00:00 To see is to believe.
00:02 How many times have we heard that?
00:04 We're always looking for visual proof that something exists.
00:07 And once we find that proof, we jump ahead and believe it, no matter what it is.
00:11 So I have a question for you.
00:13 Which one of these images do you think is real?
00:16 This image of a Zomato delivery person dancing in the rain?
00:19 Or this image of Barack Obama in a hat?
00:24 Whichever one you guessed, you'd be wrong.
00:29 Neither one of these is real.
00:31 Both of them are generated by artificial intelligence.
00:34 Which begs the question, can we believe everything we see?
00:38 Whether we like it or not, artificial intelligence has become a part of our daily lives.
00:52 Every time we use a Snapchat filter to add cat ears to our face,
00:55 every time we use Google Maps to navigate to our destination,
00:58 and every time we speak to Customer Care because of a defective product,
01:01 we're interacting with artificial intelligence.
01:03 What's relatively new is generative AI.
01:06 Most of us experienced generative AI for the first time when we tried out ChatGPT.
01:11 ChatGPT and other AI chatbots can simulate human-like dialogue.
01:15 From preparing legal briefs to composing college essays,
01:18 these can generate any text you want them to.
01:21 And it's not just text.
01:22 There are generative AI models that can create images, video, and even music.
01:26 These are being tweaked and enhanced as we speak.
01:29 The appeal of generative AI is in the simplicity of the interface.
01:32 Almost anyone can use it.
01:34 I've never been very great at art.
01:37 I don't think I have the ability to create something visually appealing
01:40 with just a canvas, some material, and my hands.
01:43 But I'm going to give myself 10 minutes to draw something.
01:46 And that something is written inside this piece of paper.
01:52 [Drawing]
01:54 I'm very quickly going to look up images of the Eiffel Tower on my phone.
02:04 I know what it looks like, but...
02:06 I'd like some reference.
02:09 [Drawing]
02:12 [Music]
02:40 We've reached a point in the evolution of generative AI
02:43 where my abysmal drawing skills will no longer affect my ability to express myself visually.
02:47 And this is how it works.
02:49 All I need to do is type a prompt here.
02:53 A prompt is the text you give the AI model,
02:56 describing the image you want it to generate.
02:58 Wow.
03:06 [Drawing]
03:08 Here it is.
03:14 An image that is better than what I've drawn,
03:16 and in much, much lesser time too.
03:19 The more detailed the prompt is, the better.
03:22 I can also try and change the aspect ratio
03:25 and the type of content.
03:32 Here's a photorealistic image of the prompt that was given to me.
03:36 I can also change the lighting.
03:41 So, the possibilities are endless.
03:44 In fact, there's a whole field named prompt engineering,
03:48 in which people can train and learn how to describe an idea
03:51 in such a way that the AI model can understand it
03:54 and generate an acceptable image.
03:56 So, how is the AI model doing this?
03:58 Am I just that good at describing an image?
04:00 You just saw that the more detail my prompts got,
04:03 the better the image turned out.
04:05 [Mumbling]
04:13 [Mumbling]
04:23 [Mumbling]
04:25 But that's not all.
04:32 The AI model actually learned to produce these images.
04:35 How did it learn?
04:36 Well, how does a human learn an art form?
04:39 We first consume several examples of the art form,
04:42 we observe the details of it, and then we practice it.
04:45 When we practice it, someone, usually a teacher,
04:47 points out what is wrong,
04:49 and we learn to tweak the way we do it.
04:52 [Music]
04:54 This is almost exactly the way an AI model learns to produce art.
05:06 It first consumes several thousands of examples of art,
05:09 usually fed into it by the human who is building the AI model.
05:12 These examples are part of what is called a data set.
05:15 AI that is being trained to generate images
05:18 learns from a data set of several millions of images.
05:21 An AI engineer shows the model these images.
05:24 The model learns the patterns, the details, the colors, the shapes, everything.
05:28 And it learns how to associate a particular visual with a particular text.
05:32 Once the AI model has learned from the data set,
05:34 it uses an algorithm to make decisions
05:36 and produce new art based on what it's learned.
05:39 To draw an analogy, an artist would use paints as the raw material
05:44 and would manipulate that paint with paint brushes, which is the tool.
05:48 Here, for me, there are two broad materials that I work with.
05:54 One is data and then algorithms, which are tools to manipulate that data.
05:59 So, no, it's not just about entering a prompt, generating an image,
06:03 and then calling it art.
06:04 Harshit is an MIT-trained machine learning expert and AI artist.
06:08 He's among the human machine learning experts
06:10 who create data sets and train AI models.
06:13 I might have used Firefly as a way to demonstrate what these models are capable of,
06:17 but there are people out there who use these models every day as part of their workflow.
06:21 I've been into filmmaking for almost three years now,
06:24 and I started as an editor.
06:26 And then from there, I got into direction.
06:28 And currently, I'm working at Zomato as a film director.
06:31 I spoke to Ranje Jha, a filmmaker.
