Aashi Dutt - AI and Women Tech Makers
Founder's Voyage ·
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Transcript
SPEAKER_03
00:00:00
Whenever you are in a fix or you think that whether you should do it or not, just give it a try. You might fail, but I think you'll learn a lot from that.
SPEAKER_01
00:00:26
A featured speaker today is the founding AI engineer at Medengoj Healthcare PVT LTD, a Women Techmakers Ambassador and the lead organizer of TFUG Chandigarh, a community of tech -oriented people who share her passion for AI and machine learning. Aishi, it's a great pleasure to have you as our featured guest today. Thanks so much for being willing to share your journey with us.
SPEAKER_03
00:00:54
Thank you so much, Nancy and Spencer. It's been a great journey since I graduated from MIT boot camps and joining with people from all around the world and learning so much with them. It's been a real pleasure. Thank you so much for having me.
SPEAKER_04
00:01:14
I was wondering if you might kick us off,
SPEAKER_04
00:01:16
you know, talking about times long before that, maybe some of your early experiences growing up, some of the kind of founding experiences of you as a person that you feel really impacted you personally and professionally.
SPEAKER_03
00:01:32
Let me just start from really beginning of my life. So as a kid, I was kind of the studious kids who like to always be on the top and always the front bencher kind of person who had lots of questions for my teachers and especially the science teacher who loved to answer my questions and intrigued that curiosity mind in me. So that was one. And as I grew up, I saw one of my first ever space movies, Armageddon. I think you might have heard of it. And I was intrigued by the space and dreamed of being an astronaut, though it did not happen, but my curiosity of science did let on. And while I was in high school, I started to understand that there is something deep about solving some real life problems and making an impact on people. So, as I grew up and I went to college, I was intrigued by some kind of things that would convert my thinking, my imagination of solving problems into actual solutions. So, engineering got my way. I started with engineering as a communication engineer and I think most of you would agree with me that yeah engineers can do anything and that's the concept that still lives on today. So yeah I started with electronics and communication engineering because none of other engineering departments really I thought that would not show any kind of output. I really wanted to see that one LED bulb light on that yeah I did this thing yeah that's where all this thing started and computer science quite funny but computer science did not exist so there was no AI there was no Python no Java no C++ no such kind of thing and it just came into me through the experience of of what I saw around me. So, yeah, I started solving some problems, looking for different problems,
SPEAKER_03
00:04:03
and ended up where I am today.
SPEAKER_01
00:04:07
That's so interesting. Thank you for taking us through that. I share your perspective of having those early teachers, especially in science, that were so good at motivating and inspiring the curiosity that we have in what they're teaching. I had a very similar experience. Can you take us a bit through your career journey to MedEngage Healthcare Limited and TFUG Chandigarh? I hope I'm not pronouncing that too awfully.
SPEAKER_03
00:04:40
No, it's all right. Nothing to worry about. So MedEngage is actually a product of COVID. So, during the COVID times, we saw the world fell apart and we saw that while all of us were within our households trying to be safe, there were people who were putting their lives on the line, especially in the hospitals. And yeah, a few of my family members and close friends were also there. Some were the patients and some were the actual staff who were working there. What happened was we were watching the television one day and we saw that there was some kind of shortage of staff members and the patients were not looked after well because the patients were more and the staff was less and they were quite helpless at that time.
