June 22, 2025
From Cloud Architect to AI Specialist: Naveen Krishnan's Microsoft Journey
Welcome to episode 33 of the Designing with Love podcast! In this episode, I had the pleasure of interviewing Naveen Krishnan, an expert in the AI technology and cloud computing field.
What does the future of work look like when AI becomes your daily assistant? Microsoft AI Solutions Architect Naveen Krishnan offers a compelling glimpse into this reality, sharing how artificial intelligence already handles 30-40% of his daily tasks—and why that percentage will likely reach 70-80% soon.
Naveen's 16-year journey from electronics engineering in India to his current specialized AI role at Microsoft provides valuable context for understanding how rapidly technology careers can evolve. After working with global companies like PepsiCo, JP Morgan Chase, and Capital One, he joined Microsoft in 2021, initially as a Cloud Architect before diving deep into artificial intelligence. His passion for continuous learning—encapsulated in his philosophy that "what I know is just 1% and what I don't know is 99%"—has driven him to write technical blogs, develop AI applications, and even author a comprehensive 350-page book on AI fundamentals and applications.
For instructional designers and educators, Naveen offers practical advice: experiment with AI tools across all aspects of your work now, while the technology is still evolving. He encourages approaching repetitive or time-consuming tasks with the question: "Is there an AI tool that could help me do this more efficiently?" This mindset, combined with staying current on industry developments, positions professionals to thrive in an increasingly AI-enhanced workplace.
🔗Website and Social Links:
Please visit Naveen's website and social media links below.
Naveen's Technical Blog on Medium
Join PodMatch!Use the link to join PodMatch, a place for hosts and guests to connect.
Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.
💟Designing with Love + allows you to support the show by keeping the mic on and the ideas flowing. Click on the link above to provide your support.
☕Buy Me a Coffee is another way you can support the show, either as a one-time gift or through a monthly subscription.
🗣️Want to be a guest on Designing with Love? Send Jackie Pelegrin a message on PodMatch, here: Be a guest on the show
📝Check out the companion blog site here: Designing with Love Blog
📱Send a text to the show by clicking the Send Jackie a Text link above.
👍🏼Please make sure to like and share this episode with others. Here's to great learning!
00:01 - Introduction to Naveen Krishnan
03:34 - Career Journey and Microsoft Role
08:04 - AI Applications in Enterprise Systems
15:03 - AI as a Daily Work Assistant
20:26 - Continuous Learning Approach
23:47 - Tips for Instructional Designers
WEBVTT
00:00:01.040 --> 00:00:04.107
Hello and welcome to the Designing with Love podcast.
00:00:04.107 --> 00:00:11.752
I am your host, Jackie Pelegrin, where my goal is to bring you information, tips and tricks as an instructional designer.
00:00:11.752 --> 00:00:20.080
Hello, GCU students, alumni and educators, welcome to episode 33 of the Designing with Love podcast.
00:00:20.080 --> 00:00:22.751
Today, I have the pleasure of interviewing Naveen Krishnan, an expert in the information technology field at Microsoft.
00:00:22.751 --> 00:00:22.911
Welcome.
00:00:22.911 --> 00:00:27.123
I have the pleasure of interviewing Naveen Krishnan, an expert in the information technology field at Microsoft.
00:00:27.123 --> 00:00:28.166
Welcome, Naveen.
00:00:29.126 --> 00:00:42.426
Hey, jackie, nice meeting you and your team of podcast, so I'm very glad to see you all and your audience and looking forward to see what you have for me.
00:00:42.887 --> 00:00:44.933
Great, thank you, thank you.
00:00:44.933 --> 00:00:50.305
So can you tell us a little bit about yourself, maybe personally and professionally, definitely.
00:00:50.326 --> 00:01:01.171
So I started my career 15, 16 years back and I started back in India and I worked for a small.
00:01:01.171 --> 00:01:15.073
I completed my engineering in electronics and communication and then I went into a one-year rigorous course learning all IT systems and programming skills and things like that.
00:01:15.073 --> 00:01:22.185
So after getting that knowledge, I joined a small startup company back in India and I worked there for a year.
00:01:22.185 --> 00:01:29.787
We were developing some HR systems and then I moved on to a product-based company so that's an account payable process.
00:01:29.787 --> 00:01:40.694
So I stayed there for around two, three years maybe, and after that I joined a consulting firm where my customers are UK-based.
00:01:41.301 --> 00:01:48.840
I worked for Ricoh and I worked for PepsiCo, uk based.
00:01:48.840 --> 00:01:53.472
I work for rico and I work for pepsico, and then I work for jpmc, capitol one, morgan shanley and delanco so many other customers.
00:01:53.472 --> 00:01:57.561
So that's where uh, that's what my journey with uh, that consulting company.
00:01:57.561 --> 00:02:02.168
I shared that for around nine years and then in between I moved to US in 2015.
00:02:02.168 --> 00:02:13.527
Since 2015, I landed in Dallas, texas, and I'm here still, and I joined Microsoft in 2021, maybe I'm here for the last three years now.
00:02:14.759 --> 00:02:15.603
Yeah, I do a lot of.
00:02:15.603 --> 00:02:25.706
I joined as a cloud architect and then I got myself interested into AI and now I'm here as a solutions architect specialized in AI space.
00:02:26.520 --> 00:02:27.444
Wow, that's great.
