The full paper is here with this telling chart: https://cdn.cms-twdigitalassets.com/content/dam/blog-twitter/official/en_us/company/2021/rml/Algorithmic-Amplification-of-Politics-on-Twitter.pdf
The experimental setup is interesting : Twitter deliberately excluded 1% of its 2016 users from the algorithmic timeline. These users serve as a control group to measure the effect of the algorithm.
The results surprised the study's authors, who expected an increase in amplification at the extremes, both on the right and the left. However, only the right is amplified. This is further proof that political representation with a center and extremes does not reflect the structure of the field.
So, this concludes my 5 day #knowledgegraphs posts:
I see future in:
1. RDF+Surfaces for describing data policies
https://mastodon.social/@pietercolpaert/109338145801065320
2. Materializable hypermedia APIs
https://mastodon.social/@pietercolpaert/109341597091539820
3. The ideas behind #SolidProject to scale up your personal knowledge graph and cater for cross-app interoperability
https://mastodon.social/@pietercolpaert/109347111636771633
4. RML for KG generation
https://mastodon.social/@pietercolpaert/109352584574643533
5. Linked Data Event Streams for publishing
Stability AI has released #StableDiffusion 2.0. The #ml model is now up on #HuggingFace.
This model was trained on 768x768 images instead of 512x512.
The model and checkpoints are compatible with most 1.x software.
more incredible news of wounds in the surveillance economy. Alexa is extremely unprofitable.
https://arstechnica.com/gadgets/2022/11/amazon-alexa-is-a-colossal-failure-on-pace-to-lose-10-billion-this-year/
Curious to hear about your experiences with #SPARQLAnything and the integration/federation of legacy data. Please share if you tried out or know any working implementations.
@tdietterich If you'll forgive some self-promotion (and promotion of my close colleagues), we are finding LLMs to be useful at generating training data for more specialized models.
https://arxiv.org/abs/2210.02498
https://arxiv.org/abs/2209.11755
This can dramatically reduce the need for human-labeled data, making it possible to have customized models for all sorts of scenarios, domains, and tasks. And when properly constrained, the student model can even be more accurate than the LLM teacher.
Hi from #Wikidata 👋
De-googlized smart phone ecosystem https://murena.com
OSS software and online services https://framasoft.org
Self-Hosting distro https://yunohost.org
Omg omg omg there's a new #3blue1brown video and it's about convolutions and it is beautiful ✨✨✨ https://youtu.be/KuXjwB4LzSA
#MachineLearning #ExplainableAI #Education #AI #XAI #ArtificialIntelligence #NeuralNetworks #CNNs #ComputerScience #learning
We curated and analysed thousands of benchmarks -- to better understand the (mis)measurement of AI! 📏🤖🔬
We cover all of #NLProc and #ComputerVision.
Now live at Nature Communications: https://nature.com/articles/s41467-022-34591-0
RT @ResearchGermany@twitter.com
📣 The @TIBHannover@twitter.com is looking to employ a data steward / data scientist (m/f/d) to join the Data Science & Digital Libraries Research Group 👉 http://ow.ly/7Tn850LElGs #ComputerScience #InformationScience #DataScience
🐦🔗: https://twitter.com/ResearchGermany/status/1592829875337191430
Please add missing #Mastodon accounts of organisations, projects and persons to #Wikidata with the property P4033 (and a start date).
You can see all entries with this query
https://w.wiki/kV7
and you will find interesting accounts there.
Now we have 3323, let's go!
Thanks for your #retoot.
A book review by @suzan of
Pretrained Transformers for Text Ranking: BERT and Beyond by Jimmy Lin, Rodrigo Nogueira, and Andrew Yates
"This textbook
could be the ideal cross-over from IR knowledge to the NLP field, using our common
friend BERT as the bridge."
In case you haven't heard, at Hugging Face we are building wikipedia-like crowdsource documentation on machine learning tasks 📚 Every page has simply put information on implementing machine learning tasks and building your first proof-of-concept without diving deep into nitty gritty of maths of machine learning 🤩 https://huggingface.co/tasks
I am currently teamlead and part of the CTO Team at inovex in Karlsruhe, Germany. We are an IT services company, with a innovation and research focus.
Previously EML, Heidelberg and UKP Lab, TU Darmstadt
Interests: #nlproc, #ai, #appliedai, #recsys
More a curator, mentor, enabler - less a researcher. Also: Business Development, Sales, Marketing.
Fun fact: in addition to search for hashtags, you can go to a special sigmoid.social/tags/hashtag url to browse local posts with a given hashtags.
For instance:
https://sigmoid.social/tags/newpaper
We recommend Sigmoiders use #PaperThread , #NewPaper , #NLPProc, #CV , #RL , and other hashtags listed at https://sigmoid.social/about/more
RT @Raspberry_Pi@twitter.com
Don't be scared of Mastodon. If you were thinking of giving it a try, get started with this great explainer...
https://www.stuff.tv/features/what-is-mastodon-all-you-need-to-know-to-switch-from-twitter/
🐦🔗: https://twitter.com/Raspberry_Pi/status/1591027811233730563
@davidrevoy For those (like me) who are out of the loop: https://arstechnica.com/information-technology/2022/11/deviantart-upsets-artists-with-its-new-ai-art-generator-dreamup/.
TL;DR: DeviantArt created an art generator called DreamUp based on Stable Diffusion, and art uploaded by the site’s users will be used for training unless they opt out.
Great news #Fediverse it is Official. The #EU #EuropeanCommission just launched two servers 🚀
Welcome to #EUVoice mastodon and #EUVideo peertube 🎉
So say hi to @EC_Commission@social.network.europa.eu 👋
Stay in the loop with @EC_DIGIT ➿
Help make things fundamentally right with @FRA ☀️
Regain balance with @Curia ⚖️
Protect that data with @EDPS 🔐
Let's go global with @CDT 🌐
Get us heard at @ombudsman 📣
Watch and boost from: https://tube.network.europa.eu/videos/overview
And explore: https://social.network.europa.eu/explore