SPEAKER_03
00:05:39
So, we came across one of our colleagues from MIT bootcamps only, he came up with this really amazing idea that why not build a product that would actually help the hospital staff in such conditions, even COVID or no COVID, let's build a product that would actually be really good and helpful to the patients as well as to the doctors and the staff members. MedEngorge was born. MedEngorge is basically that med is the medical device and we talk about in the hospital perspective and gorge is basically any instrument that would help in all those medical interfaces. So we thought of that let's just build a whole ecosystem that you connect it with any device that is in the hospital like the ventilators, the the monitors and you get the data out of it and you train a ML model over it so that you can detect any analogy that something bad has happened on that particular patient and if the staff is not around, we might be able to help him out by raising an alarm or maybe raising some kind of notification to the doctor
SPEAKER_03
00:07:07
that such and such patient needs their, you know, requirement is there. So, Medin Gauj was born out of that. While I talk about TFUG Chandigarh, TFUG is basically the short form for TensorFlow user groups and Chandigarh is actually a city or a U .T. in India nearby my place where I live. DFU Chandigarh is actually an effort by the Google Developers community here in India and all across the world. They have kinds of different groups and communities that brings people of tech, who are really interested into tech, come together and learn something new. So Chandigarh is basically a community where we welcome students, professionals who might, might not have any background in AI or ML specifically, and we welcome them to learn with us, to grow with us in an environment where they can put out their skills, they can showcase their skills, we give them a platform for that, so they can host events with us, they can attend events with us, and learn about TensorFlow and any products of Google with us. That's how I hold the story of TF -UG and MED -EN -GORGES. Thanks
SPEAKER_04
00:08:35
so much for breaking down that acronym too. It makes, I I understand why that could be cumbersome to write on LinkedIn,
SPEAKER_04
00:08:42
but it makes so much more sense when you spell it out like that. Going back to Medangaj and their story of coming into being during COVID, what led you at that time to really want to join their founding team?
SPEAKER_03
00:08:59
Oh, that's a pretty good question. My parents do often ask me that.
SPEAKER_04
00:09:05
I'm glad I'm in good company.
SPEAKER_03
00:09:06
Yes, of course. I was right out of college when Merin got started. It was 2020, really harsh times to graduate in 2020. And I was about to graduate in May 2020. But unfortunately, The whole thing was postponed till November 2020, and I had lots and lots of time in my hand.
SPEAKER_03
00:09:36
And we were thinking about the problem and thinking about the solution for hospitals when my co -founder came along and we started our own startup. Ed & Gorge started right after I graduated from my college in 2020, November. And it was like one of my first jobs. So I was a pretty newcomer, had no experience of the whole professional world. And it was something that came in like a hot wind to me. So it was something that was hard to digest, but a lot more things to learn from. And I took it as an opportunity to learn. And at the same time, there was lots many things that I did not know. And to cover that up, I thought of interning with a lot of startups. I interned with startups in India, with startups in Netherlands, one was in Italy. So, lots of startups and in different domains. I started off with IoT, that was the base hardware that we were working with Med &Gorge. Then, because most of my co -founders are already in the professional world and they had a lot of experience, I thought of giving a try to the non -tech world and learnt about business development. So, when I interned about for at least 2 -3 months about business development, how the whole business thing works and what all things you have to take care before you reach out to the market. And before you reach out to your actual customers, what all things you have to take care of. And all those internships did help me well, to hold that ground and implement those same things and reproduce them in my own startup. So that was one thing that I like to share with you all even that if you are really new to something, and you think that we don't have any experience of that. I think that interning for a start -up or interning with a start -up or a company would be a really great idea if you are like me, like right out of college and you don't have any experience. I think that was the best thing that I've done till date.
SPEAKER_01
00:11:56
That's so interesting. I think that's such a strong move to intern at start -ups because Because it's, to some degree, throwing yourself into the deep end pretty heavily. Because when I worked at a startup previously, it was my first job as well. And I was like, you know, thrown in the deep end, had a lot of responsibility that I didn't anticipate having, and things like that. But I think it's a really powerful education experience. And I definitely agree that it's a good thing for people to really start with.
SPEAKER_03
00:12:30
Absolutely. Absolutely.
SPEAKER_01
00:12:31
Can I ask a little bit about how you became interested in AI and what you see as sort of, in your view, the, you know, the really interesting or impassioning aspects of AI for you?
SPEAKER_00
00:12:47
Yeah.