00:02:27.444 --> 00:02:32.871
You've had quite a journey and now you've been here in the United States for 10 years, so that's exciting.
00:02:32.871 --> 00:02:33.633
Wow.
00:02:33.633 --> 00:02:35.305
And so you've been at Microsoft three years.
00:02:35.305 --> 00:02:36.429
Wow, that's great.
00:02:36.429 --> 00:02:40.931
So you're really seeing AI take off and things like that.
00:02:40.931 --> 00:02:42.447
So how did you become interested?
00:02:42.447 --> 00:02:50.562
Did this position at Microsoft just kind of did it land on your lap in a sense, or were you looking, or how did that?
00:02:50.603 --> 00:02:51.044
come about.
00:02:51.044 --> 00:03:21.325
No, so my initial days when I was with a consulting firm, I worked for several customers and then we did a lot of cloud migration-related work and that helped me get into Microsoft and the main reason is I was at the center of excellence there and the center of excellence team and I managed a complete azure and I was the first one to get certified as a cloud solutions architect at my consulting company and yeah that.
00:03:21.325 --> 00:03:25.274
So customer sizes are like very huge.
00:03:25.274 --> 00:03:34.832
So at some point we design migration of 800 apps and we design migrations or we re-architect, re-factor.
00:03:34.832 --> 00:03:40.625
I worked on all three or four hours basically restructuring, re-architecting, re-factoring and things like that.
00:03:40.625 --> 00:03:45.231
So these things helped me get through Microsoft very quick.
00:03:45.231 --> 00:03:47.425
So that was not easy.
00:03:47.979 --> 00:03:52.586
A lot of preparation became the scenes and slowly I landed here.
00:03:52.586 --> 00:03:59.050
And after getting into this role, I still continue to be as a cloud engineer.
00:03:59.050 --> 00:04:04.472
And after a year or two maybe, I got myself into AI.
00:04:04.472 --> 00:04:06.554
That's when AI emerged.
00:04:06.554 --> 00:04:15.348
I won't say AI emerged, but that's when the generative AI stuff came out, and then AI became a talk.
00:04:16.081 --> 00:04:18.088
And I started learning a lot of things around AI.
00:04:18.088 --> 00:04:26.761
I went back and then I did a lot of courses around machine learning and deep learning and whatnot Right so?
00:04:26.761 --> 00:04:29.927
And I got myself into data as well.
00:04:29.927 --> 00:04:40.584
So in parallel I worked on data as well as AI, so that made me very easy to land here safe, and so for the last one year I went to AI completely.
00:04:40.584 --> 00:04:54.233
So For the last one year I've been doing AI completely Designing AI applications, helping to build AI solutions, identifying AI use cases and whatnot Everything about AI.
00:04:54.233 --> 00:04:56.995
I'm writing research papers on AI.
00:04:56.995 --> 00:04:59.898
I write my own technical blogs on AI completely AI.
00:04:59.898 --> 00:05:04.862
I do AI podcasts.
00:05:04.862 --> 00:05:07.625
Yeah, I almost think I'm covering everything.
00:05:07.644 --> 00:05:16.271
So you're immersed in the AI technology generative AI and all of that and the chatbots and how that can help all the different industries.
00:05:16.271 --> 00:05:20.375
Because as I read your profile, I was like, wow, this is amazing.
00:05:20.375 --> 00:05:21.836
So that's so cool.
00:05:21.836 --> 00:05:33.026
So what's one of the most exciting projects you've worked on at Microsoft where you've utilized AI technology to create personalized learning experiences, maybe for students or for even learners in general?
00:05:33.666 --> 00:05:38.665
Yeah, sure, so I can talk in general, basically.
00:05:38.665 --> 00:05:46.848
So there is one other good example which my colleague in UK is working on, so maybe I'll talk about that, so that will be more interesting.
00:05:46.848 --> 00:05:56.862
So, for example, what they are doing is they are using agents AI agents, basically to completely monitor their cloud infrastructure.
00:05:56.862 --> 00:06:04.281
So, for example, as we work on IT systems right, so these systems are meant to run 24 per 7.
00:06:04.281 --> 00:06:08.702
So there is no risk for my apps or my data or whatever.
00:06:08.702 --> 00:06:09.204
It is right.
00:06:09.204 --> 00:06:11.687
So there are problems.
00:06:12.242 --> 00:06:19.987
Sometimes you see issues at midnight and sometimes your application crashes or your database goes down or things like that.
00:06:19.987 --> 00:06:26.267
So you have to get into a call First, you have to troubleshoot where the problem is and then try to fix those things.
00:06:26.267 --> 00:06:30.666
So that takes several hours, basically, and there is no proactive approach yet.
00:06:30.666 --> 00:06:44.211
So, with this help of AI agent implementation, they are automating these end-to-end systems so agents can identify proactively, based on the previous knowledge or data, whatever it has got.
00:06:44.211 --> 00:07:01.848
So it identifies the problem and proactively senses it and then it tries to remediate by itself with all the list of instructions, what we have provided and the level of control, what it can do, basically, and so once it fixes.
00:07:01.848 --> 00:07:02.911
It keeps human in loop.
00:07:02.911 --> 00:07:07.612
So it will just alert someone, like there is something happened and then they fixed it.
