Kakani Katija's guest appearances

Kakani Katija

Women's Media Center Live with Robin Morgan

The Deep-Sea Podcast

Gloria Steinem

Cecile Richards

Ashley Monroe

Sheryl Sandberg

Rachel Lloyd

Sheila Johnson

Marlo Thomas

Pat Mitchell

Kathy Najimy

Rebecca Traister

Katie Goodman

Rachel Simmons

Sally Kohn

Lily Tomlin

Shannon Watts

OwlTail

We have often talked about how difficult it is the get data from the deep sea… but would you believe that the bottleneck to our understanding of the deep ocean, at least as far as visual data, is processing those images? Turning a picture of the deep sea into a list of species, habitat type, sediment type etc. is a time-consuming process that requires a wide range of skilled people. Due to time/funding constrains a lot of valuable information is lost. A team looking at a specific question will have lots of information in their data that other teams could use. A picture is worth a thousand data points. We chat with Dr Kakani Katija, the co-founder of FathomNet, an open-source repository for labelled deep-sea imaging data. The platform is still in beta but it is hoped that it will allow scientists to easily and usefully share their amassed data in a single and easily searchable place. But what about that processing bottleneck? The tech-savvy listener may have noticed that a massive collection of labelled image data is exactly the sort of thing you need to train a Machine Learning or Deep Learning algorithm. Can we automate a lot of the time-consuming image processing and let the experts focus on the new and unusual stuff? It’s at this cutting edge that things get exciting and we may be at the cusp of a marine science renaissance. We have all our usual nonsense. Alan continues to find things in Australia that want to kill him. We answer some listener questions on deep-sea fish memory and Thom and Alan’s origin story. We also hear from Don about his time on the cruise ships. A decidedly un-deep-sea segment but it could be considered ‘adventure’ on the high seas. We also launch our podcast merch! Please do send in any pics of you wearing the merch. We find the idea of real people in the actual world wearing this so surreal!  Feel free to get in touch with us with questions or you own tales from the high seas on: podcast@armatusoceanic.com   We are also on Twitter: @ArmatusO   Facebook: ArmatusOceanic   Instagram: @armatusoceanic   Read the show notes and find out more about us at: www.armatusoceanic.com  GlossaryArtificial Intelligence (AI) – A science dedicated to making machines think in an intelligent way, mirroring a biological brain. Data pipeline – A path that raw data follows to become useful information. Deep Learning – a more complex subset of ML that mirrors the way a brain works Machine Learning (ML) – computers learning to perform a task without being explicitly programmed to do so ML/AI model or algorithm – A model that has been trained on real data and can now process new data itself. Online Repository – A database stored online so that people can access it from anywhere Open Source – A publicly accessible design that people can freely repurpose and adapt. Visual data – photos or video as a form of scientific data  LinksOur new merch!   Abyssal EDNA article and Paper   Our Angola fish paper and the Open access version   Kakani’s Twitter  FathomNet goodiesThe FathomNet website – have an explore of the labelled deep-sea critter data FathomNet GitHub – take a peek under the hood or even get involved FathomNet articles with tutorials/explanations Helpful video tutorials Paper NOAA Science Seminar, 8 March 2022 1200-1300 PST (UTC-8) Register now! FathomNet Workshop, 31 March &amp; 1 April 2022 0800-1100 PST (UTC-8) Register now!   Internet of Elephants (gamifying processing camera-trap data)   Beyond Blue (game)  CreditsTheme – Hadal Zone Express by Märvel Logo image An image of the small-eyed rabbitfish (Hydrolagus affinis) we took off West Africa Some of our new merch!