SPEAKER_03
00:12:48
That is quite a story actually. So while I was in college, final year, I was travelling to my college in the morning and And I saw like a bunch of garbage lying around. And that very same day, one of the person from municipal corporations here, he came about and he gave us two baskets, the green bins and the blue bins, so you segregate your waste. So what he did was that we had to now segregate our waste. But as I told you that I always think about solving some real life problems and how we can impact them. So a problem came into my mind that why not we solve a problem that is already existing that the waste that is already lying is just mixed up and you cannot segregate everything by hand.
SPEAKER_03
00:13:46
Why not just make something truly, you know, automated or intelligent that you solve the problem right where it's lying and not just start right now, just solve the previous history as well. And that's when I started researching about it and OpenCV and all the computer vision libraries came in and I was quite intrigued by what people have done with AI. So, as I told you that I was an electronics person who just loved lighting up the LEDs. But at the same time, the world of AI was so intriguing and so fast moving. And with all those handwritten digit recognition happening at that time, and people were learning, people were enjoying computer vision. We can't say the same thing about right now scenario with LLMs. but yeah right people were enjoying computer vision and I thought that that problem was really a great idea to get started with computer vision and that's how I was introduced to AI because it made my vision of solving that problem much easier and I could convey that to much more larger audience because most of the people were learning AI at that time And I feel that that was the right point where, or the right combustion that I got to get started into AI.
SPEAKER_04
00:15:20
The way you describe it, I mean, it's like how I wanna go about problem solving and I am more, I'm interested in conversations about AI, but technically I know nothing about actually creating something with artificial intelligence, but you make it sound so exciting. I'm like, every problem should be solved with AI. But before I go down that rabbit hole, I actually want to ask you something, and this is completely subjective. Your opinion is great. We're not holding your feet to the fire at all. So we've had several conversations, interviews, and then other conversations in this community that have kind of evolved into the ethics of AI. And I saw that that's something that you actually study this part of your program. And I'm wondering if you have any particularly strong
SPEAKER_04
00:16:17
opinions about shoulds and should nots about AI or whether or not governments should be allowed to regulate it at all, a little bit or not at all. So this is completely opinion based, but I was just wondering what your thoughts were on that.
SPEAKER_03
00:16:37
Absolutely. So I think that in current scenario, it is kind of difficult to stay away from AI or data sharing, to be honest. So AI is based all upon data. If you don't have the data, AI can't do anything. The models are useless without the data. And they're actually built on the data, right? So in layman's language, AI is nothing without data. and I feel that if you want to create something that is strong enough and you
SPEAKER_03
00:17:09
want to harness the power of AI, it is really required that you give it the data that is required. But keeping in mind the AI ethics part of it, it is really important that you hold the party that is holding your data responsible of how they are using your data. Let me give you an example of federated learning. What Google did was, they launched something called federated learning, where they said that the model would not take all the data out of your phones to the cloud. The data of your phone would be remaining on your phone itself. Your data is not going anywhere, not on the cloud, not any servers or anything. your phone is the main device, the data stays there, the models or any AI, that we say, is learning from that data and it's implementing what it got the best on your phone itself. So, that's how the data won't leave it. So, the parties or the third party won't be able to misuse your data. But at the same time, I think all of you might remember every time we, you know, install
SPEAKER_03
00:18:29
any new app and how we just click on allow, allow, allow, or okay, or anything that come and that pop up that comes along, saying that give this consent of this consent, or this is the disclaimer, and we don't give a heed on just reading about it, right? we just go about and click allow because we don't want to spend that time on how our data is being used. So, yeah, government should regulate it. We should be responsible ourselves as well on whom we give the consent to use our data. It is very important that the data that we give away is very personal to us and we don't want the third party to make misuse of it, but at the same time we want the goodness of AI. We want those spammers to not spam us any longer and that all is built upon the data that is collected by the actual user. Yes, the regulation is required, but yes, the consent from both us as well as the government is required as well. That's my take at least.