00:07:07.612 --> 00:07:26.850
And if it couldn't, then it will give you the list of steps, what you can perform, which agent doesn't have control to, and then pick you up in the night and then it will just consult with you whether should I take this recommendation and what are the plus and minus if I do this.
00:07:26.850 --> 00:07:31.108
So, if you just agree, it's going to perform this task for you.
00:07:31.108 --> 00:07:34.971
So that's the level of automation with agents, what they are planning on.
00:07:34.971 --> 00:07:36.687
It's a very interesting solution.
00:07:36.687 --> 00:07:47.408
It may be a very simple use case, but if this gets succeeded in one enterprise, then several of those enterprises may even follow this same thing.
00:07:47.408 --> 00:07:57.946
So this is one interesting use case, what I recently got from my friend, and apart from that, you can use AI in any of these wherever you can.
00:07:58.100 --> 00:08:01.807
First, you can think of increasing it, increasing the customer experience, maybe.
00:08:01.807 --> 00:08:23.649
So, for example, I call my cell phone provider, or there is an effort provider, my entrant is down and I call them and I have to wait for like around 30 minutes to get a technician on my call, because the technician is working on the things that are like a Q&A type of questions.
00:08:23.649 --> 00:08:33.870
For example, they are loaded with 300 calls at a time and there are only 80 technicians out there and out of 300 calls maybe 200 are just FAQs.
00:08:33.870 --> 00:08:37.289
So you can just repeat based on the knowledge base.
00:08:37.289 --> 00:08:48.706
So those types of things heavy lifting can be handled by AI so that other cases, other problems which are really valid, so that can be put into a technician directly.
00:08:48.706 --> 00:09:05.683
So these types of things where you can start with basically we call it as the AI bot or AI chat bot, anything like that where you can chat with AI and then see if this is an existing problem or a known solution, then AI can fix it for you and if not, it will escalate it to a next level.
00:09:05.683 --> 00:09:06.686
So you can start there.
00:09:07.147 --> 00:09:14.001
And with agents, you have automated tasks so we can automate your task basically.
00:09:14.001 --> 00:09:25.452
So day-to-day tasks for example, I come in and then I read my emails and I, I I kind of figure out how my day is going to be and then I do a lot of analysis on my meetings and what to talk and whatnot.
00:09:25.452 --> 00:09:42.347
So those types of preparations, they can help them, they can help you and apart from that, it can help write your emails and if you have office respect, uh, all your office 365 is now embedded with Copilot and if you have those capabilities, then it can draft your emails as well.
00:09:42.347 --> 00:09:46.629
So you don't have to wait, sit, spend an hour to draft those notes.
00:09:46.629 --> 00:09:54.892
So these are the capabilities, or what I am seeing, and if you are a hard core developer, you can make yourself hit up Copilot.
00:09:54.912 --> 00:10:04.177
So at least in a IT day to day work, in 30 to 40 percent of my work is now closely with AI.
00:10:04.177 --> 00:10:10.839
So basically, this 30-40% of my work, ai is my assistant.
00:10:10.839 --> 00:10:14.395
So that is sitting next to me and then it is assisting for framing emails.
00:10:14.395 --> 00:10:18.371
If I miss a meeting, it gets my summarization and whatnot.
00:10:18.371 --> 00:10:29.234
So it's going to evolve soon and then close to 70, 80% of your day on what you do, a is going to be your assistant for those tasks.
00:10:29.234 --> 00:10:32.634
So this is what I see basically.
00:10:32.634 --> 00:10:35.575
Maybe it's a lengthy answer, but I think I covered all the pieces.
00:10:36.145 --> 00:10:37.270
Yeah, that's great.
00:10:37.270 --> 00:10:52.615
So you're really seeing that AI is becoming that assistant and coming alongside people, right, so that they can take those, as some people call them, mundane tasks, those everyday tasks like writing an email and making it to where it's simpler.
00:10:52.615 --> 00:10:56.158
And there can be those automated tasks, right, that AI can do.
00:10:56.158 --> 00:10:57.340
So I love that.
00:10:57.340 --> 00:10:59.660
I like that idea, too, of the chat bot.
00:10:59.660 --> 00:11:09.594
I know I've interacted with some chat bots on some websites where it'll help you to see, okay, is this something that's more general that the AI chat bot can help you solve?
00:11:09.594 --> 00:11:17.114
And then, like you said, if it is something more complicated, then it can go to a live agent and they can help them with it.
00:11:17.114 --> 00:11:20.230
So it helps to eliminate that a lot of that busy work for them.
00:11:20.230 --> 00:11:29.669
Probably, so that it it helps to eliminate that, uh, a lot of that uh busy work for them, probably so that they don't have to take calls that they don't necessarily need to take, and then it frees up some of that time as well.
00:11:30.251 --> 00:11:31.153
Wow, that's amazing.
00:11:31.153 --> 00:11:34.287
I love that, yeah, cause I used to work in a call.
00:11:34.287 --> 00:11:47.738
I used to work in a couple of call centers before I worked at um, at Discover Card, which is part of Morgan Stanley and I worked in a call center there in the early 2000s and then that was when we were migrating computer systems.
00:11:47.738 --> 00:11:53.998
So I just think of wow, if AI was around, then it would have been amazing to have all of that.