We have often talked about how difficult it is the get data from the deep sea… but would you believe that the bottleneck to our understanding of the deep ocean, at least as far as visual data, is processing those images? Turning a picture of the deep sea into a list of species, habitat type, sediment type etc. is a time-consuming process that requires a wide range of skilled people. Due to time/funding constrains a lot of valuable information is lost. A team looking at a specific question will have lots of information in their data that other teams could use. A picture is worth a thousand data points. We chat with Dr <a href="https://www.mbari.org/katija-kakani/" rel="nofollow" target="_blank">Kakani Katija</a>, the co-founder of <a href="http://www.fathomnet.org/" rel="nofollow" target="_blank">FathomNet</a>, an open-source repository for labelled deep-sea imaging data. The platform is still in beta but it is hoped that it will allow scientists to easily and usefully share their amassed data in a single and easily searchable place. But what about that processing bottleneck? The tech-savvy listener may have noticed that a massive collection of labelled image data is exactly the sort of thing you need to train a Machine Learning or Deep Learning algorithm. Can we automate a lot of the time-consuming image processing and let the experts focus on the new and unusual stuff? It’s at this cutting edge that things get exciting and we may be at the cusp of a marine science renaissance. We have all our usual nonsense. Alan continues to find things in Australia that want to kill him. We answer some listener questions on deep-sea fish memory and Thom and Alan’s origin story. We also hear from Don about his time on the cruise ships. A decidedly un-deep-sea segment but it could be considered ‘adventure’ on the high seas. We also launch our <a href="https://www.armatusoceanic.com/merch" rel="nofollow" target="_blank">podcast merch</a>! Please do send in any pics of you wearing the merch. We find the idea of real people in the actual world wearing this so surreal! Feel free to get in touch with us with questions or you own tales from the high seas on: podcast@armatusoceanic.com We are also on Twitter: <a href="https://twitter.com/ArmatusO" rel="nofollow" target="_blank">@ArmatusO</a> Facebook: <a href="https://www.facebook.com/ArmatusOceanic" rel="nofollow" target="_blank">ArmatusOceanic</a> Instagram: <a href="https://www.instagram.com/armatusoceanic/" rel="nofollow" target="_blank">@armatusoceanic</a> Read the show notes and find out more about us at: <a href="http://www.armatusoceanic.com" rel="nofollow" target="_blank">www.armatusoceanic.com</a>  Glossary Artificial Intelligence (AI) – A science dedicated to making machines think in an intelligent way, mirroring a biological brain. Data pipeline – A path that raw data follows to become useful information. Deep Learning – a more complex subset of ML that mirrors the way a brain works Machine Learning (ML) – computers learning to perform a task without being explicitly programmed to do so ML/AI model or algorithm – A model that has been trained on real data and can now process new data itself. Online Repository – A database stored online so that people can access it from anywhere Open Source – A publicly accessible design that people can freely repurpose and adapt. Visual data – photos or video as a form of scientific data  Links <a href="https://www.armatusoceanic.com/merch" rel="nofollow" target="_blank">Our new merch!</a> <a href="https://www.sciencealert.com/dna-shed-by-deep-sea-organisms-reveals-an-abyss-teeming-with-life" rel="nofollow" target="_blank">Abyssal EDNA article</a> and <a href="https://www.science.org/doi/epdf/10.1126/sciadv.abj9309" rel="nofollow" target="_blank">Paper</a> <a href="https://www.sciencedirect.com/science/article/abs/pii/S014111361730185X" rel="nofollow" target="_blank">Our Angola fish paper</a> and the <a href="https://eprints.ncl.ac.uk/file_store/production/240150/0B575B13-F5B4-45A4-9618-411E5CF4D756.pdf" rel="nofollow" target="_blank">Open access version</a> Kakani’s <a href="https://twitter.com/KakaniKatija" rel="nofollow" target="_blank">Twitter</a>  FathomNet goodies <a href="http://www.fathomnet.org/" rel="nofollow" target="_blank">The FathomNet website</a> – have an explore of the labelled deep-sea critter data <a href="http://www.github.com/fathomnet" rel="nofollow" target="_blank">FathomNet GitHub</a> – take a peek under the hood or even get involved <a href="http://www.medium.com/fathomnet" rel="nofollow" target="_blank">FathomNet articles</a> with tutorials/explanations <a href="https://www.youtube.com/channel/UCTz_lVO8Q_FSjC5yE6sXAGg" rel="nofollow" target="_blank">Helpful video tutorials</a> <a href="https://arxiv.org/abs/2109.14646" rel="nofollow" target="_blank">Paper</a> NOAA Science Seminar, 8 March 2022 1200-1300 PST (UTC-8) <a href="https://tinyurl.com/noaatalk" rel="nofollow" target="_blank">Register now</a>! FathomNet Workshop, 31 March &amp; 1 April 2022 0800-1100 PST (UTC-8) <a href="https://tinyurl.com/fathomnet" rel="nofollow" target="_blank">Register now</a>! <a href="https://www.internetofelephants.com/" rel="nofollow" target="_blank">Internet of Elephants</a> (gamifying processing camera-trap data) <a href="https://www.beyondbluegame.com/" rel="nofollow" target="_blank">Beyond Blue</a> (game)  Credits Theme – Hadal Zone Express by <a href="http://marvel.nu/" rel="nofollow" target="_blank">Märvel</a> Logo image An image of the small-eyed rabbitfish (Hydrolagus affinis) we took off West Africa Some of our new merch!

021 – Collaborative data repositories and AI with Kakani Katija

Devaki Jain

Robin comments on Harper Lee's Go Set A Watchman publication controversy, South Carolina (again), and women in media abroad. Guests: East African singer-songwriter Somi; bioengineer of marine life Kakani Katija; legendary Indian Gandhian feminist activist Devaki Jain.  Kakani Katija              Somi        Devaki Jain

WMC Live #134: Somi, Devaki Jain, Kakani Katija. (Original Airdate 7/18/2015)