the whole vibe, the whole feel of the outfit.

9:03 Um, an example is like, oh, I saw Taylor Swift,

9:06 uh, in this like, awesome look, uh, that is going viral.

9:10 Uh, and, uh, it's like she posted her Instagram,

9:13 or I saw through her Instagram account,

9:15 and now I want to like, find every part of that look and of course,

9:18 recreate that look, but in my budget.

9:20 Um, and so Circle to Search didn't really work well for that.

9:23 It worked really well for single objects, and you could circle one by one,

9:26 like the jacket, the top, the jeans, the shoes, the, the bag.

9:30 And some of these influencers have sunglasses.

9:32 So there's like, you know, five- A lot to circle, right?

9:35 Yeah.

9:35 Right.

9:36 Uh, and so, um, and so now with this update,

9:39 what we enabled was the user to just

9:41 circle the whole thing and then find the look.

9:45 And with the late, the, with Gemini 3 and all the latest, uh,

9:49 model updates that we've made,

9:51 we are able to really look at the image in its whole, uh,

9:55 and break it down and think through what are

9:57 the different parts of the image that are really interesting,

9:59 uh, and break it down, uh, uh,

10:01 for the user of all the different parts of the image.

10:04 And then the best part,

10:05 as we do the same visual search for each part of the image,

10:08 so we find the sunglasses, the jacket, the jeans, et cetera,

10:12 uh, using visual search, and then we find you the exact product,

10:16 if possible, and many, many similar products as well,

10:20 um, uh, for you to like, be able to, uh,

10:22 you know, browse and, and, and find something that's

10:24 in your range and really recreate the whole look.

10:27 And then the cherry on top, once you find the product that you like,

10:30 you can click on it and you will see an option to try that thing on you.

10:34 So when you, when you click the try on new option, you will see the jacket, uh,

10:38 that you found that is maybe in your budget, on you,

10:41 on your on and on, what it looks like on you.

10:44 And so that whole like, you know,

10:46 end to end journey or something that when we tested with users,

10:49 they really, really loved it.

10:50 Like, oh my God, Taylor Swift was wearing that, and I,

10:53 I found something for like less than

10:55 a hundred bucks for that, and it looks great.

10:57 I'm gonna buy that.

10:58 Right?

10:58 Um, and, and it really delighted users.

11:01 That's amazing.

11:01 Now, if you back up a little bit, you mentioned,

11:03 so Circle to Search can now, uh, detect multiple objects.

11:07 Yep.

11:07 Uh, and we've been speaking about fashion,

11:09 but what other scenarios are you thinking about where it

11:12 might actually be useful to detect multiple things in one image?

11:15 Yeah, yeah.

11:16 And get a, a, a result from search?

11:18 Yeah.

11:18 There's, there's many, uh, so like, uh,

11:22 one obvious one related to products, uh, is one,

11:25 one the PMs who, uh, one of the PMs, uh, in the team who works on this, uh,

11:29 came up with, uh, she's really into skincare and, you know, she came across,

11:34 uh, like this, like skincare routine on Instagram,

11:36 which had like 14 different products.

11:38 And it literally lists out 14 different,

11:40 like, or images of 14 different products.

11:42 And so, you know, she basically just circled it and it's like, Hey,

11:45 can you find me all the products and give me reviews for everything?

11:48 And like, uh, you know, like rank it by price and it's able to search

11:53 for every single thing and then just do that for you.

11:56 Uh, another one that, uh, you know, uh,

11:58 I came across, uh, was like the, in, I was,

12:01 I was on social media and I came across the setup of plants, um,

12:04 and I was like, oh, these plants look great,

12:06 but I don't know what the names are.

12:07 And they'll, you know, uh, like I can grow in them in my house.

12:12 So I just circle it and ask for like, Hey,

12:13 can you name all the plants their growing conditions, what, what it takes?

12:17 Will they thrive in these conditions, et cetera.

12:19 I was able to search for everything, uh, for, for those as well.

12:22 Um, another one was like, uh, I saw this post,

12:25 uh, where like there were a group of like five actors, uh, holding their, uh,

12:29 awards at a, I think it was Golden Globe or one of those awards ceremonies.