00:11:53.998 --> 00:12:10.692
And then I also worked for Vanguard, which is a financial institution, so it would have been pretty amazing to have all of that, instead of having all these calls come in of general questions where they could have gone to the website right and found that information.
00:12:10.692 --> 00:12:12.277
So that's great.
00:12:12.477 --> 00:12:12.860
Wow.
00:12:12.860 --> 00:12:20.416
So you're really seeing the future of AI, it's really expanding, and that's amazing.
00:12:20.416 --> 00:12:22.359
Wow, that's wonderful.
00:12:22.359 --> 00:12:38.631
So it sounds like you're even in a leadership role and what you do too, because you're helping to lead these projects, and so there are different types of styles and skills that you find helpful in your daily work there at Microsoft that you think are really helpful, especially in this type of work you do.
00:12:39.465 --> 00:12:52.636
Yeah, so usually I don't follow something standard or a specific style, but what I do is I kind of take every opportunity and see how we can be better or good at it.
00:12:52.636 --> 00:12:58.254
So every chance what you get is learning.
00:12:58.254 --> 00:13:05.943
So I always have this mindset of what I know is just 1% and what I don't know is 99%.
00:13:05.943 --> 00:13:10.969
So that always keeps you learning and I don't myself.
00:13:10.969 --> 00:13:15.009
I don't think that I know everything, so I still don't know anything.
00:13:15.009 --> 00:13:29.091
So I will keep on hunting and then spend most of my time learning and helping others who are learning, basically so writing some technical blogs and I'm in fact, writing a book on AI.
00:13:29.110 --> 00:13:47.347
So it is just covers everything, basically so who is just from a different field and then wanted to jump into this and wanted to know more about AI and how it evolved and what is machine learning, what is deep learning and what is neural networks and what is this right?
00:13:47.347 --> 00:13:53.187
So it kind of covers everything and what is agent and what is the multi-agent system and how do you design that.
00:13:53.187 --> 00:13:54.471
So it covers end to end.
00:13:54.471 --> 00:13:55.995
So that book is around.
00:13:55.995 --> 00:13:59.067
It's getting what you say.
00:13:59.067 --> 00:14:01.254
The publisher is actually working on it.
00:14:01.254 --> 00:14:09.048
Once it is out, maybe that will help you land in English.
00:14:09.048 --> 00:14:15.357
I took that opportunity and after I wrote around 30-40 blocks then I kind of thought, okay, what's next?
00:14:15.357 --> 00:14:18.827
Then I jumped into it and I started writing my own book.
00:14:19.450 --> 00:14:20.693
Wow, that's wonderful.
00:14:21.664 --> 00:14:30.770
This is of making every opportunity for you to grow and evolve.
00:14:30.770 --> 00:14:31.594
So that's what I do.
00:14:34.267 --> 00:14:35.893
It's like a continuous learning culture.
00:14:35.893 --> 00:14:40.267
Right, you're constantly learning because technology is always changing.
00:14:40.267 --> 00:14:48.489
I was talking to someone earlier about that and we yeah, those emerging technologies are yeah it's amazing that interest.
00:14:48.509 --> 00:15:06.990
So as soon as you see something new out there, I would say you go try it and then see what's what's in there and then what it can do, so that having that knowledge will definitely help you, help you as well as help others when you share those learnings.
00:15:06.990 --> 00:15:13.635
So that's one thing, what I do, and apart from that I do a lot of hands on work.
00:15:13.635 --> 00:15:19.668
So I develop applications, I develop code, and then if there is something which I can automate physically, then I'll try to.
00:15:19.668 --> 00:15:20.071
I even try to create some games.
00:15:20.071 --> 00:15:20.892
Is something which I can automate physically, then I'll try to.
00:15:20.892 --> 00:15:25.215
I even try to create some games for me which I am interested on.
00:15:25.215 --> 00:15:26.740
So it keeps going.
00:15:26.740 --> 00:15:28.102
So, yeah, that's how.
00:15:28.705 --> 00:15:34.022
If you, if you are interested and then if you are eager to do more, then don't hesitate.
00:15:34.022 --> 00:15:38.751
So this is the right time for you to, because it's just evolved right.
00:15:38.751 --> 00:15:42.298
So we just crossed only two years of this uh a channel.
00:15:42.298 --> 00:15:53.393
So if, if you start uh getting uh the grasp of it, then it's like computer, like how you get it got into a computer before when it started, right.
00:15:53.393 --> 00:16:02.609
So those who don't know how to use computers, so they are now struggling to get into it and start using all their apps and everything.
00:16:02.609 --> 00:16:03.974
It's a similar thing.
00:16:03.974 --> 00:16:15.653
So if you try to stay out of it, then you are not going to be part of this and then enjoy the developments, for what will be happening around you.
00:16:18.047 --> 00:16:18.769
Wow, that's exciting.
00:16:18.769 --> 00:16:19.533
So when are you planning to?
00:16:31.755 --> 00:16:32.596
release your book.
00:16:32.596 --> 00:16:35.639
Is it going to be coming out soon?
00:16:35.639 --> 00:16:41.124
Got pulled into several other things and then I tried to complete it in spring and it's not possible.
00:16:41.124 --> 00:16:47.633
And finally, for this summer I have completed and now it's waiting for this peer review and things like that.
00:16:47.633 --> 00:16:52.813
So once it's all complete, maybe it will be out in two months, maybe.
00:16:53.666 --> 00:16:54.168
That's good.
00:16:54.168 --> 00:16:57.111
Wow, so you got it to where you need it.
00:16:57.111 --> 00:16:58.809
Now it's going through peer review.
00:16:58.809 --> 00:16:59.826
That's great, wonderful.
00:16:59.846 --> 00:17:02.279
Yeah, it's a 300-page book, so 350-page book.
00:17:02.279 --> 00:17:06.436
So it's not easy to get it to a good place and then take it to market.
00:17:06.436 --> 00:17:08.539
It takes its own time to.
00:17:11.248 --> 00:17:12.190
That's exciting, wow.
00:17:12.309 --> 00:17:30.997
Maybe once you get it released you can come back on the podcast and kind of talk a little bit through some of the elements, yeah, and then we can focus on the AI technology and by then, you know, it'll be kind of neat to see how things like you know, because you know most companies have Microsoft already built in, microsoft already built in.
00:17:31.017 --> 00:17:42.247
So we're at first, when we had Microsoft and where I work at our company, the copilot was disabled.
00:17:42.247 --> 00:17:44.791
But now they've got copilot enabled and I'm seeing it embedded in everything.
00:17:44.791 --> 00:17:48.446
So it's really neat to see that it's in Outlook and it's in Word and all of that.
00:17:48.446 --> 00:17:55.439
So it's pretty neat to see that it's there and it's a good assistant, because we do have an internal tool.
00:17:55.439 --> 00:17:59.394
But they say that Copilot is safe to use within the organization as well.
00:17:59.394 --> 00:18:10.513
So it's nice to know that we have options and that we don't have to use an external tool that potentially could have proprietary information that could get out there, because we don't want that.
00:18:10.513 --> 00:18:15.035
So it's great to have Copilot embedded into all of Microsoft now.
00:18:15.035 --> 00:18:16.086
So it's great.
00:18:16.468 --> 00:18:25.460
You can also do it in the work mode, so that if you need to know about any policy information whether what is my insurance plan and things like that you can ask it.
00:18:25.460 --> 00:18:28.147
So it will be within your company.
00:18:28.147 --> 00:18:42.035
So instead of waiting for HR to respond back and that takes a day and instead of that I use it if I need to know some policy information of whether I can share this or not and what, so you can get all this from the work mode.
00:18:43.767 --> 00:18:44.811
Oh, wow, that's good to know.
00:18:44.811 --> 00:18:46.213
Wow, I love that it's.
00:18:46.255 --> 00:18:53.420
M365 for pilots and we can just install it and make this office so that is integrated with your complete Office 365 ecosystem.
00:18:53.420 --> 00:18:53.803
So spreadsheets, sharepoints, excel, word.
00:18:53.803 --> 00:18:54.388
Solve it and make this so that is integrated with your complete office system.
00:18:54.388 --> 00:19:05.898
So spreadsheets, sharepoints, excel, words and your enterprise data which you have access to.
00:19:05.898 --> 00:19:18.093
Basically, what it uses is on behalf of access, so, which means whatever access you have, it takes that level of access and then it go find data which is related to you and which is accessible.
00:19:18.874 --> 00:19:21.257
Oh, wow, that's one thing.
00:19:21.257 --> 00:19:22.659
That's amazing.
00:19:22.659 --> 00:19:23.420
I love that.
00:19:23.420 --> 00:19:26.730
Wow, I'll have to pass that on because I know our IT.
00:19:26.730 --> 00:19:32.078
They check, you know, all the different systems and internally and as things get released out.
00:19:32.078 --> 00:19:34.772
So yeah, so I'll have to look into that.
00:19:34.772 --> 00:19:40.316
And Microsoft recently went through an update I think it was Friday, so yesterday.
00:19:40.316 --> 00:19:43.290
So I'll have to check into that, yeah definitely.
00:19:43.490 --> 00:19:44.433
Yeah, that's great.
00:19:44.433 --> 00:19:53.476
So, as you know, my students are mostly instructional design students, but I also have novice instructional designers.
00:19:53.476 --> 00:19:58.410
I have listeners from all over the world, which I never expected with this podcast, but so there's.
00:19:58.410 --> 00:20:13.789
Are there any tips and advice you can share with those who are currently in the master's program and instructional design at Grand Canyon University that maybe are thinking of utilizing AI technology or they're not sure where to start when it comes to learning and and and those types of areas?
00:20:14.512 --> 00:20:15.154
Yeah, sure.
00:20:15.154 --> 00:20:22.451
So what I would say is it's better to try AI in all aspects of what you are doing.
00:20:22.451 --> 00:20:40.112
So because the future for next two, three years it's completely going to be AI and you will see a lot of developments around AI, a lot of things happening around AI, and so this is the right time for you to grasp and then learn stuff, what's out there, and make use of all the tools.
00:20:40.244 --> 00:20:42.232
There are plenty of tools that's available out there.
00:20:42.232 --> 00:20:48.555
So make use of all the tools for whatever you're doing and if you're making designing right.
00:20:48.555 --> 00:20:56.296
So, for example, I see I don't remember the name so there's a website called Napkin AI, I think so.
00:20:56.296 --> 00:21:03.596
So you just fill in your text content, it can update an image for you, design for you, whatnot?
