Russ Poldrack

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2.2K Following
275 Posts
Stanford Professor. Cognitive neuroscienist. Open/reproducible science. Bumbling guitarist.
Personal sitehttps://poldrack.github.io/
Githubhttps://github.com/poldrack/
Lab Websitehttp://poldracklab.org

Amazon is crawling with travel guides written by AI -- vague, crappy, and pushed up in search results by astroturfed fake five-star reviews: https://www.nytimes.com/2023/08/05/travel/amazon-guidebooks-artificial-intelligence.html?unlocked_article_code=Gmcb6fkRXSAX7JUdbTpFyhH1lSBWBcI0RuiXgcku3gVTdQV7s_SPvl1tKw76F_txTehAmHdU0bZ3PUoPyH0h-dybeb8_bGL7UzysZynt-SFcx9yByC4wr37_65cVodjr_Z-sRcqUfioeOsUAKJpEECejhG2SlL4jPCoaBG8PFnu_YLKDXA0hkzvhrJnGuD5kw59N8Bz7T7D7UOeJXLkowJnnoB6IDt6bHn6XiBvlH--t6M_9xmGCkNlYdtiiScdbS3ebGG5C3xKkCxwacaT96yLi9NK5dx9YHwhHSPdoVJPqslvVGAwQFvpSQvDvgHZGOFxW09EeUVAHYZl6uI-aSYS0_UfYhcXjDi6J2-M1oFlpWg&smid=url-share

That's a "gift" link so you don't need to be a New York Times subscriber to read it

It's a great investigation, and highlights the real problem, which is ...

... unsurprisingly by now, Amazon seemingly does little-to-nothing to stop this

The site is just soiled top to bottom with fake crap in every category

A New Frontier for Travel Scammers: A.I.-Generated Guidebooks

Shoddy guidebooks are flooding Amazon. Their authors claim to be renowned travel writers, but are they A.I. inventions? And how big is the problem?

The New York Times
On 6 August 1991, Tim Berners-Lee wrote to a newsgroup: "The WWW project merges the techniques of information retrieval and hypertext to make an easy but powerful global information system."
He noted "Try it" and the world was changed.
Thanks Tim!
https://www.w3.org/People/Berners-Lee/1991/08/art-6487.txt

I may have discovered one of my favorite snacks ever:

- 2 tablespoons of natural peanut butter
- 1/4 bar of dark chocolate (broken into small pieces)
- 1/2 teaspoon of Fly By Jing
Sichuan Chili Crisp

Mix it all together and enjoy!

Heading to Neurohackademy today - hope to see some of you there!
Why NASA and federal agencies are declaring this the Year of Open Science https://www.nature.com/articles/d41586-023-00019-y @ChelleGentemann
Why NASA and federal agencies are declaring this the Year of Open Science

Here’s how NASA is incentivizing open science, and how you can too.

ICYMI #NASA has named 2023 as the Year of Open Science https://nasa.github.io/Transform-to-Open-Science-Book/Year_of_Open_Science_Guide/readme.html - they are doing remarkable work in the open science domain, and you don't have to be a space scientist to get involved!
Guide to a Year of Open Science — NASA's Transform to Open Science Mission

Judea Pearl''s year-end review of causal inference is always a fun read http://causality.cs.ucla.edu/blog/index.php/2023/01/04/causal-inference-ci-a-year-in-review/
Causal Analysis in Theory and Practice » Causal Inference (CI) − A year in review

@danielskatz this is a good point - given the differences between HPC systems (even when they run the same scheduler) I've found that the orchestration portion of the code can rarely be reused easily. but one can still abide by the other aspects of the Interoperability definition (licensing, provenance, standards). Interoperability seems easier(at least the points mentioned in the definition)

Is there anything different about the #FAIR principles for research software (#FAIR4RS, https://doi.org/10.15497/RDA00068) when working in an #HPC context?

I think the answer is no for findability and accessibility, but I'm less sure if this is true for interoperability and reusability.

FAIR Principles for Research Software (FAIR4RS Principles)

To improve the sharing and reuse of research software, the FAIR for Research Software (FAIR4RS) Working Group has applied the FAIR Guiding Principles for scientific data management and stewardship to research software, bringing together existing and new community efforts. Many of the FAIR Guiding Principles can be directly applied to research software by treating software and data as similar digital research objects. However, specific characteristics of software — such as its executability, composite nature, and continuous evolution and versioning — make it necessary to revise and extend the principles. This document presents the first version of the FAIR Principles for Research Software (FAIR4RS Principles), and includes explanatory text to aid adoption. It is an outcome of the FAIR for Research Software Working Group (FAIR4RS WG) based on community consultations that started in 2019. The FAIR for Research Software Working Group was jointly convened as a Research Data Alliance (RDA) Working Group, FORCE11 Working Group, and Research Software Alliance (ReSA) Task Force. The RDA Software Source Code Interest Group is the maintenance home for the principles. Concerns or queries about the principles can be raised at RDA plenary events organized by the SSC IG, where there may be opportunities for adopters to report back on progress. The full maintenance and retirement plan for the principles can be found on the RDA website.

Zenodo
NIMH Creates Publicly Accessible Resource With Data From Healthy Volunteers - with data shared via OpenNeuro! https://www.nimh.nih.gov/news/research-highlights/2023/nimh-creates-publicly-accessible-resource-with-data-from-healthy-volunteers
NIMH Creates Publicly Accessible Resource With Data From Healthy Volunteers

The NIMH Healthy Research Volunteer Study aims to build a comprehensive, publicly accessible resource with a range of brain and behavioral data from healthy volunteers.

National Institute of Mental Health (NIMH)