12:33 Mm-hmm.

12:34 I was like, I know a couple of them, but I don't know the others,

12:36 and I don't know what they won the awards for.

12:38 And so I just circled all of them and I'm like, Hey,

12:40 can you just tell me in a, in a nice table what,

12:43 what they, who they are and what they won these awards for, and like,

12:47 what should I watch a movie?

12:48 And then it just like constructed a great, uh,

12:51 result for, uh, result for me there as well.

12:53 So lots of different use cases where the user really is asking

12:57 about the whole thing and not just a part of the thing.

13:00 Uh, and now, uh, we are able to do that for users, um,

13:04 but like find the, finding the look is

13:06 one of the most canonical journeys that like,

13:08 kind of gets to, you know, like it really makes the, uh,

13:12 people feel, aha, I get get it,

13:14 but then they end up using it for many different things,- You know,

13:17 Harsh, what's better than talking about the try on tool,

13:20 I guess is maybe showing it to us.

13:21 How about that?

13:23 Yeah.

13:23 Let me just quickly record my screen, uh, so I can show you guys.

13:28 Um, but let's, let's take this example.

13:31 Uh, it's like a example I came across on social media.

13:35 It's a golf look.

13:36 It's, it's a, it's, it's a look

13:37 that I wouldn't completely ever conceive of, like getting,

13:40 but there are parts of it that are very interesting to me.

13:43 So I will, I, so all I need to do is invoke circle to search, which I just did.

13:47 And then, uh, I circle the whole look, and when I circle the whole look,

13:51 I get this a I overview response that allows me to find the look.

13:55 And when I tap on find the look, um, I'm,

13:59 as you can see now, it's actually able to deconstruct that entire look.

14:03 So look at the shirt, look at the shots,

14:05 look at the, uh, you know, uh, the shirt.

14:09 And so now I have, okay, this is what the cap is,

14:12 this is what the shirt is and so forth,

14:14 and I can click on and it found the exact shirt so I can open the shirt,

14:19 um, you know, in, in the viewer and see it closely.

14:22 Um, and then what I'm able to do is, uh, I'm able to, uh, try it on as well.

14:27 So let me take, uh, an example here.

14:30 And now I see a try it on button and when I tap on, try it on, uh,

14:34 it is able to instantly put that shirt on me.

14:36 Uh, and so probably not the thing that I want to wear, uh,

14:40 but at least tells me, uh, you know, like not something for me.

14:44 Um, so that's like the whole journey of like, Hey,

14:46 I found this look, uh, online looks interesting, uh, let me search for it.

14:51 And then, you know, you search for it in two taps,

14:53 we found you something very similar and now you

14:55 try it on and you're like, uh, probably not.

14:57 And then you can move on or like buy- It, you know?

15:01 I'm so curious what it was like to build this feature and then see it progress,

15:05 because of course you need to do a lot of testing.

15:07 Can you tell me a little bit how that works?

15:09 I mean, I presume you've done dozens and dozens and dozens of tryouts,

15:13 uh, while building the product,

15:15 but probably you need more than just the people on the team who are testing it.

15:19 Uh, yeah, like I think the, so, so to, to be able to like do,

15:24 like, find the look, well, uh, there's like a couple of things.

15:27 So, uh, first there's like,

15:30 we need to get a very diverse set of images that have

15:35 all the different types of looks that people might wanna search for, right?

15:40 So, uh, you know, like female influencers, male influencers, younger,

15:44 older influencers wearing different types of outfits,

15:47 jackets, skirts, dress, and so books.

15:50 And so first we need to like just get a very

15:52 broad set of like all the different images and then, uh,

15:55 we have to like build a model to really,

15:58 and make sure that all the different objects are like,

16:01 you know, parts of the look are being deconstructed properly.

16:05 So, uh, early on we saw like, you know, the model will just not,

16:09 won't do a good job act actually searching shoes because shoes

16:12 are generally a very small part of, uh, the whole look.

16:15 I see.

16:15 Um, and so we had to really tune it and say like,

16:18 Hey, there's shoes all there too.

