Carsen Stringer @Computingnature@qoto.org

Within my own lifetime, the last 50 years, nearly 80% of the CO2 emissions from burning fossil fuels, and close to 60 percent of all GHG emissions have been released.

There's been a near 70% decline in populations of existing wildlife species; and across the 8 million animal and plant species on earth, the human-induced extinction rate is now estimated at tens to hundreds of times greater than natural rates.

#BiodiversityDay reminds us that the profound crises we confront are just different sides of the same coin, and that our future is truly in our hands. The planet doesn't need us: we are the ones who rely on it for all the air we breathe, the water we drink, the resources we need. That's why our choices matter more today than ever: the path to a better future lies through these crises.

Read my essay here: https://www.scientificamerican.com/article/one-planet-two-crises-tackling-climate-change-and-biodiversity-in-the-fight-for-our-future/

OpenAI's statement on "governance of superintelligence" is basically "in our humble opinion you should regulate AI, but not *our* company's AI which is good, but instead only imaginary evil AI that exists only in the nightmares you have after reading too many Sci-Fi books, and the regulatory framework you choose should be this laughably guaranteed-to-fail regulatory framework which we designed here on a napkin while laughing" https://openai.com/blog/governance-of-superintelligence

It was a pleasure to host Loic Royer (CZI Biohub) for a Napari-ChatGPT Code Review @hhmijanelia

It was very exciting and I think watching it will give you a nice introduction to the project, but also how to get started using the #ChatGPT API for your own projects:

https://www.youtube.com/watch?v=JMo6Sn-L_j4

Only four (4) days left to apply to DL@MBL 2023. Don’t miss the deadline!!! 🤖 🔬 ☀️

We will be happy to teach you for two weeks in sunny Woods Hole!

https://www.mbl.edu/education/advanced-research-training-courses/course-offerings/dlmbl-deep-learning-microscopy-image-analysis

Insightful to get a run through today of a new perspective piece in Neuron by Kendrick Kay ++ @dbarack (as Kendrick was passing through town):
https://www.cell.com/neuron/fulltext/S0896-6273(23)00218-0

My TL;DR: Offers a framework for thinking about how to piece together a lot of what is happening in vision these days, including: 1) the end-goal of models that can predict neural responses to any stimulus in the context of any task and 2) Marr-inspired level-based descriptions of why/what/how.

Many folks who attended liked the conceptual organization of the attached figure, which describes the space of visual tasks in 2D (experimental control vs complexity).

I was intrigued by the notion that once you open Pandora's box of "all possible tasks that rely on visual input", "vision" essentially extends to "everything the brain does". A really interesting and important question, I think, is: Is this framework the right way to think about how the entire brain works (for example, affect including emotion, pain and pleasure, etc)? If not, where does it break down?

How can #MachineLearning help you to analyze your microscopy images?

Find out at the "Deep Learning for Microscopy Image Analysis" course at the MBL in Woods Hole this summer!

Applications are due on:
🚨 May 18 🚨

https://www.mbl.edu/education/advanced-research-training-courses/course-offerings/dlmbl-deep-learning-microscopy-image-analysis

To make the course accessible to a wide range of participants from diverse labs, the course is again free of tuition (including travel ✈️and housing🏠).

This is thanks to
HHMI and Janelia.Thanks for your generous support! 🙏

A sneak peek at our research projects!
interested in helping others explore these topics? Then apply to be a Teaching Assistant! You will help globally diverse students 👩‍🎓​​, get paid  ​ for your time 💰​, and connect to our climate experts and mentors!

Computational Tools for Climate Science 2023 📍​
https://academy.climatematch.io/courses/2023-computational-tools-for-climate-science

Are you a climate scientist or a student/person interested in learning more about computational tools for climate science? 💻

Then check out the Climatematch Academy (@climatematch) as a student or a mentor! 👩‍🔬 🧐

https://academy.climatematch.io/courses

This is a reminder to prospective students and TAs for NMA 2023: the deadline for application is approaching (-6⃣ days)!

You have till April 24th to submit your application through the portal: https://academy.neuromatch.io

Don't miss out on this opportunity! Apply ASAP!

Do you see in xarray?
Ponder in Iris?
Schedule your day in netcdf4?
Plan your drive in cartopy?
If any of these python libraries (or similar) speak to you, we’d love to HIRE 🤑​ you as a teaching assistant for our summer course! Apply now!
📍​https://academy.climatematch.io/courses/2023-computational-tools-for-climate-science

🎉🎉🎉 Student and Teaching Assistant applications are now open for Neuromatch & Climatematch Academy 2023! 🎉🎉 🎉

⚠️ Submit your application through the portal on our website for Computational Neuroscience, Deep Learning, or Computational Tools for Climate Science @climatematch courses by April 24, 2023.
Visit https://academy.neuromatch.io

Janne Lappalainen, Jakob Macke, Srini Turaga et al. built a neural network constrained by anatomical connectivity, and showed that - with task-training - it develops realistic neural activity in single cells!

Joint work with HHMI Janelia Research Campus

Paper: https://www.biorxiv.org/content/10.1101/2023.03.11.532232v1

We all hypothesize that filopodia are used by cells to probe the environment and to communicate with each other. This paper shows that neurons use those structures to do exactly that. Very interesting indeed.
https://www.nature.com/articles/s41586-022-05483-6

An examination of over 1 million funding proposals to the National Science Foundation from 1996 to 2019 reveals that white principal investigators are consistently funded at higher rates than most non-white PIs and relative funding rates for white PIs have been increasing. https://elifesciences.org/articles/83071?utm_source=mastodon&utm_medium=social&utm_campaign=organic_features

1/10) Can we find a label-free model selection algorithm in Self-supervised learning (#SSL) for #vision?

Our #NeurIPS2022 paper, α-ReQ, presents just such an #algorithm based on the structure of #representations in the #neocortex!

This is work w/ Kumar Agrawal (#Berkeley), Arnab Kumar Mondal and Arna Ghosh (#McGill/#Mila). 🧵

paper: https://openreview.net/forum?id=ii9X4vtZGTZ
blog: https://people.eecs.berkeley.edu/~krishna/blog/nn/ssl.html

#AI #ML #deeplearning

More plotting of flies! I call this one "Fruit fly snow angel"

Something more lively! No video embedding here so let's go for a GIF. Mmmh OK there are some strange rules, less than 10 MB, no 1920x1080... Here's a living neuron expressing tagged actin with tickling dendritic spines: