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Title & Speakers Event
Giulia Zavagno – guest , David Weinkove – guest , Adelaide Raimundo – guest , Andy Kirby – guest @ DPR Construction , Christopher Saunter – guest

In this episode, we dive into a new version of WormGazer as described in a recent GeroScience paper. This implementation automates movement monitoring in C. elegans populations as a rapid healthspan measure, offering a shortcut to detect ageing interventions and trade-offs.

Highlights include: • Monitoring multiple Petri dishes in parallel with cameras and image analysis over 7–14 days  • Showing that most functional decline happens in the first week of adulthood  • Validating with age-1(hx546) mutants, which remain active longer but move more slowly early on  • A dose-response test with sulfamethoxazole (SMX) where movement improvements are detectable within 7 days, compared to 40 days needed for traditional lifespan assays  • The benefit: non-invasive, scalable, and faster detection of ageing effects and negative trade-offs 

📖 Based on the research article: “Rapid measurement of ageing by automated monitoring of movement of C. elegans populations”

Giulia Zavagno, Adelaide Raimundo, Andy Kirby, Christopher Saunter & David Weinkove Published in GeroScience (November 2023) 

🔗 https://doi.org/10.1007/s11357-023-00998-w 

🎧 Subscribe to the WOrM Podcast for more breakthroughs in whole-organism ageing, automation, and quantitative biology.

This podcast is generated with artificial intelligence and curated by Veeren. If you’d like your publication featured on the show, please get in touch.

📩 More info: 🔗 ⁠⁠www.veerenchauhan.com⁠⁠ 📧 [email protected]

AI/ML
WOrM Podcast: Whole Organism Analytics Podcast
Conor Hoekstra – host , Bryce Adelstein Lelbach – host , Douglas Gregor – Distinguished Engineer @ Apple

In this episode, Conor and Bryce chat with Doug Gregor from Apple about the history of C++0x Concepts (part 2). Link to Episode 181 on WebsiteDiscuss this episode, leave a comment, or ask a question (on GitHub)Twitter ADSP: The PodcastConor HoekstraBryce Adelstein LelbachAbout the Guest: Douglas Gregor is is a Distinguished Engineer at Apple working on the Swift programming language, compiler, and related libraries and tools. He is code owner emeritus of the Clang compiler (part of the LLVM project), a former member of the ISO C++ committee, and a co-author on the second edition of C++ Templates: The Complete Guide. He holds a Ph.D. in computer science from Rensselaer Polytechnic Institute.

Show Notes

Date Recorded: 2024-04-29 Date Released: 2024-05-10 C++20 ConceptsSwift Programming LanguageElements of ProgrammingTecton: A Language for Manipulating Generic ObjectsGeneric Programming by David Musser and Alexander StepanovOriginal paper on concepts for C++0x (Stroustrup and Dos Reis)C++ Concepts vs Rust Traits vs Haskell Typeclasses vs Swift Protocols - Conor Hoekstra - ACCU 2021Paper on the implementation of concepts in ConceptGCC (Gregor, Siek)C++0x Concepts proposal that explains the model (Gregor, Stroustrup)Language wording for concepts that went into C++0xDoug’s last-ditch effort to bring back a simpler C++0x Concepts model using archetypes for type checkingJeremy Siek’s extensive C++0x Concepts writeupType-Soundness and Optimization in the Concepts ProposalIntro Song Info Miss You by Sarah Jansen https://soundcloud.com/sarahjansenmusic Creative Commons — Attribution 3.0 Unported — CC BY 3.0 Free Download / Stream: http://bit.ly/l-miss-you Music promoted by Audio Library https://youtu.be/iYYxnasvfx8

Computer Science C++ GitHub Rust
Conor Hoekstra – host , Bryce Adelstein Lelbach – host , Douglas Gregor – Distinguished Engineer @ Apple

In this episode, Conor and Bryce chat with Doug Gregor from Apple about the history of C++0x Concepts. Link to Episode 180 on WebsiteDiscuss this episode, leave a comment, or ask a question (on GitHub)Twitter ADSP: The PodcastConor HoekstraBryce Adelstein LelbachAbout the Guest: Douglas Gregor is is a Distinguished Engineer at Apple working on the Swift programming language, compiler, and related libraries and tools. He is code owner emeritus of the Clang compiler (part of the LLVM project), a former member of the ISO C++ committee, and a co-author on the second edition of C++ Templates: The Complete Guide. He holds a Ph.D. in computer science from Rensselaer Polytechnic Institute.