00:21:03.596 --> 00:21:06.515
So there are several tools and things that's available.
00:21:06.515 --> 00:21:08.792
Make use of all the tools.
00:21:08.845 --> 00:21:19.442
So, whenever you get stuck somewhere and then you're doing some tedious job like it takes five days or ten days then first thing that comes to my mind comes to your mind is whether can I leverage it?
00:21:19.442 --> 00:21:24.823
Is there any tools that's readily available which can do all this instead of me doing it manually?
00:21:24.823 --> 00:21:30.162
So ask this question every time when you get into such a difficult task or anything.
00:21:30.162 --> 00:21:31.747
So there are plenty of tools available.
00:21:31.747 --> 00:21:40.550
Only thing is you want to explore something and then figure out which tool fits best for you for all your needs.
00:21:40.550 --> 00:21:54.154
Make use of those tools, liberate them as and when needed and keep yourself updated on all the trends that's happening and new innovation that's coming out.
00:21:54.154 --> 00:22:08.984
Just watch and eye on it and follow people who are at C levels on all these big companies so that you know what is coming out, so which feature or what development is happening around there.
00:22:08.984 --> 00:22:13.404
So follow them and then read them, read what they have been, so keep yourself updated.
00:22:13.404 --> 00:22:14.707
So keep yourself updated.
00:22:14.707 --> 00:22:17.549
So that's a recommendation, what I would say at this time.
00:22:18.451 --> 00:22:19.352
Right, that's great.
00:22:19.352 --> 00:22:24.717
Yeah, just keeping yourself up to date on the technology and knowing what's out there, right, that's that's great.
00:22:24.717 --> 00:22:52.394
Yeah, because there are definitely, I agree, a lot of tools out there and it's hard sometimes for us to know what's, what's going to be a good tool and not, um, but you know, even maybe, like you were kind of mentioning, kind of experimenting right with those tools and seeing will it work or will it not, because you don't know right until you try it and see how it's going to work and I yeah, I've done that before, I've tried something, and I'm like I don't know, but it seems like the text to image is getting better than what it used to be.
00:22:52.413 --> 00:22:58.394
It used to be where I had some students do that and it was so obvious that it was an AI image.
00:22:58.394 --> 00:23:03.191
I was like, wow, the hands don't look right on the person and the eyes look off.
00:23:03.191 --> 00:23:05.432
But now it seems like it's much better.
00:23:05.545 --> 00:23:06.796
I had another student that did that.
00:23:06.796 --> 00:23:07.622
Yeah, it's far better now.
00:23:07.622 --> 00:23:09.431
Yeah, it's good, I love it.
00:23:16.825 --> 00:23:17.547
So I use that for my book session.
00:23:17.547 --> 00:23:18.509
So okay, so check that out, that's cool.
00:23:18.509 --> 00:23:26.893
Yeah, I had a student that used um, adobe um for hers and she did a presentation and all of the images were ai generated images and I was like, wow, they look so realistic.
00:23:26.893 --> 00:23:28.998
I'm like that's, that's amazing, it's come.
00:23:28.998 --> 00:23:30.105
It's come a long way.
00:23:30.145 --> 00:23:52.338
I think they keep improving the technology and even with the machine learning right and the AI generation and how it's able to kind of pick up on your tone and your style of how you're doing things I've noticed that with chat, gpt it's gotten better Copilot's gotten better with that and recognizing that, okay, this is the tone that you want and I can kind of pick up on that.
00:23:52.338 --> 00:24:02.759
And then you don't have to tell it so many things or ask it so many things, that what you need, it can really pick up on that tone and that that voice that you're looking for as well.
00:24:02.759 --> 00:24:09.031
So it's really great and having that conversation with the AI and no, this isn't quite right, this is where I wanted to go.
00:24:09.031 --> 00:24:13.417
And then it can shift and it can say, okay, I'm sorry, I was wrong, let me change it.
00:24:13.417 --> 00:24:15.760
So it's kind of neat how it can do that.
00:24:16.265 --> 00:24:18.675
Yeah that's great, wonderful.
00:24:18.675 --> 00:24:19.619
Thank you, naveen.
00:24:19.619 --> 00:24:22.594
Is there any other thoughts or ideas you'd like to share before we wrap up?
00:24:24.266 --> 00:24:32.329
So what I would say is follow me on LinkedIn, so it's N-A-V-I-N-T-K-R, so that's my LinkedIn handle, and so that's my LinkedIn handle, and that's my GitHub handle as well.
00:24:32.329 --> 00:24:38.519
And if you wanted to read my blogs, then I would say AI with Navin Krishnan.
