Impact of AI on Jobs

Rinat Malik: 00:00:05

Hi everyone.

Rinat Malik: 00:00:06

Welcome to Tech Talk, a podcast where Amit and I talk about all things tech.

Rinat Malik: 00:00:11

We don't just talk about tech, we also talk about how the tech affects

Rinat Malik: 00:00:15

our society and all the other things related to everything tech.

Rinat Malik: 00:00:20

So today we are gonna talk about something that everyone's talking

Rinat Malik: 00:00:23

about impact of AI on jobs.

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with the last year 2023.

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We've seen a surge of many, many different types of AI being available to consumers

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to produce various types of content and help them augment their performance

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of anything that they want to do, and that obviously opened the discussion

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on how is it going to impact our jobs.

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Many people are thinking that what they do on a day-to-day

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basis will become obsolete.

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the optimists are thinking that there will be new jobs there are various

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weaknesses that with time we've started to figure out that okay, not everything

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can be replaced exactly with AI as we are seeing the AI scene evolve on a

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month by month and week by week basis.

Rinat Malik: 00:01:12

So yeah, there's many aspects to explore and talk about and, so it would be

Rinat Malik: 00:01:17

really fun topic to talk about with Amit.

Rinat Malik: 00:01:19

So what's your thought on this, Amit?

Amit Sarkar: 00:01:21

So I think it's a very relevant topic and, thanks,

Amit Sarkar: 00:01:24

Rinat for that introduction.

Amit Sarkar: 00:01:25

I think AI is quite relevant now and it's all around us.

Amit Sarkar: 00:01:28

A lot of tools are coming up and a lot of use cases are coming

Amit Sarkar: 00:01:31

up now with the advent of AI.

Amit Sarkar: 00:01:33

We talked about generative AI a couple of episodes back.

Amit Sarkar: 00:01:36

We talked about chat GPT, we talked about AR and VR.

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So there are a lot of different aspects to this whole AI thing.

Amit Sarkar: 00:01:43

there is metaverse coming in, so there's a huge potential for this.

Amit Sarkar: 00:01:46

I think the surge of AI is predominantly because of the large language

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models, LLMs, as they call it.

Amit Sarkar: 00:01:52

Machine learning has been there for a very long time, and we have been

Amit Sarkar: 00:01:55

using that for image recognition and mapping different images.

Amit Sarkar: 00:01:58

But I think with LLMs, it's just taken a whole new level with with

Amit Sarkar: 00:02:03

respect to AI reaching to the masses.

Amit Sarkar: 00:02:05

So what I feel is, and I've read this as a quote, is that AI will not replace you.

Amit Sarkar: 00:02:11

People using AI will replace you.

Amit Sarkar: 00:02:13

I.

Amit Sarkar: 00:02:14

So I think that's very apt.

Amit Sarkar: 00:02:15

So there are so many AI tools in the market and we ourselves have

Amit Sarkar: 00:02:19

been playing with a lot of AI tools.

Amit Sarkar: 00:02:20

And what we are trying to see is what these AI tools can do and what

Amit Sarkar: 00:02:24

can we do with these AI tools and what, what is the pricing like, what

Amit Sarkar: 00:02:28

can we do with the fee free tier?

Amit Sarkar: 00:02:29

What can we do in the paid tier?

Amit Sarkar: 00:02:31

So I am.

Amit Sarkar: 00:02:32

I'm currently paying for a tool called Descript on which

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we are recording this podcast.

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And it has this facility where it'll generate the transcript and we can

Amit Sarkar: 00:02:40

edit the video using transcript.

Amit Sarkar: 00:02:42

I think Rinat is using Chat GPT paid version, so there he can use GPT four

Amit Sarkar: 00:02:47

and then he can use images, he can use websites and everything to search

Amit Sarkar: 00:02:52

the internet and create content.

Amit Sarkar: 00:02:53

And we have used AI In generating transcripts, but also, like, I've used

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it for a few articles for my newsletter.

Amit Sarkar: 00:03:01

I've created an AI influencer using AI.

Amit Sarkar: 00:03:04

And we have been using AI for the last one year, and it's really amazing.

Amit Sarkar: 00:03:09

So I think it's a very relevant topic and let's discuss further

Amit Sarkar: 00:03:12

about what it impacts on a day-to-Day life and how it affects our jobs.

Rinat Malik: 00:03:17

Yeah, very much so.

Rinat Malik: 00:03:18

when, when we talk about AI and jobs, this reminds me of a short video I've

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seen when chat GPT first came out at the end of Everyone was trying and,

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whoever was in whichever profession they were seeing how would chat GPT react

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or reply to that professional question.

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And there was a video.

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I remember a lawyer was doing a, a live in front of camera see what Chat

Rinat Malik: 00:03:43

GPT can do and it asks it to create a contract with particular various.

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legal terms, et cetera, and, some of those things as audiences who are not legally

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aware, we didn't understand those terms.

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But then Chat GPT wrote this contract, which actually exceeded the expectation

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of the lawyer who was doing it.

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And he was saying that not only he did what I asked it to do, it.

Rinat Malik: 00:04:07

Not only it did what I asked it to do but also it added some, relevant

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addendums and clause in that contract, which would be typical for that scenario.

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So now that's using common sense.

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it appears as though Chat GPT is using common sense and adding those things.

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And then, the, the next second he was very happy saying that, oh, my

Rinat Malik: 00:04:29

job would be really easy from now on.

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then the second afterwards, you see the realisation in his face and he

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realises that it's almost like he himself is not required anymore because

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he was a recent graduate from law school and he was like, okay, it can

Rinat Malik: 00:04:46

do everything I can do and better.

Rinat Malik: 00:04:48

So where, where does it put me?

Rinat Malik: 00:04:51

that realization is what people are having all throughout last year in

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2023, as they start using chat GPT more and more, as more people become aware.

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So even when you send.

Rinat Malik: 00:05:04

A very well written email, nowadays, people might not give you the

Rinat Malik: 00:05:08

credit or, or, the articulation that has gone into the email.

Rinat Malik: 00:05:12

They might actually not give you that credit for that

Rinat Malik: 00:05:16

because everyone's doing it.

Rinat Malik: 00:05:17

It's like a inflation of intelligence is what's happening right now

Rinat Malik: 00:05:23

and how does that affect jobs?

Rinat Malik: 00:05:25

It is affecting jobs, but I think what's happening is because of the hype of,

Rinat Malik: 00:05:30

oh, AI can do so many groundbreaking things, it's like day and night

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difference between 2022 and 2023.

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in terms of productivity.

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So companies also became quite hyped and thinking, there are

Rinat Malik: 00:05:43

so many ways we could use it.

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But actually on an enterprise scenario, there are many things to think about when

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you wanna implement a new technology.

Rinat Malik: 00:05:52

especially, I, I am primarily experienced in banking and finance,

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and there are regulatory requirements, there are various risks that you need

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to take into account and quantify how would you manage these risks?

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So for example, there has been talks that AI has been found to be biased in many

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ways, gender bias, race bias, et cetera.

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And what if a bank integrates AI to reply to a customer and these biases

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come through in that conversation, that would be a huge reputational risk for

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the bank or any organization as well as regulatory and compliance issue as

Rinat Malik: 00:06:29

well, because it appears as though that organization is treating people unfairly

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or differently based on their age, race, gender, So there are many, many risks.

Rinat Malik: 00:06:39

as useful as it may seem to make it work on an enterprise scenario

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is not just, okay, let's just buy subscription of Chat GPT, and we are set.

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it's not as easy as that.

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And sometimes you might even have to think about how can we dial down

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the intelligence, dial down the.

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bespoke responses, but always make sure it comes back with standardized

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set of responses as required, which is a bit of a dumbed down version

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of the solution people might think, but that is maybe what is required.

Rinat Malik: 00:07:13

So.

Rinat Malik: 00:07:14

just overnight transition of AI is gonna be doing my job from tomorrow is not

Rinat Malik: 00:07:19

realistic to think And also whether it can do everything to the degree that a

Rinat Malik: 00:07:25

human would is still very much questioned.

Rinat Malik: 00:07:28

So these are different perspective to think about when you think

Rinat Malik: 00:07:33

about the answer to this question.

Amit Sarkar: 00:07:34

Yeah, I think and you've raised a valid point about regulations

Amit Sarkar: 00:07:37

and regulatory requirements, but I think before we delve into job

Amit Sarkar: 00:07:41

security, I think our AI taking over.

Amit Sarkar: 00:07:44

I think I'll come back to the quote.

Amit Sarkar: 00:07:45

AI will not replace people.

Amit Sarkar: 00:07:47

People using AI will replace people.

Amit Sarkar: 00:07:49

So what that means, so it means that AI is augmenting you and it's augmenting

Amit Sarkar: 00:07:54

your productivity and augmenting anything that you're currently doing.

Amit Sarkar: 00:07:57

So suppose you take some time to write an email or suppose you take

Amit Sarkar: 00:07:59

some time to draft a, a contract.

Amit Sarkar: 00:08:02

So that now is augmented.

Amit Sarkar: 00:08:04

It means you can do the research far more quicker with AI.

Amit Sarkar: 00:08:07

Of course it's not a hundred percent accurate, but it

Amit Sarkar: 00:08:09

means you can do it quicker.

Amit Sarkar: 00:08:10

So it means you are already much better than someone who's doing it by himself,

Amit Sarkar: 00:08:14

just doing all the Google search.

Amit Sarkar: 00:08:16

so you are doing it much faster and you can create a early

Amit Sarkar: 00:08:18

draft using AI very easily.

Amit Sarkar: 00:08:21

So now, before we talk about the tools, we have to talk about these

Amit Sarkar: 00:08:24

large language models and what are the different aspects to current generative

Amit Sarkar: 00:08:28

AI which is actually generating different types of things for us.

Amit Sarkar: 00:08:32

So when we look at large language models, it is trained on text, and that text

Amit Sarkar: 00:08:36

is currently taken from the internet.

Amit Sarkar: 00:08:37

So it could be papers, it could be websites, it could be forums, it could

Amit Sarkar: 00:08:40

be video sites, et cetera, et cetera.

Amit Sarkar: 00:08:43

So, but large language models is predominantly, trained on text.

Amit Sarkar: 00:08:47

Now, this text data, it means that whatever is written on the internet,

Amit Sarkar: 00:08:50

say on Twitter or say on LinkedIn.

Amit Sarkar: 00:08:52

So it just captures it and trains itself on it.

Amit Sarkar: 00:08:54

So if there is bias on it, it means there is bias in the.

Amit Sarkar: 00:08:57

system.

Amit Sarkar: 00:08:58

So that means bias in training data translates to bias in the system itself.

Amit Sarkar: 00:09:02

So a lot of companies, what they try to do is they try to remove the bias.

Amit Sarkar: 00:09:05

They have humans to look at the training data, try to identify if

Amit Sarkar: 00:09:09

there is any bias, try to remove it.

Amit Sarkar: 00:09:10

But of course it's not possible because your dealing with billions

Amit Sarkar: 00:09:14

and billions of text lines of text.

Amit Sarkar: 00:09:16

Then we have images.

Amit Sarkar: 00:09:17

So we have mid journey, we have Dall-e, and they are trained

Amit Sarkar: 00:09:20

on different types of images.

Amit Sarkar: 00:09:22

So you have a big data set of images, and now you can generate new images,

Amit Sarkar: 00:09:26

especially for graphic designers, logo designers, website creators, et cetera.

Amit Sarkar: 00:09:31

So this is again, a.

Amit Sarkar: 00:09:33

Very different aspect now.

Amit Sarkar: 00:09:34

So suppose I want to create a thumbnail for my YouTube instead of creating

Amit Sarkar: 00:09:37

it myself I can ask AI to use certain images as input images and generate

Amit Sarkar: 00:09:42

a new image for my YouTube as a thumbnail or as a Instagram picture.

Amit Sarkar: 00:09:46

I.

Amit Sarkar: 00:09:46

The next thing is video.

Amit Sarkar: 00:09:48

So now there are tools that can generate videos for you.

Amit Sarkar: 00:09:51

So you give them a text prompt and it generates video.

Amit Sarkar: 00:09:53

And these videos are not highly realistic, but it can be highly stylized.

Amit Sarkar: 00:09:56

So suppose you want to create an animated video, but you are

Amit Sarkar: 00:09:59

not an expert in animation.

Amit Sarkar: 00:10:00

So you can create a text prompt, pay some money, and get these

Amit Sarkar: 00:10:04

videos created for you very quickly.

Amit Sarkar: 00:10:06

Without a lot of creative input.

Amit Sarkar: 00:10:08

So when the generative AI came, it was the age of democratizing creation.

Amit Sarkar: 00:10:14

So it means that anything that you want to create now or using ai, it's much

Amit Sarkar: 00:10:18

more faster, much better, and quicker.

Amit Sarkar: 00:10:21

But, but the thing is, it's not, going to replace you?

Amit Sarkar: 00:10:25

It's not at that stage yet because it is based on the training data.

Amit Sarkar: 00:10:28

So there is nothing new coming out of it because it is just

Amit Sarkar: 00:10:32

correlation from that data.

Amit Sarkar: 00:10:34

So if I ask it

Rinat Malik: 00:10:35

yeah, just, just a little bit of anecdote as you were saying.

Rinat Malik: 00:10:38

I just remembered something that AI falls over when it is

Rinat Malik: 00:10:42

fed AI generated training data.

Rinat Malik: 00:10:44

It just completely starts generating things that are not meaningful in any way.

Rinat Malik: 00:10:49

So if you keep feeding it data that's also generated by an ai,

Rinat Malik: 00:10:54

then it just can't work at all.

Rinat Malik: 00:10:56

So you might think that, from YouTube to everything is gonna be filled with

Rinat Malik: 00:11:00

AI generated content, but those content then can't generate new content anymore.

Rinat Malik: 00:11:06

So there has to be a steady influx of human generated content always in

Rinat Malik: 00:11:12

order for AI to work side by side.

Rinat Malik: 00:11:14

I.

Amit Sarkar: 00:11:14

So, that, that's a very good point.

Amit Sarkar: 00:11:15

Rinat, that AI being fed on data that's created by ai, so that's synthetic data.

Amit Sarkar: 00:11:20

So and a lot of companies are already thinking about how to create synthetic

Amit Sarkar: 00:11:24

data because you will run out of training data after a certain period of time.

Amit Sarkar: 00:11:27

If you have scanned all the internet over the last couple of years and that's

Amit Sarkar: 00:11:31

all you have, then you would have to create new data to create new models.

Amit Sarkar: 00:11:35

Of course, we are generating a lot of data.

Amit Sarkar: 00:11:37

But that may not be enough to train the new models.

Amit Sarkar: 00:11:40

So companies are looking on how to generate data by themselves so

Amit Sarkar: 00:11:44

that these models can be trained.

Amit Sarkar: 00:11:46

But of course, we'll have to be very careful about what there

Amit Sarkar: 00:11:48

is, what is there in the data.

Amit Sarkar: 00:11:49

But the whole idea of talking about this is that it's not

Amit Sarkar: 00:11:52

going to create something new.

Amit Sarkar: 00:11:53

It is going to take an input of what is already there and then

Amit Sarkar: 00:11:57

create something, a mixture of it.

Amit Sarkar: 00:12:00

So suppose I want to create a test policy.

Amit Sarkar: 00:12:02

I ask the test policy, create a test policy for me.

Amit Sarkar: 00:12:05

So it's not going to create a new test policy for me.

Amit Sarkar: 00:12:07

It's going to scan the, it's already scanned the internet.

Amit Sarkar: 00:12:09

It has got some of the data, and then it's just going to blabber out

Amit Sarkar: 00:12:13

some of the things that are already there in standard test policies,

Amit Sarkar: 00:12:16

that data is read on the internet.

Amit Sarkar: 00:12:17

So that is what it is.

Amit Sarkar: 00:12:18

But how it makes me better or more productive, say to my colleague is

Amit Sarkar: 00:12:23

that now I can create a test policy in few seconds, whereas my colleague

Amit Sarkar: 00:12:27

will have to think about it and draft a test policy and and like do a lot

Amit Sarkar: 00:12:32

of research in order to create one.

Amit Sarkar: 00:12:34

But for me, I asked Chat GPT, it created a test policy.

Amit Sarkar: 00:12:37

I just edited it.

Amit Sarkar: 00:12:38

So, that's the difference.

Rinat Malik: 00:12:41

Absolutely.

Rinat Malik: 00:12:41

And yeah, editing something rather than creating something from scratch

Rinat Malik: 00:12:45

is a lot quicker and You can focus on enhancing the quality of the final

Rinat Malik: 00:12:49

output rather than just creating the very crude skeleton part.

Rinat Malik: 00:12:54

'cause that takes a lot of time, but that doesn't really enhance

Rinat Malik: 00:12:56

the quality that just, the basic building blocks needs to be there.

Rinat Malik: 00:13:00

Time consuming.

Rinat Malik: 00:13:01

And now that part is taken care of.

Rinat Malik: 00:13:03

And now you can focus on more creative stuff how you can expand on the already

Rinat Malik: 00:13:07

created product or content, et cetera.

Rinat Malik: 00:13:10

And this reminds me of another interesting not study, but

Rinat Malik: 00:13:13

phenomena that we've seen in this.

Rinat Malik: 00:13:15

This is something I've seen in 2019 or 2020 before chat GPT or this

Rinat Malik: 00:13:20

popularized AI systems were in play.

Rinat Malik: 00:13:22

But we were, we've been working with AI way before that.

Rinat Malik: 00:13:26

the different types of ai, which are pattern identifying AI and then there was

Rinat Malik: 00:13:31

in medical sector I was working with an AI which would identify, look at MRI scans

Rinat Malik: 00:13:37

thousands and thousands, billions of MRI scans to, to train it and then identify

Rinat Malik: 00:13:42

whatever is wrong within those scans.

Rinat Malik: 00:13:46

the percentage of accuracy when after the AI model was matured with training data,

Rinat Malik: 00:13:52

It always Shifted between 88% to 93%.

Rinat Malik: 00:13:58

And at the same time, a very experienced medical professional doctor or a surgeon,

Rinat Malik: 00:14:04

their accuracy was also about at the same level, 90 to 95% or, or something.

Rinat Malik: 00:14:09

There is an overlap and, but they're pretty much on par.

Rinat Malik: 00:14:13

But where the difference came is if, medical professional worked together

Rinat Malik: 00:14:18

with the AI generated solution, then the accuracy shot up to 98%.

Rinat Malik: 00:14:24

So basically going back to your quote again you're not gonna be replaced by AI.

Rinat Malik: 00:14:29

You're gonna be replaced by people using AI because.

Rinat Malik: 00:14:31

That's the most lethal combination as well, because highest accuracy

Rinat Malik: 00:14:36

highest level of creativity and the highest level of speed you can

Rinat Malik: 00:14:41

also achieve in terms of generating whatever content or product or whatever

Rinat Malik: 00:14:45

output it is that you're looking for.

Rinat Malik: 00:14:48

So yeah, augmenting human performance is is what AI does

Rinat Malik: 00:14:52

best at this point in time.

Rinat Malik: 00:14:54

Obviously in future, there is talks about artificial general intelligence, although

Rinat Malik: 00:14:58

that is a vastly different concept.

Rinat Malik: 00:15:00

people do mistake the large language models as if it's thinking

Rinat Malik: 00:15:04

and understanding, but it's not.

Rinat Malik: 00:15:06

So I think we are still a bit far away from that, but you never know.

Amit Sarkar: 00:15:11

what I have noticed from using charge GPT over the

Amit Sarkar: 00:15:13

last couple of months is that it's not a hundred percent accurate and

Amit Sarkar: 00:15:16

sometimes it starts repeating itself.

Amit Sarkar: 00:15:18

So if you ask specific things, it can respond.

Amit Sarkar: 00:15:22

I.

Amit Sarkar: 00:15:22

But after you delve into it with much more questioning, then it starts failing.

Amit Sarkar: 00:15:26

And that's where you see the limitations of a system like this because it tries

Amit Sarkar: 00:15:29

to repeat the same thing and it's just trying to predict what the next word is.

Amit Sarkar: 00:15:34

it's not actually having any intelligence.

Amit Sarkar: 00:15:36

It's just trying to see that, okay, what's the next word?

Amit Sarkar: 00:15:38

What is the probability of that next word?

Amit Sarkar: 00:15:40

And I try to fit it to make sense of it, and that's how it works.

Rinat Malik: 00:15:44

I.

Rinat Malik: 00:15:45

Absolutely, and that's, that's another interesting thing

Rinat Malik: 00:15:48

that happens if you ask it.

Rinat Malik: 00:15:49

What's two plus two?

Rinat Malik: 00:15:50

It will very confidently answer four and it'll be right, but it doesn't know what

Rinat Malik: 00:15:55

two is and what plus is and what two is.

Rinat Malik: 00:15:57

It just knows.

Rinat Malik: 00:15:58

It just went through a lot of training data where it's seen two

Rinat Malik: 00:16:01

plus two is four, but if you ask it a random but a very simple arithmetic.

Rinat Malik: 00:16:07

An addition arithmetic, but two large random numbers, maybe 17,542

Rinat Malik: 00:16:14

plus 37,000 something something.

Rinat Malik: 00:16:18

It very likely will completely get it wrong because that's, it's very

Rinat Malik: 00:16:22

unlikely that it was fed on that exact training data multiple times.

Rinat Malik: 00:16:27

So it doesn't have anything to refer back to or, tell you what

Rinat Malik: 00:16:31

would be the next next word for it.

Rinat Malik: 00:16:33

So, that's how you can see where it breaks down.

Rinat Malik: 00:16:36

I think.

Rinat Malik: 00:16:37

after using chat, GPT and other LLMs, like Claude and Google Bard.

Rinat Malik: 00:16:42

And a few other ones as well.

Rinat Malik: 00:16:44

Much smaller ones I think I would come to a conclusion that even though it

Rinat Malik: 00:16:48

sounds like it's an overnight change from what we had before and after Chat

Rinat Malik: 00:16:53

GPT, but it's actually a really big step forward from google search engine

Rinat Malik: 00:17:01

because in 2022, we were already asking in in the Google search

Rinat Malik: 00:17:06

engine that, okay, how do I do this?

Rinat Malik: 00:17:09

And then it will find the answer and it will also try and, generate

Rinat Malik: 00:17:15

some question and answer for you from the result already.

Rinat Malik: 00:17:18

So it was doing that already Google.

Rinat Malik: 00:17:21

what is the job of a search engine is?

Rinat Malik: 00:17:23

It's basically by the time we reached 2022 or 2020, we had vast amount

Rinat Malik: 00:17:30

of information on the internet and.

Rinat Malik: 00:17:32

We needed a way to categorize it so that we can find the

Rinat Malik: 00:17:36

information when we need it.

Rinat Malik: 00:17:38

The, very particular information from that sea of everything.

Rinat Malik: 00:17:41

We just needed the answer to this one question that how do I, solve the blue

Rinat Malik: 00:17:46

screen issue when my BIOS is not working or some something when you're working.

Rinat Malik: 00:17:51

And then Google would find you that answer from all the things that he had indexed.

Amit Sarkar: 00:17:56

No, no.

Amit Sarkar: 00:17:56

Google will not find you the answer.

Amit Sarkar: 00:17:58

Google will give you a set of websites that it thinks has the

Amit Sarkar: 00:18:02

and Chat GPT gives you the answer because it doesn't give you a set of links.

Rinat Malik: 00:18:06

Yes.

Rinat Malik: 00:18:06

that's how it is to the user, right?

Rinat Malik: 00:18:08

It's appearing like that.

Rinat Malik: 00:18:10

But ultimately, what's happening is Google has indexed all of internet.

Rinat Malik: 00:18:14

But Chat GPT was, it doesn't index, it was trained on, on patterns of data,

Rinat Malik: 00:18:18

but those data is, is, is still there and it's basically bringing you up the

Rinat Malik: 00:18:24

right data and in a way that you don't have to click five links and, read

Rinat Malik: 00:18:28

five conversation between human beings.

Rinat Malik: 00:18:30

It just bringing you the specific information you need.

Rinat Malik: 00:18:34

And presenting it to you in a way that is most useful to you.

Rinat Malik: 00:18:39

it just a, a direct one-to-one conversation.

Rinat Malik: 00:18:41

So yeah, it is an overnight real big step forward.

Rinat Malik: 00:18:45

But if you think about it, it's a really big step forward from

Rinat Malik: 00:18:50

search engines to what it is now.

Rinat Malik: 00:18:52

obviously we can talk about the image generation and all of the

Rinat Malik: 00:18:55

other different content types after.

Rinat Malik: 00:18:57

But in terms of text generation, you're searching for something.

Rinat Malik: 00:19:01

Nowadays, most of the ways public are using chat GPT, if they have a

Rinat Malik: 00:19:05

question, they say, oh, give me the answer, and it gives you the answer.

Amit Sarkar: 00:19:11

Yeah, I think it's a valid point that, okay, the search

Amit Sarkar: 00:19:13

engines were used and find you the answer and charge strain on the data.