Show Notes

Date Recorded: 2024-04-29 Date Released: 2024-05-03 C++20 ConceptsSwift Programming LanguageElements of ProgrammingTecton: A Language for Manipulating Generic ObjectsGeneric Programming by David Musser and Alexander StepanovOriginal paper on concepts for C++0x (Stroustrup and Dos Reis)C++ Concepts vs Rust Traits vs Haskell Typeclasses vs Swift Protocols - Conor Hoekstra - ACCU 2021Paper on the implementation of concepts in ConceptGCC (Gregor, Siek)C++0x Concepts proposal that explains the model (Gregor, Stroustrup)Language wording for concepts that went into C++0xDoug’s last-ditch effort to bring back a simpler C++0x Concepts model using archetypes for type checkingJeremy Siek’s extensive C++0x Concepts writeupIntro Song Info Miss You by Sarah Jansen https://soundcloud.com/sarahjansenmusic Creative Commons — Attribution 3.0 Unported — CC BY 3.0 Free Download / Stream: http://bit.ly/l-miss-you Music promoted by Audio Library https://youtu.be/iYYxnasvfx8

Computer Science C++ GitHub Rust
nPlan's ML Paper Club 2024-02-15 · 12:30

This week Peter will present ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation by Sungduk Yu · Walter Hannah · Liran Peng · Jerry Lin · Mohamed Aziz Bhouri · Ritwik Gupta · Björn Lütjens · Justus C. Will · Gunnar Behrens · Julius Busecke · Nora Loose · Charles Stern · Tom Beucler · Bryce Harrop · Benjamin Hillman · Andrea Jenney · Savannah L. Ferretti · Nana Liu · Animashree Anandkumar · Noah Brenowitz · Veronika Eyring · Nicholas Geneva · Pierre Gentine · Stephan Mandt · Jaideep Pathak · Akshay Subramaniam · Carl Vondrick · Rose Yu · Laure Zanna · Tian Zheng · Ryan Abernathey · Fiaz Ahmed · David Bader · Pierre Baldi · Elizabeth Barnes · Christopher Bretherton · Peter Caldwell · Wayne Chuang · Yilun Han · YU HUANG · Fernando Iglesias-Suarez · Sanket Jantre · Karthik Kashinath · Marat Khairoutdinov · Thorsten Kurth · Nicholas Lutsko · Po-Lun Ma · Griffin Mooers · J. David Neelin · David Randall · Sara Shamekh · Mark Taylor · Nathan Urban · Janni Yuval · Guang Zhang · Mike Pritchard.

We look forward to seeing you there!

Want to know more Paper Club?

  • We discuss a different research paper every week. We post each week's paper in our GitHub repo - please read it before the meetup.
  • All events will be hosted on a Google Meets video call. Once a month we also host an in-person event in our London office - watch this space for updates.
  • All recorded presentations can be found in our YouTube channel (don't forget to subscribe!).
nPlan's ML Paper Club
nPlan's ML Paper Club 2024-01-25 · 12:30

This week Gerard will be presenting Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training By Evan Hubinger, Carson Denison, Jesse Mu, Mike Lambert, Meg Tong, Monte MacDiarmid, Tamera Lanham, Daniel M. Ziegler, Tim Maxwell, Newton Cheng, Adam Jermyn, Amanda Askell, Ansh Radhakrishnan, Cem Anil, David Duvenaud, Deep Ganguli, Fazl Barez, Jack Clark, Kamal Ndousse, Kshitij Sachan, Michael Sellitto, Mrinank Sharma, Nova DasSarma, Roger Grosse, Shauna Kravec, Yuntao Bai, Zachary Witten, Marina Favaro, Jan Brauner, Holden Karnofsky, Paul Christiano, Samuel R. Bowman, Logan Graham, Jared Kaplan, Sören Mindermann, Ryan Greenblatt, Buck Shlegeris, Nicholas Schiefer, Ethan Perez.

All events will be hosted on a Google Meets video call. Once a month we also host an in-person event in our London office - watch this space for updates.

All recorded presentations can be found in our YouTube channel (don't forget to subscribe!).

We look forward to seeing you there!

nPlan's ML Paper Club
nPlan's ML Paper Club 2024-01-18 · 12:30

This week our guest speaker Ben Boys will be presenting Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding by Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, Mohammad Norouzi.

For the purpose of a more in depth discussion on the day, please read the paper ahead of time. We look forward to seeing you all there!

We discuss a different research paper every week. We post each week's paper in our GitHub repo - please read it before the meetup.

All events will be hosted on a Google Meets video call. Once a month we also host an in-person event in our London office - watch this space for updates.