00:00:01.040 --> 00:00:04.107
00:00:04.107 --> 00:00:11.752
00:00:11.752 --> 00:00:20.080
00:00:20.080 --> 00:00:22.751
00:00:22.751 --> 00:00:22.911
00:00:22.911 --> 00:00:27.123
00:00:27.123 --> 00:00:28.166
00:00:29.126 --> 00:00:42.426
00:00:42.887 --> 00:00:44.933
00:00:44.933 --> 00:00:50.305
00:00:50.326 --> 00:01:01.171
00:01:01.171 --> 00:01:15.073
00:01:15.073 --> 00:01:22.185
00:01:22.185 --> 00:01:29.787
00:01:29.787 --> 00:01:40.694
00:01:41.301 --> 00:01:48.840
00:01:48.840 --> 00:01:53.472
00:01:53.472 --> 00:01:57.561
00:01:57.561 --> 00:02:02.168
00:02:02.168 --> 00:02:13.527
00:02:14.759 --> 00:02:15.603
00:02:15.603 --> 00:02:25.706
00:02:26.520 --> 00:02:27.444
00:02:27.444 --> 00:02:32.871
00:02:32.871 --> 00:02:33.633
00:02:33.633 --> 00:02:35.305
00:02:35.305 --> 00:02:36.429
00:02:36.429 --> 00:02:40.931
00:02:40.931 --> 00:02:42.447
00:02:42.447 --> 00:02:50.562
00:02:50.603 --> 00:02:51.044
00:02:51.044 --> 00:03:21.325
00:03:21.325 --> 00:03:25.274
00:03:25.274 --> 00:03:34.832
00:03:34.832 --> 00:03:40.625
00:03:40.625 --> 00:03:45.231
00:03:45.231 --> 00:03:47.425
00:03:47.979 --> 00:03:52.586
00:03:52.586 --> 00:03:59.050
00:03:59.050 --> 00:04:04.472
00:04:04.472 --> 00:04:06.554
00:04:06.554 --> 00:04:15.348
00:04:16.081 --> 00:04:18.088
00:04:18.088 --> 00:04:26.761
00:04:26.761 --> 00:04:29.927
00:04:29.927 --> 00:04:40.584
00:04:40.584 --> 00:04:54.233
00:04:54.233 --> 00:04:56.995
00:04:56.995 --> 00:04:59.898
00:04:59.898 --> 00:05:04.862
00:05:04.862 --> 00:05:07.625
00:05:07.644 --> 00:05:16.271
00:05:16.271 --> 00:05:20.375
00:05:20.375 --> 00:05:21.836
00:05:21.836 --> 00:05:33.026
00:05:33.666 --> 00:05:38.665
00:05:38.665 --> 00:05:46.848
00:05:46.848 --> 00:05:56.862
00:05:56.862 --> 00:06:04.281
00:06:04.281 --> 00:06:08.702
00:06:08.702 --> 00:06:09.204
00:06:09.204 --> 00:06:11.687
00:06:12.242 --> 00:06:19.987
00:06:19.987 --> 00:06:26.267
00:06:26.267 --> 00:06:30.666
00:06:30.666 --> 00:06:44.211
00:06:44.211 --> 00:07:01.848
00:07:01.848 --> 00:07:02.911
00:07:02.911 --> 00:07:07.612
00:07:07.612 --> 00:07:26.850
00:07:26.850 --> 00:07:31.108
00:07:31.108 --> 00:07:34.971
00:07:34.971 --> 00:07:36.687
00:07:36.687 --> 00:07:47.408
00:07:47.408 --> 00:07:57.946
00:07:58.100 --> 00:08:01.807
00:08:01.807 --> 00:08:23.649
00:08:23.649 --> 00:08:33.870
00:08:33.870 --> 00:08:37.289
00:08:37.289 --> 00:08:48.706
00:08:48.706 --> 00:09:05.683
00:09:05.683 --> 00:09:06.686
00:09:07.147 --> 00:09:14.001
00:09:14.001 --> 00:09:25.452
00:09:25.452 --> 00:09:42.347
00:09:42.347 --> 00:09:46.629
00:09:46.629 --> 00:09:54.892
00:09:54.912 --> 00:10:04.177
00:10:04.177 --> 00:10:10.839
00:10:10.839 --> 00:10:14.395
00:10:14.395 --> 00:10:18.371
00:10:18.371 --> 00:10:29.234
00:10:29.234 --> 00:10:32.634
00:10:32.634 --> 00:10:35.575
00:10:36.145 --> 00:10:37.270
00:10:37.270 --> 00:10:52.615
00:10:52.615 --> 00:10:56.158
00:10:56.158 --> 00:10:57.340
00:10:57.340 --> 00:10:59.660
00:10:59.660 --> 00:11:09.594
00:11:09.594 --> 00:11:17.114
00:11:17.114 --> 00:11:20.230
00:11:20.230 --> 00:11:29.669
00:11:30.251 --> 00:11:31.153
00:11:31.153 --> 00:11:34.287
00:11:34.287 --> 00:11:47.738
00:11:47.738 --> 00:11:53.998
00:11:53.998 --> 00:12:10.692
00:12:10.692 --> 00:12:12.277
00:12:12.477 --> 00:12:12.860
00:12:12.860 --> 00:12:20.416
00:12:20.416 --> 00:12:22.359
00:12:22.359 --> 00:12:38.631
00:12:39.465 --> 00:12:52.636
00:12:52.636 --> 00:12:58.254
00:12:58.254 --> 00:13:05.943
00:13:05.943 --> 00:13:10.969
00:13:10.969 --> 00:13:15.009
00:13:15.009 --> 00:13:29.091
00:13:29.110 --> 00:13:47.347
00:13:47.347 --> 00:13:53.187
00:13:53.187 --> 00:13:54.471
00:13:54.471 --> 00:13:55.995
00:13:55.995 --> 00:13:59.067
00:13:59.067 --> 00:14:01.254
00:14:01.254 --> 00:14:09.048
00:14:09.048 --> 00:14:15.357
00:14:15.357 --> 00:14:18.827
00:14:19.450 --> 00:14:20.693
00:14:21.664 --> 00:14:30.770
00:14:30.770 --> 00:14:31.594
00:14:34.267 --> 00:14:35.893
00:14:35.893 --> 00:14:40.267
00:14:40.267 --> 00:14:48.489
00:14:48.509 --> 00:15:06.990
00:15:06.990 --> 00:15:13.635
00:15:13.635 --> 00:15:19.668
00:15:19.668 --> 00:15:20.071
00:15:20.071 --> 00:15:20.892
00:15:20.892 --> 00:15:25.215
00:15:25.215 --> 00:15:26.740
00:15:26.740 --> 00:15:28.102
00:15:28.705 --> 00:15:34.022
00:15:34.022 --> 00:15:38.751
00:15:38.751 --> 00:15:42.298
00:15:42.298 --> 00:15:53.393
00:15:53.393 --> 00:16:02.609
00:16:02.609 --> 00:16:03.974
00:16:03.974 --> 00:16:15.653
00:16:18.047 --> 00:16:18.769
00:16:18.769 --> 00:16:19.533
00:16:31.755 --> 00:16:32.596
00:16:32.596 --> 00:16:35.639
00:16:35.639 --> 00:16:41.124
00:16:41.124 --> 00:16:47.633
00:16:47.633 --> 00:16:52.813
00:16:53.666 --> 00:16:54.168
00:16:54.168 --> 00:16:57.111
00:16:57.111 --> 00:16:58.809
00:16:58.809 --> 00:16:59.826
00:16:59.846 --> 00:17:02.279
00:17:02.279 --> 00:17:06.436
00:17:06.436 --> 00:17:08.539
00:17:11.248 --> 00:17:12.190
00:17:12.309 --> 00:17:30.997
00:17:31.017 --> 00:17:42.247
00:17:42.247 --> 00:17:44.791
00:17:44.791 --> 00:17:48.446
00:17:48.446 --> 00:17:55.439
00:17:55.439 --> 00:17:59.394
00:17:59.394 --> 00:18:10.513
00:18:10.513 --> 00:18:15.035
00:18:15.035 --> 00:18:16.086
00:18:16.468 --> 00:18:25.460
00:18:25.460 --> 00:18:28.147
00:18:28.147 --> 00:18:42.035
00:18:43.767 --> 00:18:44.811
00:18:44.811 --> 00:18:46.213
00:18:46.255 --> 00:18:53.420
00:18:53.420 --> 00:18:53.803
00:18:53.803 --> 00:18:54.388
00:18:54.388 --> 00:19:05.898
00:19:05.898 --> 00:19:18.093
00:19:18.874 --> 00:19:21.257
00:19:21.257 --> 00:19:22.659
00:19:22.659 --> 00:19:23.420
00:19:23.420 --> 00:19:26.730
00:19:26.730 --> 00:19:32.078
00:19:32.078 --> 00:19:34.772
00:19:34.772 --> 00:19:40.316
00:19:40.316 --> 00:19:43.290
00:19:43.490 --> 00:19:44.433
00:19:44.433 --> 00:19:53.476
00:19:53.476 --> 00:19:58.410
00:19:58.410 --> 00:20:13.789
00:20:14.512 --> 00:20:15.154
00:20:15.154 --> 00:20:22.451
00:20:22.451 --> 00:20:40.112
00:20:40.244 --> 00:20:42.232
00:20:42.232 --> 00:20:48.555
00:20:48.555 --> 00:20:56.296
00:20:56.296 --> 00:21:03.596
00:21:03.596 --> 00:21:06.515
00:21:06.515 --> 00:21:08.792
00:21:08.845 --> 00:21:19.442
00:21:19.442 --> 00:21:24.823
00:21:24.823 --> 00:21:30.162
00:21:30.162 --> 00:21:31.747
00:21:31.747 --> 00:21:40.550
00:21:40.550 --> 00:21:54.154
00:21:54.154 --> 00:22:08.984
00:22:08.984 --> 00:22:13.404
00:22:13.404 --> 00:22:14.707
00:22:14.707 --> 00:22:17.549
00:22:18.451 --> 00:22:19.352
00:22:19.352 --> 00:22:24.717
00:22:24.717 --> 00:22:52.394
00:22:52.413 --> 00:22:58.394
00:22:58.394 --> 00:23:03.191
00:23:03.191 --> 00:23:05.432
00:23:05.545 --> 00:23:06.796
00:23:06.796 --> 00:23:07.622
00:23:07.622 --> 00:23:09.431
00:23:16.825 --> 00:23:17.547
00:23:17.547 --> 00:23:18.509
00:23:18.509 --> 00:23:26.893
00:23:26.893 --> 00:23:28.998
00:23:28.998 --> 00:23:30.105
00:23:30.145 --> 00:23:52.338
00:23:52.338 --> 00:24:02.759
00:24:02.759 --> 00:24:09.031
00:24:09.031 --> 00:24:13.417
00:24:13.417 --> 00:24:15.760
00:24:16.265 --> 00:24:18.675
00:24:18.675 --> 00:24:19.619
00:24:19.619 --> 00:24:22.594
00:24:24.266 --> 00:24:32.329
00:24:32.329 --> 00:24:38.519