Longevity and AI - A Conversation with Dr. Ronjon Nag, Founder of R42 Group

That lesson is very important today, as Ranjan is now overseeing a wave of new startups in the area of longevity and AI. And as the science races ahead, having the right business focus is going to be important to bring those technologies to market so they can benefit everyone with that. Let's get started. This will be a closed panel. In the beginning, I will ask the first few questions and after that I will open it up for everybody else

https://s.swell.life/SSPgSzIGYxMnhNY

https://www.r42group.com/ronjonnag

Please click on the link below to read more about Ranjan's background
Arish Ali
@arish · 0:33

Q1. The big picture - where are we in terms of the science of longevity?

And while we all look at the science currently in terms of a longer healthier lifespan, it's always fascinating to think about the long term, the edge case scenarios, how close are we, or what does the science tell us about the possibility of living forever
Ronjon Nag
@ronjonn · 1:40

The science of aging so far and in the future

Hello, Arish. Thank you. This is Ron John. Ron John Nag. I'm President of our 42 Institute, and we make investments and study longevity and artificial intelligence. So where are we in the science of longevity? Originally, there was the concept of telomeres. These are these buffer cells at the ends of your chromosomes that get shorter and shorter as you become older. And it was thought that might be causal. We think now that there may be correlation. And so that's one aspect
Arish Ali
@arish · 0:26

Q2. What role is AI playing in Longevity research?

Thank you, Ronjon. My next question is about the role of Ali in longevity research. When people think of longevity science, like conjures images of biologists in white lab coats trying to find the right chemical cocktail that will extend the lifespan of a mouse. So where does software and AI fit in terms of the actual research and innovation that's happening in the field
Ronjon Nag
@ronjonn · 1:20

Finding bio markers for longevity

And all these wearables that wear is generating billions and trillions of points of data. And eventually we're going to have longitudinal data across many people. So the idea in using machine learning or AI is to actually extract characteristics that people who live long, healthy lives actually have the characteristics that they have. These are known as biomarkers. And if we know what those biomarkers are, we can see what things can encourage those biomarkers to have a longer life. Thank you
Arish Ali
@arish · 0:24

Q3. Examples of new bio markers or other early success AI is having?

Thanks Ronjon. That sounds very exciting. Are there any new biomarkers that have been identified as a result of applying AI and Ml techniques on large data sets? Or are there any other breakthroughs or promising results which would not have been been possible? But for the use of AI, it would be great if you could share some examples of early success that AI is having in this field
Swell Team
@Swell · 0:15

Welcome to Swell!

Ronjon Nag
@ronjonn · 1:41

Ageotypes

Hello, Arish. Yes. Thank you very much for the question about new biomarkers for aging. It turns out there's this concept known as ageotypes, that each of us are of a particular kind of age, Joe type. And maybe intuitively, we think of this that maybe our age is related to our genetic background. If our parents lived a long time, often we will and maybe vice versa
Arish Ali
@arish · 0:34

Q4. What is the R42 institute and how it is advancing research in the field

Thank you, Ronjon. My next question is about the R 42 Institute that you have founded and that is kind of helping pioneer some of the research in this field. Can you talk a bit about what is this Institute and how it is advanced answering research in the field. By the way, I love the name. It's a very cool and a name for an Institute whose goal is to find big answers
Ronjon Nag
@ronjonn · 2:27

What is the R42 Institute

Other projects we have are how to make artificial intelligence easier to use, for example, how to come up with protein folding software simulations, or how to make neural networks easier to use in a draganddrop format. We also have a project on stock market prediction, and we also have a project on solving the water crisis called Water Data Science
Arish Ali
@arish · 0:35

Thank you @ronjonn - the interview is now open for any public questions.

I know you're a very busy man, so whenever you get a chance, if you can check back in and reply, that will be great and much appreciated. And thank you again for the time you've given to us as well. Thank you

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