Amit Sarkar: 00:19:17

But if you look at say an example where I want to create a travel

Amit Sarkar: 00:19:21

plan for my family to go to South Africa on a holiday in November, I.

Amit Sarkar: 00:19:27

So, so if I go to Google search and I say, okay I want to have a travel itinerary

Amit Sarkar: 00:19:32

for a trip like this in November to South Africa, it'll gimme a lot of links.

Amit Sarkar: 00:19:38

I'll have to look at the different flight options.

Amit Sarkar: 00:19:40

I'll have to look at the hotel options.

Amit Sarkar: 00:19:41

I'll have to look at what places I want to go.

Amit Sarkar: 00:19:44

I'll have to look at how many days I have to spend in each place, et cetera.

Amit Sarkar: 00:19:47

If I ask the same question in charge GPT giving all the necessary details,

Amit Sarkar: 00:19:51

charge GPT is going to gimme an itinerary day by day itinerary.

Amit Sarkar: 00:19:53

It's going to break it down.

Amit Sarkar: 00:19:55

It's going to tell me that you take a flight from here to here.

Amit Sarkar: 00:19:58

And depending upon the weather in November, it'll tell me, okay, go

Amit Sarkar: 00:20:01

to this city or that city and do this sighting and that sight seeing.

Amit Sarkar: 00:20:04

So it's already done a lot of research for me, and now I just have to do those things

Amit Sarkar: 00:20:08

like book a hotel, look at the itinerary.

Amit Sarkar: 00:20:11

And it's not like I will plan my whole trip around the itinerary, but most

Amit Sarkar: 00:20:15

of the research has already been done.

Amit Sarkar: 00:20:16

And now if you take that into a job aspect, because I think we, we have, we

Amit Sarkar: 00:20:20

are, we have digressed a lot from the job.

Amit Sarkar: 00:20:22

So in a job a lot of people they have chat.

Amit Sarkar: 00:20:25

We chat a lot, say on Slack.

Amit Sarkar: 00:20:27

Then we send a lot of emails.

Amit Sarkar: 00:20:28

So email is where you do a lot of your work because you have to

Amit Sarkar: 00:20:31

communicate about different things.

Amit Sarkar: 00:20:32

Then you use some a project management tool where you'll

Amit Sarkar: 00:20:35

have to manage different tasks.

Amit Sarkar: 00:20:38

Or a task management tool, any, any task.

Amit Sarkar: 00:20:40

It could be task of development, task of testing, task of managing

Amit Sarkar: 00:20:43

projects, resources, budget, et cetera.

Amit Sarkar: 00:20:45

And then you would also try to do some presentations.

Amit Sarkar: 00:20:48

You will have to draft some contracts, et cetera.

Amit Sarkar: 00:20:50

Now, for all these use cases what I've, I've noticed is that chat gpt is very

Amit Sarkar: 00:20:55

good at giving you an initial draft.

Amit Sarkar: 00:20:57

So suppose I want to send out an email about about a new proposal.

Amit Sarkar: 00:21:01

Okay.

Amit Sarkar: 00:21:02

And I want to tell my boss that, okay, I think that we should be proposing this

Amit Sarkar: 00:21:05

company about our products like this.

Amit Sarkar: 00:21:08

And it's something there in my head, but I don't know how to articulate it.

Amit Sarkar: 00:21:11

And I'll have to do some Google search.

Amit Sarkar: 00:21:12

I'll have to see what others are thinking about this same product and

Amit Sarkar: 00:21:16

how do you promote things, et cetera.

Amit Sarkar: 00:21:17

Now, if I ask Chat GPT and I give it context, like, okay, I'm a person

Amit Sarkar: 00:21:21

who's a manager at this company that specializes in this sector.

Amit Sarkar: 00:21:25

And I'm now trying to draft an email to my boss, and we want to write a proposal

Amit Sarkar: 00:21:29

and we want to talk about this product.

Amit Sarkar: 00:21:31

Now give me an output and Chat GPT will give you a very detailed

Amit Sarkar: 00:21:35

output because you've defined the context, you've defined the scenario.

Amit Sarkar: 00:21:37

And Chat GPT will give you a very good output.

Amit Sarkar: 00:21:40

And on that output you can edit things, tweak things replace few things that you

Amit Sarkar: 00:21:44

don't like, and then just send it and also it can, write in a particular tone.

Amit Sarkar: 00:21:49

So it can be a very formal tone, it can be a very informal tone, it can

Amit Sarkar: 00:21:52

be a very casual tone, et cetera.

Amit Sarkar: 00:21:54

So that way you have the hard work is done.

Amit Sarkar: 00:21:57

So now you just have to focus on the final output, tweaking

Amit Sarkar: 00:22:01

it and sending it to your boss.

Amit Sarkar: 00:22:03

So, imagine.

Amit Sarkar: 00:22:04

A person who's doing it from scratch and someone who's using AI to do it.

Amit Sarkar: 00:22:08

So the person doing from scratch would take about 10 to 15 minutes

Amit Sarkar: 00:22:11

or maybe 20 to 20 minutes or 30 minutes to do the research, draft

Amit Sarkar: 00:22:14

an email with you, augmenting AI.

Amit Sarkar: 00:22:17

You write the prompt, it takes you about two minutes.

Amit Sarkar: 00:22:19

Then you get the output, you tweak it, edit it 15 minutes

Amit Sarkar: 00:22:22

max, so you have half the time.

Amit Sarkar: 00:22:24

So from 30 minutes you've come down to 15 minutes, and maybe you can do it even

Amit Sarkar: 00:22:27

in five minutes if you are good at it.

Amit Sarkar: 00:22:30

So most of Chat GPT now is about prompts.

Amit Sarkar: 00:22:33

what is the quality of your prompt and how can you get the best output

Amit Sarkar: 00:22:38

in the, in the least amount of inputs?

Amit Sarkar: 00:22:42

So suppose I want to get an output for a travel itinerary or an email.

Amit Sarkar: 00:22:46

I want it to give me the best possible answer in, in one or two prompts.

Amit Sarkar: 00:22:50

I don't want to write 10 different prompts.

Amit Sarkar: 00:22:53

And asking it for 10 different outputs, and then I collate all the

Amit Sarkar: 00:22:58

information and then I create something.

Amit Sarkar: 00:23:00

I won't have one single prompt and then one quick great

Amit Sarkar: 00:23:04

output, and then just use that.

Amit Sarkar: 00:23:06

So a lot of this is actually about writing good prompts.