SPEAKER_01
00:19:41
I think that's a very smart take. I'm definitely someone who tries to be pretty responsible with not clicking allow too quickly, not, you know, having all of the cookies, all of the agreements to share my data. But, you know, sometimes you definitely have scenarios where you're like, oh, I just really want to do something. And you just let it go through. I think you make
SPEAKER_01
00:20:03
very excellent point about the responsibility being on the individual. Now, I have seen recently some studies into the concept of protecting your data from companies that just scrape the internet. You mentioned LLMs earlier, and there's also generative AIs in regards to images. And one group has developed a technology they're calling Nightshade, which is like a, I don't really know the specifics to be honest, but it hides from an AI what the image is actually of, and they describe it as poisoning the AI through their images being downloaded without permission. I don't want to see a world where generative AIs don't exist, but I think it can be taken too far if there's internet scraping entirely and we have to be somewhere in the middle. So what I'd love to understand, if we can just dig a little bit deeper into that, do you know about this sort of research and do Do have any perspectives on its validity or is it just something that AI will not notice after a short period of time?
SPEAKER_03
00:21:34
To be honest, I haven't really found a really good use case of generative AI till now, except for the open AI chat with your bot that kind of I frequently use to understand bit of the concepts that I'm not really clear about. I think that is a really good take of generative AI. But when you talk about generating images or scraping data from the internet without the acknowledgement or without the consent, that is kind of a tricky part to be honest. Because when we talk about companies and getting the data, we all know that, Yeah, there are practices from the companies for scraping data, and we are not at all aware of where the data comes from, and they easily get by that as well. Oh, yeah, I don't have much take upon that. But I feel that, yes, we do have to do a little bit more work on when it comes to generated with AI because, yeah, of course there is goods to that and bads to that as well. But getting images adds watermarks to the images and as well as there are some of the transformers libraries through Hugging Face, I've recently heard of that.
SPEAKER_03
00:22:56
Through that you can watermark your images so that it adds an extra layer of security to it. I hope that answers your question.
SPEAKER_04
00:23:05
Yeah and I appreciate you. Generative AI is something I've been thinking about a little bit actually in regard to images lately because there are several services that offer, I mean basically to create whatever image based on their stock library that you want to use. So I think it will be more interesting as we get into people actually being part of it. Where is that line? Because I guess I feel like you can have a nature photo that can be doctored to the point that it is barely representative of the composite images that produced it. But when you put a person in there,
SPEAKER_04
00:23:57
How far are you gonna take that away from what that person initially looked like? And then are you still allowed to use their likeness? You because and I'm just thinking about this because I I know this has been a point of like lawsuits, you know, in in the art artist world, you know, the digital artist world. So I don't know. I think it's kind of a fascinating topic that we could probably keep going into but you've been involved in so many different things and one of the things I thought was really neat about your resume was that you really give back like being a mentor is really important to you as well and I was wondering if you could talk a little bit about women tech makers can you tell us like sort of how you became an ambassador and what you do in that role
SPEAKER_03
00:24:54
Yeah, so Women Techmakers is actually a platform where you get to learn about what women are doing in tech, how they are adding the value to the tech stack, so to call. And Women Techmakers and how I got introduced was through communities itself. So, I became a part of TensorFlow user groups and I was introduced to a whole lot of communities around me.
SPEAKER_03
00:25:26
So, there were Google developers groups, there were groups for student communities, and as a part of that groups, there was a community called Women Techmakers. One special thing about Women Techmakers is that they platform, they encourage all the women in tech to come together and provide them a platform to showcase their skills, to showcase what sessions they are giving, what new technologies they are learning, if they are facing any problems. It's basically women backing all the other women. So it was a great opportunity for me to meet wonderful women around the world. And especially in India, from where I come from, I have seen a lot of male traction in the IT industry, in the AI industry, and I was so excited to be a part of Women Techmakers, and I met really, really amazing women who are actually contributing so well to the AI world that I was so excited about. And I've learned a lot from them. I'd like to quote one of the Kaggle grandmasters here, her name is Usha Rengaraju and her simplicity about being a women tech maker, a person who comes about and you can talk to her about anything, she's so open and you get to learn a lot from her. I usually try to ping her around when I'm around or I have some problems or I'm looking
SPEAKER_03
00:27:05
for some kind of solutions. And that whole community, to be honest, has never let me down. It's basically women backing for women in a world filled with people and just helping each other out.