06:33 He uses AI programs in his work at Zomato.
06:36 First, like, I usually, what we do is we have a script,
06:39 like our team of writers, they write, of course, like brilliant scripts,
06:42 and that's what I get.
06:44 Then I take that script and I feed it to Chahat GPD to start with.
06:47 Now, the best part is that you can tell Chahat GPD
06:50 to behave the way you want it to behave.
06:52 Like, I can tell Chahat GPD,
06:54 "Write the screenplay like Christopher Nolan."
06:56 I, by default, am getting the styled-up screenplay,
07:00 and I have to put zero effort in it.
07:01 Now, moving to the next part, storyboarding, right?
07:04 We might not have the budget to get a storyboard artist in the first place, right?
07:09 So, when these kind of scenarios are there,
07:11 like, I would use Midjourney for usually creating a storyboard.
07:15 Like, we just have to feed the prompt, you know,
07:18 based on what we're looking at,
07:20 and we are getting visuals right from there.
07:23 We just put all of them in a deck, and then we have a storyboard,
07:26 or, you know, in general, a mood reference ready for us.
07:29 So, that's another way in which I incorporate AI in my workflow.
07:34 Apart from creatives who use AI models to help with their workflow,
07:38 there are also people who work with open-source AI models
07:41 to make their vision a reality.
07:42 It was raining a lot in Bombay.
07:44 I just saw, in my society, there were a lot of kids,
07:47 they were dancing or something like that,
07:49 and I ordered lunch,
07:51 and one of the Zomato guy came wearing that raincoat,
07:55 and I saw that, and I just combined,
07:57 and it clicked me that time, immediately,
08:00 that these people are, like, you know, delivering food and all of that,
08:03 and the kids are dancing, like, literally, down.
08:07 So, it's a very high contrast.
08:09 Meet Saurabh Dhabai, a creative from Mumbai,
08:11 who came up with a campaign idea.
08:13 Coincidentally, also for Zomato, executed it on Midjourney,
08:16 a generative AI model, and then watched it go viral.
08:20 So, I tried making it, generating it, using Midjourney,
08:24 but since Midjourney cannot come up with the logos
08:27 and doesn't understand brands that well,
08:30 so it was not generating how I was expecting.
08:33 So, yeah, then I tried to, like, you know,
08:36 simple it down, I just wrote, like,
08:39 a guy in Mumbai streets, dancing, wearing a red raincoat,
08:45 then it generated something like that,
08:47 and then I did the branding, I would say, in Photoshop.
08:51 I would say this whole process, thinking about the idea,
08:54 and posting it, live, took me, max to max, four and a half hours.
08:59 And then there is the third, most important category of AI practitioners,
09:02 those who actually train the AI model to do what it does.
09:05 I'm Harshit, I work as an artist,
09:08 I make art primarily with emerging technologies,
09:11 like machine learning, augmented reality, virtual reality,
09:15 new forms of fabrication.
09:17 All of us spend pretty much 24/7 with technology these days,
09:22 we can't imagine sort of living without it,
09:24 so we have to sort of move from thinking of it as something
09:28 that gets our tasks done, to forming this more poetic partnership with it.
09:33 Harshit works with AI to create abstract works of art
09:36 that clearly don't exist, but whose inherent intent is to make the consumer think.
09:41 But given how accessible these tools are,
09:43 anyone can also use AI models to create photorealistic images
09:47 of people, objects, places and scenes.
09:50 You saw how Saurabh took a campaign idea
09:52 and created something that is so realistic, yet completely fabricated.
09:56 The humans in those images do not exist.
09:58 So how do you decide what's true and what isn't?
10:01 Can you believe everything you see?
10:03 Till now, how we consume visuals is to believe first,
10:07 and then only if we have enough reasons to doubt it,
10:11 that we go on to verify something, right?
10:14 We kind of believe what we see, there's no two ways about it.
10:17 Now, especially all the digital content that we see,
10:21 I think there has to be a big mental shift of
10:24 trying to form ourselves somehow to doubt first
10:30 and then believe only if there are enough reasons to believe it.
10:34 And I think that kind of transformation is not trivial at all.
10:38 So I think that is something that kind of fundamental shift
10:42 is something that we have to start designing for in systems already.
10:47 Through the course of doing the research for this video
10:49 and speaking to all of these people,
10:51 we have learnt that regardless of how potent the AI is,
10:54 the onus is on users, human beings,
10:56 to make sure that they use it in ways that do not harm the interests of our own kind.
11:00 This video showed you a glimpse of what generative AI is
11:03 and what it is capable of creating.
11:05 But these images, can we really call them art?
11:08 Will AI change our understanding of the concept of art?
11:11 Will it make creative jobs irrelevant?
11:13 Those are the questions I'll be answering in the next video.
11:16 If you have questions or suggestions, let me know in the comments below.
11:19 Subscribe to Deccan Herald's social media channels
11:21 to make sure you don't miss the next video.
11:24 [Music plays]
11:29 [MUSIC]