Amit Sarkar: 00:23:09

So you get good outputs in the shortest amount of time because

Amit Sarkar: 00:23:12

you have to pay for these tools.

Amit Sarkar: 00:23:14

These are not free tools and a lot of companies, what they're now thinking

Amit Sarkar: 00:23:17

is, can we create an LLM for ourselves?

Amit Sarkar: 00:23:20

Can we use our company data, our product data, and train an AI

Amit Sarkar: 00:23:25

just for our specific things?

Amit Sarkar: 00:23:26

Because the thing is, the moment you start talking to chat GPT,

Amit Sarkar: 00:23:30

you are sending confidential information to Chat GPT servers.

Amit Sarkar: 00:23:35

Now that means that suppose you tweak in some information about your

Amit Sarkar: 00:23:38

company, some stock prices or anything, it's gone in the training data.

Amit Sarkar: 00:23:42

Of course, they won't be able to identify exactly but that data is now

Amit Sarkar: 00:23:46

in the training data because whatever you talk to them, it's using it to

Amit Sarkar: 00:23:50

train itself and getting better at it.

Amit Sarkar: 00:23:53

So that's the downside.

Rinat Malik: 00:23:54

Absolutely.

Rinat Malik: 00:23:55

it's a downside.

Rinat Malik: 00:23:56

But having known that this is what happens, you could protect yourself

Rinat Malik: 00:24:00

from it and see the power of it.

Rinat Malik: 00:24:02

So, the first scenario when you were mentioning that, yeah, you wanna

Rinat Malik: 00:24:05

draft an email and all of these.

Rinat Malik: 00:24:07

So if, imagine if the AI model had all the information.

Rinat Malik: 00:24:12

all, all the internal company information and for large companies with a hundred k

Rinat Malik: 00:24:16

employees, that's a lot of information in Slack, in teams, in all of these channels.

Rinat Malik: 00:24:22

And also knowledge bases.

Rinat Malik: 00:24:23

SharePoint is like, a slew of information for data protection, if

Rinat Malik: 00:24:27

you can have like a internal AI model.

Rinat Malik: 00:24:31

which has the base of understanding and responding to you like chat

Rinat Malik: 00:24:35

GPT, but then it's been trained on all the internal data.

Rinat Malik: 00:24:38

Then you could ask it, write

Rinat Malik: 00:24:40

this report.

Rinat Malik: 00:24:41

And then as a human, you would check that, that that report is actually fit for

Rinat Malik: 00:24:46

purpose and it quantifies the exact metric that you are looking for or your boss is

Rinat Malik: 00:24:51

looking for or your team is looking for.

Rinat Malik: 00:24:53

So you can then tailor make it but then the, generating the base

Rinat Malik: 00:24:57

report part is done in seconds

Amit Sarkar: 00:24:59

Yeah.

Rinat Malik: 00:25:00

and that's what makes chat GPT or AI models so much more powerful.

Rinat Malik: 00:25:04

In a way that it increases your productivity, but it does not

Rinat Malik: 00:25:08

make your human judgment obsolete.

Rinat Malik: 00:25:11

Not yet anyway.

Amit Sarkar: 00:25:12

And I think one of the things that I'm, I'm seeing even in my

Amit Sarkar: 00:25:15

own company is that a lot of effort is now being put into designing your own

Amit Sarkar: 00:25:19

LLMs or designing your own AI model.

Amit Sarkar: 00:25:21

The reason being that if you use Chat GPT you have to first pay for it.

Amit Sarkar: 00:25:25

You don't have control over the data.

Amit Sarkar: 00:25:26

You don't have control over the output, and the training data is quite vast,

Amit Sarkar: 00:25:30

and you want your training data to be very specific just for your industry.

Amit Sarkar: 00:25:33

So you don't want to want a AI model that uses the whole internet

Amit Sarkar: 00:25:36

as its training data base.

Amit Sarkar: 00:25:38

You just want the specific information needed for your sector,

Amit Sarkar: 00:25:41

for your industry, for your product, and train your model on that.

Amit Sarkar: 00:25:45

That's it.

Amit Sarkar: 00:25:46

You don't want, so suppose you're in the retail sector.

Amit Sarkar: 00:25:48

I don't want information about what do you say?

Amit Sarkar: 00:25:50

A travel company.

Amit Sarkar: 00:25:52

Okay.

Amit Sarkar: 00:25:53

I'm just giving a wrong example.

Amit Sarkar: 00:25:54

It can be related, but say defense company.

Amit Sarkar: 00:25:56

So retail has got no relation with defense.

Amit Sarkar: 00:25:59

We are not selling anything to defense companies, so I don't want that data

Amit Sarkar: 00:26:01

to be correlated or I don't want that unnecessary data or if I'm just

Amit Sarkar: 00:26:05

creating on certain types of images.

Amit Sarkar: 00:26:07

I don't want a different type of images.

Amit Sarkar: 00:26:09

So I'm, I've just given you example of email.

Amit Sarkar: 00:26:11

The other example could be logo generation.

Amit Sarkar: 00:26:13

So suppose there is a person who, who designs new logos or who designs new

Amit Sarkar: 00:26:17

new, new art for artwork, say book covers or podcast covers, et cetera.

Amit Sarkar: 00:26:21

Now that person's job can be done now much more quicker.

Amit Sarkar: 00:26:25

So you are not going to replace that person.

Amit Sarkar: 00:26:27

But imagine that person who was handling now 10 clients can handle

Amit Sarkar: 00:26:29

a hundred clients because that.

Amit Sarkar: 00:26:32

Can use AI to augment his or her productivity.

Amit Sarkar: 00:26:36

And that's just one example of logo generation.

Amit Sarkar: 00:26:39

The other example is

Rinat Malik: 00:26:40

So j just to also intercept a little bit on this example,

Rinat Malik: 00:26:43

'cause this is very interesting.

Rinat Malik: 00:26:44

So as you mentioned that the person who could generate 10 artworks before

Rinat Malik: 00:26:49

now can generate a hundred artworks.

Rinat Malik: 00:26:50

And now the immediate thought to our audience or anyone who's thinking might

Rinat Malik: 00:26:55

be that, okay, so now there was only ever a thousand logos to generate.

Rinat Malik: 00:27:00

Now, before a hundred people would be doing those thousand logo designs.

Rinat Malik: 00:27:05

Now only 10 people can do all the market, meet all the market needs, so there is

Rinat Malik: 00:27:10

no jobs for the rest of the 90 people.