SPEAKER_01
00:27:24
I think that's phenomenal. I think there's a lot that is inaccessible to individuals individuals by themselves, but when they're working together, when they're helping each other out, can absolutely open up the world for people. I think it's a great path you're taking there. Absolutely. Thank you so much. In regards to MedEngage, what do you see as the long -term vision for it? And do you see it as something that would potentially grow beyond India, or is there an advantage to keeping it restricted to India?
SPEAKER_03
00:27:58
Right now, we are planning to keep it kind of restricted to India, because we are in the phase of testing it out with in and around hospitals and some grocery clubs that provide a proof of concept to us basically. And we are allowing some of the local vendors to help us out in the hardware production and getting the things right and prototyping it right. But we are certainly not stopping here. And I think we are kind of solving a problem that could be a solution to every problem that's around the world.
SPEAKER_03
00:28:42
So I don't think that a shortage of staff or not having complete monitoring of the patients around the world is not a problem. I think it's a problem that we all face and if we are able to detect something before something bad happens to a person or a patient, I think it's well worth to solve that problem and it would be really helpful for all the people around the world. So, yeah, we're not stopping here, but we are kind of in the initial stages where we are building on that product. We trying to get our hands on all the things that could happen around what could go wrong, what is going right for us, and we're trying the initial phases of trying it out. But yes, we are not stopping here, and we'll be around to the world and to save some lives.
SPEAKER_04
00:29:36
I absolutely love that. If that isn't somewhere in your mission statement, then it probably should be.
SPEAKER_04
00:29:43
I want to actually pass to someone you introduced us to.
SPEAKER_02
00:29:49
Hey, everyone. Hey, Ashi. Hey, Nancy.
SPEAKER_04
00:29:52
Thank you so much for joining us. Yeah, please go ahead.
SPEAKER_02
00:29:56
Be happy to. Yeah, I think I have a question for you. Like, considering that you have been working with sensor data of probably customers who are in like in requirement of medical solutions, right? So like, at what point do you determine or how do you determine that the amount of data you're collecting is enough, right? It's not too much? Or how do you even ensure that you know, the kind of data that you're collecting, and in case there are like open source libraries or say third parties which are accessing that data how do you ensure that you know they are not using it for whatever original purpose you had intended it for. For example data of say heart rate and other sensor data taken from a person and let's say you know you're using it for detecting diseases relating to probably the heart probably something else it can also be used to determine what kind of activities they are performing these could be activities which are social which are private could be anything. How do you ensure that this does not happen? The data is not used for something which is not originally intended for. And how do you know that this is enough amount of data that you have collected? You don't need to collect any more data from the person's body.
SPEAKER_03
00:31:17
I think you'll agree with me that no data is enough data for when we talk about the ML models, and we kind of are in a continuous loop of making our models better day by day. Of course, there are certain things and restrictions that restrict us from getting certain data out of the machines, and there are certain protocols that have to be followed. And we do keep in mind about them. And when it comes to a third party using that data, we do make sure that firstly we are not using those third parties because we are using the data and streaming the data collections. And finally, there is a model generalization and customization for the person it's trained on. What we do really is that right now we are working with the ventilator data And that is provided to us by the hospitals that we are working with and the rotaries that we are working with. And we do make sure that the data never leaves the edge AI device that we are using. So only the data that is required for whenever there is an anomaly detected that goes into our cloud so that we can detect anomaly and we can fine -tune our models better. But rest assured that none of the data goes into any third party so that it cannot it can be used or misused by some other person or some other company for their purposes. And right as you said that the same data could be used for multiple purposes like activity detection and everything yeah that is a thing that they are using for and companies do use it for. But our main aim was to work with such sensitive data and heart sensitive data that we're working currently with. It's something that we take very seriously when it comes to privacy and consent of the patients, as well as the hospital authorities and management. So yes, that is a major concern. But we are working with the management to actually build on that. And also, we are working on federated learning, an on -device model fine -tuning approach. So that is kind of an on -device AI model. So we're trying that the data never leaves the edge device so that the data leakage or data privacy is not hampered.
