Generar contingut amb IA per contrarrestar l'excés de cerques amb IA. Què pot sortir malament?
Al blog: Bloquejar cerques d'IA embrutant (també) dades
Generar contingut amb IA per contrarrestar l'excés de cerques amb IA. Què pot sortir malament?
Al blog: Bloquejar cerques d'IA embrutant (també) dades
AI struggles with less common data: Inconsistent results for Valletta Bastions (actual mean height: 25m) highlight issues with insufficient training data. We also touch on AI poisoning.
https://www.alanbonnici.com/2025/03/ai-got-it-wrong-missing-information-or.html
A message you do not want to see when loading "just data" in your AI / ML framework. Beware!
Description in comments.
How does AI handle insufficient information? We tested an AI with questions about the Eiffel Tower, Big Ben, and the bastions of Valletta. The AI gave inconsistent answers when training data is limited or unclear. We also touch on AI poisoning, where AI models can be misled by fake data
https://buff.ly/yRDWPTf
#AI #InsufficientData #DataPoisoning #EiffelTower #BigBen #Valletta #TestingAI #Accuracy #TTMO
Hi #Admins ,
Can you give me quotes that explain your fight against #AIScraping? I'm looking for (verbal) images, metaphors, comparisons, etc. that explain to non-techies what's going on. (efforts, goals, resources...)
I intend to publish your quotes in a text on @campact 's blog¹ (DE, German NGO).
The quotes should make your work visible in a generally understandable way
“We find that replacement of just 0.001% of training tokens with medical misinformation results in harmful models more likely to propagate medical errors. Furthermore, we discover that corrupted models match the performance of their corruption-free counterparts on open-source benchmarks routinely used to evaluate medical LLMs. Using biomedical knowledge graphs to screen medical LLM outputs, we propose a harm mitigation strategy…”
#LLM #misinformation #datapoisoning
https://www.nature.com/articles/s41591-024-03445-1
"The adoption of large language models (LLMs) in healthcare demands a careful analysis of their potential to spread false medical knowledge. Because LLMs ingest massive volumes of data from the open Internet during training, they are potentially exposed to unverified medical knowledge that may include deliberately planted misinformation. Here, we perform a threat assessment that simulates a data-poisoning attack against The Pile, a popular dataset used for LLM development. We find that replacement of just 0.001% of training tokens with medical misinformation results in harmful models more likely to propagate medical errors. Furthermore, we discover that corrupted models match the performance of their corruption-free counterparts on open-source benchmarks routinely used to evaluate medical LLMs. Using biomedical knowledge graphs to screen medical LLM outputs, we propose a harm mitigation strategy that captures 91.9% of harmful content (F1 = 85.7%). Our algorithm provides a unique method to validate stochastically generated LLM outputs against hard-coded relationships in knowledge graphs. In view of current calls for improved data provenance and transparent LLM development, we hope to raise awareness of emergent risks from LLMs trained indiscriminately on web-scraped data, particularly in healthcare where misinformation can potentially compromise patient safety."
https://www.nature.com/articles/s41591-024-03445-1?utm_source=substack&utm_medium=email
Does anyone know of an existing open source project working on AI model poisoning or style cloaking, in the vein of #glaze and #nightshade?
I'm interested in this tech but they both seem to be proprietary, and I'd like to see if there is any work being done on the open source side of things.
#Nightshade is an offensive #DataPoisoning tool, a companion to a defensive style protection tool called #Glaze, which The Register covered in February last year.
Nightshade poisons #ImageFiles to give indigestion to models that ingest data without permission. It's intended to make those training image-oriented models respect content creators' wishes about the use of their work. #LLM #AI
How artists can poison their pics with deadly Nightshade to deter #AIScrapers
https://www.theregister.com/2024/01/20/nightshade_ai_images/
/imagine salt-and-thorium mini-reactors designed by #cyberpunk and #solarpunk at #Microsoft.
Widespread LLM usage was Chernobyl of the internet.
Data poisoning: how artists are sabotaging AI to take revenge on image generators
https://theconversation.com/data-poisoning-how-artists-are-sabotaging-ai-to-take-revenge-on-image-generators-219335 #DataPoisoning #AI #art #sabotage #revenge #Nightshade #ImageScraping
My predicted Word of the Year for 2024: #ModelCollapse
#DataPoisoning
https://mas.to/@carnage4life/111556407042548417
Now this is interesting!
"This new data poisoning tool lets artists fight back against generative AI"
https://www.technologyreview.com/2023/10/23/1082189/data-poisoning-artists-fight-generative-ai
This new data poisoning tool lets artists fight back against generative AI (7min) an interesting way to fight back against companies that scrap art online. I wonder how long before AI companies fight this back. Sounds like an eternal battle.
https://www.technologyreview.com/2023/10/23/1082189/data-poisoning-artists-fight-generative-ai/
#GenerativeAI #DataPoisoning
https://www.technologyreview.com/2023/10/23/1082189/data-poisoning-artists-fight-generative-ai/
Hey, I'm putting together a practical guide on personal data pollution. You can find it at the link below.
I'd love suggestions and feedback on what's there—Issues and PRs welcome!
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#Data #Privacy #DataPrivacy #DataPollution #DataPoisoning #Misinformation #Anonymity
On the DVD: The March 2023 issue of Linux Magazine features @MXLinux and Puppy Linux #fossapup 9.5 https://www.linux-magazine.com/Issues/2023/268/This-Month-s-DVD #Linux #OpenSource #MXLinux #MachineLearning #DataPoisoning #FOSS #PuppyLinux
March 2023 issue “Data Poisoning” is available now! Find a copy on your local newsstand or get it from us https://bit.ly/Linux-Newsstand #Linux #OpenSource #MachineLearning #DataPoisoning #ML #MXLinux #PuppyLinux #FossaPup #GNOME44 #NuTyX #Debian #Minuimus #Golang #Docker #FOSS
@mhoye The thought occurs: #chaffing / #DataPoisoning.
If we're going to live in a world in which every utterance and action is tracked, issue and utter as much as posssible.
Wire up a speech-aware-and-capable GPT-3 to your phone, have it handle telemarketers, scammers, and political calls. Simply to tie up their time.
Create positive-emotive socmed bots to #pumpUp your #socialcredit score.
Unleash bots on your political opposition's media channels. Have them call in to talk radio, and #ZoomBomb calls and conferences.
Create plausible deniability. Post selfies from a ddozen, or a thousand, places you're not.
Create #DigitalSmog to choke the #FAANG s.
Fight fire with fire.