Rinat Malik: 00:27:12

And that is gonna be a situation for the time being.

Rinat Malik: 00:27:17

if you put it on a graph, yeah, there is a dip.

Rinat Malik: 00:27:19

But what happens is now there is an influx more of a lot of other people who wanted

Rinat Malik: 00:27:27

to have logo designed but couldn't, or they wanted to have their own startup

Rinat Malik: 00:27:32

business idea, et cetera, couldn't.

Rinat Malik: 00:27:33

But now with all of these additional tools, they are now thinking, okay, let

Rinat Malik: 00:27:38

me start a side project as well as my job.

Rinat Malik: 00:27:40

Everyone's doing that.

Rinat Malik: 00:27:41

So now there is.

Rinat Malik: 00:27:43

When there was a thousand logo to be designed before now there are

Rinat Malik: 00:27:47

10,000 or a hundred thousand people are now asking for new logo designs.

Rinat Malik: 00:27:52

So after that initial dip, there will definitely be a dip

Rinat Malik: 00:27:55

where people will think, oh no 90 people are losing their job.

Rinat Malik: 00:27:58

But very soon after, there will be so much more demand because logo generation

Rinat Malik: 00:28:04

is now a lot easier and a lot cheaper.

Rinat Malik: 00:28:07

As a result, a lot more people would be interested in doing that.

Rinat Malik: 00:28:11

And then you would need a lot more people doing a hundred logos.

Rinat Malik: 00:28:15

So overall, The amount of content being generated is increased.

Rinat Malik: 00:28:19

The quality of content being generated is increased, but it then goes

Rinat Malik: 00:28:24

back to the same amount of people doing it just more efficiently.

Rinat Malik: 00:28:27

So that's how, it's in my mind, no one's losing their job.

Rinat Malik: 00:28:30

It's just that they're becoming more efficient and the demand is increasing.

Amit Sarkar: 00:28:35

and I think that's, that's a very good point.

Amit Sarkar: 00:28:37

Like the dip, there will be a dip, but it means that there will be

Amit Sarkar: 00:28:40

a new baseline of productivity.

Amit Sarkar: 00:28:42

So initially your baseline was a hundred images, now the

Amit Sarkar: 00:28:44

baseline is a thousand images.

Amit Sarkar: 00:28:46

So there.

Amit Sarkar: 00:28:46

The baseline will be changing.

Amit Sarkar: 00:28:48

It's not that, and, and jobs will some people will lose their jobs because their

Amit Sarkar: 00:28:52

baseline productivity is not matching the current standards because the current

Amit Sarkar: 00:28:56

standard is now you should be able to do a hundred images so a thousand images,

Amit Sarkar: 00:28:59

but you're able to do only 500 images.

Rinat Malik: 00:29:02

So that's interesting.

Rinat Malik: 00:29:03

So this is where we go back to your quote, that some people will be losing

Rinat Malik: 00:29:07

their jobs who did not start using AI.

Rinat Malik: 00:29:09

So people who use AI will replace people

Amit Sarkar: 00:29:14

who don't use AI.

Amit Sarkar: 00:29:14

And I think if, if you talk about all these things, we are

Amit Sarkar: 00:29:17

just talking about generation.

Amit Sarkar: 00:29:18

this generative AI is all about generating AI images, AI text, AI videos, AI sound.

Amit Sarkar: 00:29:24

I think the next big problem for any enterprise would

Amit Sarkar: 00:29:28

be, are we violating GDPR?

Amit Sarkar: 00:29:30

Are we violating any copyrights?

Amit Sarkar: 00:29:32

Because see, imagine this this training data is being used to generate

Amit Sarkar: 00:29:37

new text, but that text is already there and it might have copyright.

Amit Sarkar: 00:29:41

So suppose I want to write a book and I write a book on something very technical,

Amit Sarkar: 00:29:45

it is going to gimme something, but that something might already been copyrighted.

Amit Sarkar: 00:29:49

And if I try to use that, someone can throw a legal case at me and

Amit Sarkar: 00:29:52

say that, okay guys, you have used copyright text for your book.

Amit Sarkar: 00:29:56

That's not valid.

Amit Sarkar: 00:29:57

So be smart.

Amit Sarkar: 00:29:59

Don't just use whatever the training data is throwing at you.

Amit Sarkar: 00:30:03

Whatever the AI model is throwing at you, be smart and edit it.

Amit Sarkar: 00:30:07

So when it come to images, you would also see that animation or cartoonish

Amit Sarkar: 00:30:11

characters are far more better.

Amit Sarkar: 00:30:13

But if you try to generate real human beings, then you

Amit Sarkar: 00:30:16

would have a lot of issues.

Amit Sarkar: 00:30:17

Like arms are missing.

Amit Sarkar: 00:30:19

the proportion is not right limbs are missing, et cetera.

Amit Sarkar: 00:30:22

So I, and I have noticed this because I've created an AI influencer on Instagram,

Amit Sarkar: 00:30:26

and I have noticed this while generating the images that some images are morphed,

Amit Sarkar: 00:30:29

some, some images are not correct.

Amit Sarkar: 00:30:31

So even though you're using AI to generate these images, it's not a hundred percent.

Amit Sarkar: 00:30:36

So you might have to do some modifications.

Amit Sarkar: 00:30:38

And then same goes for sound.

Amit Sarkar: 00:30:39

you can generate a lot of new music.

Amit Sarkar: 00:30:41

you can train your model for, say, music inspired by Taylor Swift or say Dua Lipa.

Amit Sarkar: 00:30:46

But then you have to ensure that you're not violating any copyright

Amit Sarkar: 00:30:50

laws, because even in workplace, you can do whatever you want as long as

Amit Sarkar: 00:30:54

you're not violating copyright laws and you're not violating any GDPR laws.

Amit Sarkar: 00:30:58

Because if you are using confidential information off some other people,

Amit Sarkar: 00:31:03

then that just violates all these things and, your job will be at

Amit Sarkar: 00:31:06

risk, so be smart about it as well.

Rinat Malik: 00:31:09

Absolutely I think we've gone through many examples

Rinat Malik: 00:31:12

of how to use AI to augment your performance and how it impacts the

Rinat Malik: 00:31:18

society in terms of job availability.

Rinat Malik: 00:31:21

the main point of our talk today was that, it's not completely unfounded

Rinat Malik: 00:31:27

that there is a shift of how useful you can be in what way, to a company

Rinat Malik: 00:31:32

to keep your job, but then in no way is it a like a done deal where this is it.

Rinat Malik: 00:31:38

it's just an opportunity for us to upskill ourselves more, to make our

Rinat Malik: 00:31:43

jobs more interesting and more creative and expand upon more from the basic

Rinat Malik: 00:31:48

output that we can now easily generate.

Rinat Malik: 00:31:51

Now let's take this as an opportunity and rise to towards our new challenge

Rinat Malik: 00:31:57

and produce more, produce better, produce faster whatever it is that

Rinat Malik: 00:32:02

we are producing in whichever job.

Amit Sarkar: 00:32:04

be smart about using AI and definitely start using the AI

Amit Sarkar: 00:32:07

tools and start gauging what are the different tools in the market, how

Amit Sarkar: 00:32:11

you can use it and what benefit it is.

Amit Sarkar: 00:32:13

I think a lot of tools will surprise you initially, and once you

Amit Sarkar: 00:32:16

cross the o wow, this is magical.

Amit Sarkar: 00:32:19

I think once you cross that threshold, then you'll realize the limitations.

Amit Sarkar: 00:32:22

It's only when you start using certain tools in certain ways

Amit Sarkar: 00:32:24

that you realize the limitations.

Amit Sarkar: 00:32:26

But if you don't use it, you'll never realize it.

Amit Sarkar: 00:32:27

You'll always think it's magic if you use a tool once you think it's magic.

Amit Sarkar: 00:32:31

But the more you use the tool, you think it's not magic,

Amit Sarkar: 00:32:33

there is algorithm behind it.

Amit Sarkar: 00:32:35

you can tweak the prompt to make sure that the algorithm gives

Amit Sarkar: 00:32:39

you the output that you desire.

Amit Sarkar: 00:32:41

So you can do all that, but in the end, it's not magic.

Amit Sarkar: 00:32:44

It's just mathematics.

Amit Sarkar: 00:32:46

I've used a lot of tools and I've, I've attended a lot of sessions on

Amit Sarkar: 00:32:49

different AI tools and I can say that these tools are not that intelligent.

Amit Sarkar: 00:32:53

They can do something specific things really well.

Amit Sarkar: 00:32:56

So if you are involved in something very specific, like you

Amit Sarkar: 00:32:59

have to do the same thing every day, say you're just generating

Amit Sarkar: 00:33:02

logos, your job might be at risk.

Amit Sarkar: 00:33:05

In case you start using AI tools to generate more images.

Amit Sarkar: 00:33:09

So if you do a very specific task, your job might be at risk.

Rinat Malik: 00:33:12

specific repetitive job was at risk, even before as

Rinat Malik: 00:33:15

well because of automation anyway.

Amit Sarkar: 00:33:18

But now with ai, it's the creative aspect as well.

Amit Sarkar: 00:33:20

So suppose you write contracts and you write only specific

Amit Sarkar: 00:33:22

contracts, then it's at risk.

Amit Sarkar: 00:33:25

But if you write specialized contracts, which changes based

Amit Sarkar: 00:33:28

on need, then it's not at risk.

Amit Sarkar: 00:33:30

Tailored made, So I I think a lot of the AI tools in the market

Amit Sarkar: 00:33:33

now are catering to personalized experience, personalized solutions,

Amit Sarkar: 00:33:36

that's where the market is heading, and it's quite an exciting future.

Amit Sarkar: 00:33:40

if we all embrace AI rather than looking at it as a threat.

Amit Sarkar: 00:33:44

if you look at it as a, as a tool to augment us, think it's a,

Amit Sarkar: 00:33:48

it's a huge benefit for all us.

Rinat Malik: 00:33:50

I would echo what you said, Amit, that definitely use all the

Rinat Malik: 00:33:53

different tools that are out out there.

Rinat Malik: 00:33:55

Most of them have a free tier rather than the paid subscription.

Rinat Malik: 00:33:59

And you can see all the different ways AI can be used

Rinat Malik: 00:34:03

So it will open your eyes on, the limitation of it.

Rinat Malik: 00:34:06

And I have spoken to many people about this as well, and I'm surprised,

Rinat Malik: 00:34:09

obviously the initial hype of chat GPT was, like so many users faster

Rinat Malik: 00:34:14

than Facebook and everyone, but then.

Rinat Malik: 00:34:17

Not a lot of people uses tools like chat GPT as much as they could.

Rinat Malik: 00:34:21

Right?

Rinat Malik: 00:34:22

they've gone back to Yeah, the hype is finished.

Rinat Malik: 00:34:24

We do use it sometimes, but a lot of the times we don't even think about.

Rinat Malik: 00:34:27

even if you wanna reply to a very a sensitive text on WhatsApp my wife was

Rinat Malik: 00:34:32

having to do that and I said, Hey, why don't you use chat GPT on your phone?

Rinat Malik: 00:34:36

There is an app You can just literally copy and paste the text you received and.

Rinat Malik: 00:34:40

get, get your response written down in the correct tone that you want to so you don't

Rinat Malik: 00:34:46

have to overthink things and all of that.

Rinat Malik: 00:34:48

So many ways you can use it.

Rinat Malik: 00:34:51

Definitely would encourage everyone to explore, take some time every

Rinat Malik: 00:34:54

week to see, like, put, put yourself down for one evening and just search.

Rinat Malik: 00:35:00

On Google on different AI solutions.

Rinat Malik: 00:35:02

There is a website which I don't remember the exact name, but it's

Rinat Malik: 00:35:06

called, there is an AI for that.

Rinat Malik: 00:35:08

And there's thousands of different AI tools all cataloged over there.

Rinat Malik: 00:35:12

So you can see all the things that are possible.

Rinat Malik: 00:35:15

So definitely explore, know how to prompt in a way that you get predictable

Rinat Malik: 00:35:20

output and that way you can use it to your advantage and go a lot forward, a

Rinat Malik: 00:35:27

lot faster and make a big difference.

Rinat Malik: 00:35:30

So with that thought yeah we had a really nice conversation.

Rinat Malik: 00:35:33

Please do reach out if you guys want us to go through any particular AI tool and

Rinat Malik: 00:35:37

we would be happy to do that as well.

Amit Sarkar: 00:35:39

Thanks so much everyone.

Amit Sarkar: 00:35:41

See you next week.

Amit Sarkar: 00:35:42

Bye.

Rinat Malik: 00:35:43

Bye.