16:19 Like, you have to look at the shoes or handbags.

16:21 They wouldn't, wouldn't pick up handbags or sunglasses.

16:22 They would pick up 'cause there's a very prominent,

16:24 prominent, but it won't pick up these other things.

16:26 And so, uh, that, that was like the second part of like,

16:29 can, can we make sure that it's actually deconstructing that look reliably?

16:34 And then the hardest part, uh, is actually finding, uh, you know,

16:38 visual like basically the results via visual search that are very,

16:42 very similar, you know,

16:44 because what users expect is that exact product or the exact,

16:47 the very similar product.

16:49 And doing that is very hard, especially, um,

16:51 consider a look where you have a shirt and a jacket and a and and you know,

16:56 like sunglasses and, and skirt and so forth.

16:58 And there shirt is partially occluded by the jacket, like we can't even see it.

17:02 And so we get very few visual

17:04 cues to actually re retrieve similar looking shirts.

17:08 And so we really have to do a good

17:10 job of deconstructing that look and finding the, the shirt,

17:13 uh, and then like retrieving other visually similar shirts.

17:16 And then even when we do retrieve visually similar products,

17:21 then users want it to be in their locale that's in stock, that's it.

17:26 That, that, that they can quickly browse prices for, uh,

17:29 from a, from a retailer and merchant that they trust.

17:31 Um, and so there's a bunch of ranking

17:33 and quality problems on top of that to make sure

17:35 that all of these like line like pages

17:37 that we are showing to users are, are high quality.

17:40 And then, so that was the last piece of the puzzle.

17:43 And so like, it took us really breaking down

17:45 the problem into all these different pieces and nailing each

17:47 of ev each and every one of them

17:49 to, to get to the point where the product feels good.

17:52 By the way, if, if someone who is listening

17:54 isn't as much into fashion but is into interior design.

17:58 Yeah, I noticed that the updated circle

18:00 to search is also really useful for that.

18:02 Yeah,- For sure.

18:03 The exact same logic applies to interior design.

18:05 So you come across, you know, like, uh,

18:08 a living room setup that you really love, uh,

18:10 you love the couch, you love, uh, you know,

18:12 the coffee table, uh, the accent chair and so forth.

18:15 Now you just have a circle and say, find the look.

18:17 Now again, we like bake down each of those different parts

18:19 of the living room and search for you something very visually similar,

18:23 but then again, like something that's in stock,

18:26 it near you from a retailer that you trust.

18:29 Um, so you can actually go and, you know,

18:31 actually look at it or consider buying it- Harsh.

18:34 What would be your top tip for anyone interested

18:36 now in circle to search to, to try it?

18:38 Like what's one thing they definitely should

18:40 do with the updated circle to search,-

18:43 Push the product on the kind of things you want to use it for.

18:46 Uh, we, when we started it was really, you know, like, oh,

18:50 you can search parts of the image or parts of something that you're looking at.

18:53 But more and more where we are going is, uh, it's not about a single thing,

18:58 it's actually about the full context of your journey.

19:01 Uh, so this update we are starting to get into, okay,

19:04 you can, uh, ask a question about the full image,

19:07 but then soon enough we are also working on things where we can, you can,

19:10 we allow users to ask a question about the full content that they're looking at.

19:15 So with your permission, you can have us, uh, look at the full PDF,

19:18 let's say if you are on a PDF or the full webpage that you are

19:21 on, or the full video that you're looking

19:23 at, and we can really search through that entire thing.

19:25 So push the product, give us feedback,

19:27 and we continue to strive to make sure that it works best,

19:30 uh, for all your needs.

19:32 Harsh.

19:32 Thank you so much for telling us about the updated circle

19:34 to search now available on select devices like our Pixel 10 series.

19:38 Um, go and try it out.

19:40 Enjoy it and thank you so much and please come back next time.

19:43 Great, thank you Rachid.

19:45 Thank you for listening to the Made by Google podcast.

19:48 Don't miss out on new episodes.

19:50 Subscribe now wherever you get your podcasts to be the first to listen.

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