SPEAKER_03
00:33:56
I hope I answered your question.
SPEAKER_02
00:33:59
Thank you. Yes, I think that's a great answer. Yeah,
SPEAKER_01
00:34:02
absolutely. That was a great answer. Thank you so much. So you actually mentioned federated learning earlier as something that Google was doing. Is it something then that is more and more being engaged in the industry? Because I can see how that would allay a lot of people's concerns in regards to these sorts of things. Yeah.
SPEAKER_03
00:34:24
So when we talk about data and privacy related things. I think that it's very important on our part and as a company it's very important that we take these kind of things data related and data privacy related things very seriously on our part and we do make sure that the more the data we can keep with ourselves and within our models and we not expose it to the any third party or the outer environment the more it's better for us and our client, so that it builds that belief relation with them, as well as we are not on the brink of any hammerage to our data privacy as well.
SPEAKER_01
00:35:08
Excellent, thank you very much.
SPEAKER_01
00:35:10
Now, it's very clear you have a lot of talents and abilities and passion about the things that you're working on, and I'm sure they'll take a lot of your time going forward. But is there any other problems that you haven't had a chance to sort of tackle that you, in the future, are wanting to put your time and energy towards?
SPEAKER_03
00:35:33
That's a quite interesting question, actually. Recently, I've been thinking a lot about climate change, and I've seen a lot of things going around climate. And being a person who comes from agriculture background, I've seen my father farming for right around like more than 40 years now. I think there's a quite a lot of potential when we talk about agriculture and climate. And if we combine those two things together, I think that would make a good combination to solve some problems in those sectors because I think though people are working in the climate sector and companies talking about zero emissions by 2040.
SPEAKER_03
00:36:25
But I think that agriculture is kind of the untapped market where it's lot of potential solve a lot of problems and I think that that would be one of my things that I'd like to brainstorm a little bit more.
SPEAKER_04
00:36:44
That's great. I love that you have. I mean, you probably
SPEAKER_03
00:36:48
don't
SPEAKER_04
00:36:48
have endless ideas lined up, but you like your imagination is so great. I really I think you've got lots of great things ahead of you. Um, so going back to, you know, you were saying great things have happened since you attended the MIT boot camp, um, and you were also part of the impact pilot too, right?
SPEAKER_00
00:37:13
Right. Okay.
SPEAKER_04
00:37:14
I was going to say, I think that's where we first became acquainted.
SPEAKER_04
00:37:18
Um, I was wondering, you know, what your kind of takeaways are. like, do you find that some of the tools from the Disciplined Entrepreneurship Framework continue to be useful to you? Was there anything sort of new to you in the Impact Pilot? You know, what's kind of stuck with you and helped you from those programs?
SPEAKER_03
00:37:46
Absolutely. So, nothing just very specific about from the program, I remember, but there are a few points that I did pick up from MIT that talked about customer persona, value proposition that you build around your whole network and your whole product, and how you understand your target market as well your target audience the ways you tackle them the ways you understand the pain points of people the way you create an experience for people not just about the products how you understand their problems how you understand the experience they might want from the product after they before they understand that and I think that through MIT I have learned a lot about those things not just around the product but more about how you understand people how you understand your audience even from the MIT boot camp though I was the youngest of all right people around me had like the minimum amount of experience was like four or five years and maximum I was like 20 -25
SPEAKER_03
00:39:15
years of experience people had there and I was their pre -final year student who was the youngest person attending the MIT boot camp. Still the way Josh put that out on how you can understand your audience, the key audience was a wonderful way to understand and that things that key takeaways I do use when I understand any market, be it my own and be it any other market that I understand. The first thing I do is understand the what goes behind the mental maths of a person when he thinks about your product. what is the problem that you're solving? Is there something that is underlying? Is there something that is particular to like a genre of people? Or is there something that people would like to be attended to, but they're not really like intrigued. They're not in a hurry to solve that problem.