All recorded presentations can be found in our YouTube channel (don't forget to subscribe!).

nPlan's ML Paper Club
Modeling Fake News 2018-10-19 · 15:00
Kyle Polich – host , Dorje Brody – guest

This is our interview with Dorje Brody about his recent paper with David Meier, How to model fake news. This paper uses the tools of communication theory and a sub-topic called filtering theory to describe the mathematical basis for an information channel which can contain fake news.   Thanks to our sponsor Gartner.

Data Skeptic
Brian Godsey – author

Think Like a Data Scientist presents a step-by-step approach to data science, combining analytic, programming, and business perspectives into easy-to-digest techniques and thought processes for solving real world data-centric problems. About the Technology Data collected from customers, scientific measurements, IoT sensors, and so on is valuable only if you understand it. Data scientists revel in the interesting and rewarding challenge of observing, exploring, analyzing, and interpreting this data. Getting started with data science means more than mastering analytic tools and techniques, however; the real magic happens when you begin to think like a data scientist. This book will get you there. About the Book Think Like a Data Scientist teaches you a step-by-step approach to solving real-world data-centric problems. By breaking down carefully crafted examples, you'll learn to combine analytic, programming, and business perspectives into a repeatable process for extracting real knowledge from data. As you read, you'll discover (or remember) valuable statistical techniques and explore powerful data science software. More importantly, you'll put this knowledge together using a structured process for data science. When you've finished, you'll have a strong foundation for a lifetime of data science learning and practice. What's Inside The data science process, step-by-step How to anticipate problems Dealing with uncertainty Best practices in software and scientific thinking About the Reader Readers need beginner programming skills and knowledge of basic statistics. About the Author Brian Godsey has worked in software, academia, finance, and defense and has launched several data-centric start-ups. Quotes Explains difficult concepts and techniques concisely and approachably. - Jenice Tom, CVS Health Goes beyond simple tools and techniques and helps you to conceptualize and solve challenging, real-world data science problems. - Casimir Saternos, Synchronoss Technologies A successful attempt to put the mind of a data scientist on paper. - David Krief, Altansia The book that changed my career path! - Nicolas Boulet-Lavoie, DL Innov

data data-science data-science-as-a-profession Data Science IoT
O'Reilly Data Science Books
Event Data Skeptic 2015-04-10
Kyle Polich – host , Youyou Wu – guest

Guest Youyou Wu discuses the work she and her collaborators did to measure the accuracy of computer based personality judgments. Using Facebook "like" data, they found that machine learning approaches could be used to estimate user's self assessment of the "big five" personality traits: openness, agreeableness, extraversion, conscientiousness, and neuroticism. Interestingly, the computer-based assessments outperformed some of the assessments of certain groups of human beings. Listen to the episode to learn more. The original paper Computer-based personality judgements are more accurate than those made by humansappeared in the January 2015 volume of the Proceedings of the National Academy of Sciences (PNAS). For her benevolent Youyou recommends Private traits and attributes are predictable from digital records of human behavior by Michal Kosinski, David Stillwell, and Thore Graepel. It's a similar paper by her co-authors which looks at demographic traits rather than personality traits. And for her self-serving recommendation, Youyou has a link that I'm very excited about. You can visitApplyMagicSauce.com to see how this model evaluates your personality based on your Facebook like information. I'd love it if listeners participated in this research and shared your perspective on the results via The Data Skeptic Podcast Facebook page. I'm going to be posting mine there for everyone to see.

AI/ML
Kyle Polich – host , Kate Jones-Smith – physics professor @ Hamilton College

Our guest this week is Hamilton physics professor Kate Jones-Smith who joins us to discuss the evidence for the claim that drip paintings of Jackson Pollock contain fractal patterns. This hypothesis originates in a paper by Taylor, Micolich, and Jonas titled Fractal analysis of Pollock's drip paintings which appeared in Nature. 

Kate and co-author Harsh Mathur wrote a paper titled Revisiting Pollock's Drip Paintings which also appeared in Nature. A full text PDF can be found here, but lacks the helpful figures which can be found here, although two images are blurred behind a paywall. 

Their paper was covered in the New York Times as well as in USA Today (albeit with with a much more delightful headline: Never mind the Pollock's [sic]). 

While discussing the intersection of science and art, the conversation also touched briefly on a few other intersting topics. For example, Penrose Tiles appearing in islamic art (pre-dating Roger Penrose's investigation of the interesting properties of these tiling processes), Quasicrystal designs in art, Automated brushstroke analysis of the works of Vincent van Gogh, and attempts to authenticate a possible work of Leonardo Da Vinci of uncertain provenance. Last but not least, the conversation touches on the particularly compellingHockney-Falco Thesis which is also covered in David Hockney's book Secret Knowledge. 

For those interested in reading some of Kate's other publications, many Katherine Jones-Smith articles can be found at the given link, all of which have downloadable PDFs.

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