SPEAKER_03
00:40:19
So I think there are kind of a lot of key takeaways from MIT boot camps and as well as the impact sessions. But yeah, these were the few key takeaways that I'd like to share with you all.
SPEAKER_01
00:40:35
I always find it so very interesting to hear what other people found, you know, key takeaways that stuck with them. And I think you've raised a lot of very good points. Personally, I found it that unfortunate
SPEAKER_01
00:40:47
that I've had to relearn the lessons later on in life and then look back and been like, oh, they were telling me that at the boot camp. But it sounds like you've really embraced the learnings that you had. And I think that's really, really impressive. What I would like to sort of shift over to a little bit is talking a bit more about sort of life, your life side of things. How do you go about balancing your work, your family life, everything else that you're passionate about at the same time without, you know, not getting any sleep or anything like that?
SPEAKER_03
00:41:23
So I have this simple thought that you prioritize things and you do one thing at a time. Whenever there is a whole lot of mess around me and I have lots of things to get done, I just sit down and think about which of these things is thing I want to prioritize. Get that one thing out and just click just tick out that box and get it done first. Oh this is a very very easy technique that I have adopted to make a to -do list and tick boxes based upon the priority that thing I've done and just try and keep it simple. So I don't think I have a lot of experience saying this, but it's always good to keep it simple. It's always good to prioritize things and just do one thing at a time. And this is something, I call it my mantra or something, but yeah, this is something that really worked for me and still working today. and I'm very fortunate to be living with my parents, working remote, working on the thing I'm passionate about, working with the community I'm passionate about, giving out sessions, doing events, and trying to balance everything out. Yeah, though, there comes days when it's hard to balance out things, and you just need to keep it simple, I'd say.
SPEAKER_04
00:43:02
I mean, I think it's very great advice. Actually, that is something I think that the mentors that I had during our bootcamp really railed into me. I think it's not something that comes naturally to everyone. Maybe I'm just giving myself an out, but it's something that I'm continuing to work on. And I think I very much agree with your advice. The other way I've heard it explained by other people in this community
SPEAKER_04
00:43:38
that I think helps my brain get around it too is like zooming in and zooming out. So like you zoom out and see what you want to create. And I imagine this is highly important as an engineer too. But then really have to zoom into this one part, this one problem that you're trying to solve and figure out the mechanics of that, and prioritize that list and make that your focus. And not worry about how the rest is going to work out. Well, anyway, that's like my add -on to kind of like manage the crazy brain part that comes in. Well, if I do this, then what if this? To make it simpler.
SPEAKER_04
00:44:22
But I think that that is very wise advice. So thank you, thank you for sharing that with us. So I was wondering, is there any particular kind of guiding philosophy in your life that you really feel like is just like the one thing that, like if you have a serious decision to make, you would just kind of go back to? Or is make it simple really that as well?
SPEAKER_03
00:45:02
I think it's always been keeping it simple.
SPEAKER_03
00:45:06
That's kind of my advice on that. But yeah, there've been times when things do get out of hand. And the things do get a little tough on the tougher side. But I think I've always sailed through them. And one of my friends did share something with me that Aashi, you don't need to be the perfect person, you just need to be disciplined. and even if you don't want to do that thing that day it's okay but try and do a little bit part of it and then you get a hang of it oh yeah you just have to get started with something so that you reach to the end but I feel all in all yes the life philosophy for me stays the same oh it won't be the same as my parents do and others do but yes something that I'd like to share with you all that I recently binge -watched Ted Lasso I hope you have seen that and
SPEAKER_03
00:46:22
the only best thing that match I matched vibes with was being optimistic it's it's good to be optimistic it's good to see good parts in everything wrong or right, but it's always good to see the good parts. So be optimistic, the problems will come and go. And yeah, I think that is the thing that sails me through every difficult situation.
SPEAKER_01
00:46:54
That's good, that's excellent, thank you. Thank you very much for everything you've shared with us. Now, we are at just about the end of the hour, but we do like to wrap up with a particular question. Do you still have time to answer one more question?
SPEAKER_00
00:47:11
Absolutely.
SPEAKER_03
00:47:12
Go on.
SPEAKER_01
00:47:13
Thank you so much. So, this question is very sort of freeform, and I want you to take it however makes the most sense to you, and frankly, you've already shared so much wisdom with us that I feel like we're just pulling more from the well, but what do you think has been the best lesson or takeaway from your journey so far? Slash, do you have any words of wisdom you might wanna leave with us?
SPEAKER_03
00:47:40
I think it's gonna be a philosophy class,
SPEAKER_03
00:47:44
but okay, I'll share something with you. One thing, last thing that I'd like to share with you all is I think it's okay to make mistakes. I have made a lot of mistakes starting, yeah, some in my career, some in life, but I think they're part of it. I have learned through them. I have learned to my mistakes and it's okay to try something new and I'll just share something with you that while I was interning and there were rocky times when the startup was not doing well because we started off in the COVID times and you know being a med tech startup it was very difficult for us to get data out of hospitals or even reach out to hospitals because everyone was so into madness and there
SPEAKER_03
00:48:52
was so much chaos. But there was times when we thought like this might not be a good idea and I started off looking something different. So yeah, I did some UX UI freelancing at that time and designing was something that yeah, I was I'm really bad at drawing and painting stuff. But yeah, designing was something that was really, like, kicked me, right. And I was really interested into that. So I started freelancing in UX and UI. And after some time, I got bored. And I was like, how I made a really big blunder or a very big mistake or why did I spend so much time in UX UI at least six months of freelancing. But now when I look back, I think that, that was some time when, okay, I did this thing, I tried this thing, and I learned something from that. And that was the best takeaway. So whenever in doubt, my only advice, or the words, my ending words would be, whenever you are in a fix, or you think that whether you should do it or not, just give it a try. You might
SPEAKER_03
00:50:12
fail but I think you learn a lot from that and I think that would be the last things that I would like to share. That
SPEAKER_04
00:50:23
was so perfect that was very well verbalized and the failure is definitely one of those things that I think we all have worked in our own way to try to put in perspective but I really appreciate getting yours. Thank you so much Ashi, we really appreciate all of your thoughts and everything you shared with us and taught us today. But thank you so much again, Ashi. And thank you everyone who joined us today and those that participated in the discussion. Spencer and I and the team behind Founders Voyage feel really fortunate to be part of this community with you and to bring you cooperative learning experiences like this each week.
SPEAKER_04
00:51:05
We'd love to hear your nominations for other community members you think would benefit from these conversations and other interview guests, and check out Ashi's Medium blogs on technical content if you're interested in reinforcement learning, AI or machine learning, and she has a GitHub as well. And if you'd like to support this becoming a podcast, you can do that through our Patreon. So thanks so much again, everyone, and we hope you have a great day, evening, and week ahead.
SPEAKER_03
00:51:41
Thank you so much for having me, Nancy. Thank you. Thank you, Spencer, for your time. And thank you everyone who joined.
SPEAKER_01
00:51:48
Thank you so much for coming on. It was an absolute pleasure.
SPEAKER_04
00:51:52
Same here. Thank you. Thanks again. Take care, guys.
SPEAKER_00
00:52:04
You've just finished another episode of Founders Voyage, the podcast for entrepreneurs by entrepreneurs. The team at Founders Voyage wants to thank you from the bottom of our hearts. We hope you enjoyed your time with us, and if so, please share this with someone else who might enjoy this podcast. You can also support us by leaving a review on Apple Podcasts and Spotify, and by donating to our Patreon. Outro music today is Something for Nothing by Reverend Peyton's Big Damn Band.