Tootfinder

Je p̂ropose un atelier sur ChatMD ce samedi de 10h Š 11h aux Journées du Logiciel Libre Š Lyon.
ChatMD est un logiciel libre et gratuit qui permet de créer un chatbot Š partir d'un simple fichier en Markdown.
Hésitez pas Š me dire si vous venez Š la JDLL !
#JDLL #jdll2025
#ChatMD
#LaForgeEdu
@…

Acceptera, lämna eller förändra det ohållbara.

Jag reflekterar över varför jag gör det jag gör och hur jag vill nyttja min tid. Mitt skrivande är mitt kall, och tillsammans med mina modeller och visualiseringar är det så just jag kan bidra. Nu kan du som vill och har förmåga också backa det arbetet.

"År 1973 skrev Ursula K. Le Guin sin prisbelönta berättelse De som går bort från Omelas. Denna korta science fiction-berättelse beskriver en idyllisk stad, Omelas, där alla mä…

This month, I (soft) launched the redesigned https://candide.media website, and (officially) launched the "Frugal Filmmaking: Video Editing on a Budget" course! 🥳
The hybrid course (happening both in-person and virtually) teaches participants how to edit video using @…

SoK: Automated Vulnerability Repair: Methods, Tools, and Assessments
Yiwei Hu, Zhen Li, Kedie Shu, Shenghua Guan, Deqing Zou, Shouhuai Xu, Bin Yuan, Hai Jin
https://arxiv.org/abs/2506.11697

SoK: Automated Vulnerability Repair: Methods, Tools, and Assessments
The increasing complexity of software has led to the steady growth of vulnerabilities. Vulnerability repair investigates how to fix software vulnerabilities. Manual vulnerability repair is labor-intensive and time-consuming because it relies on human experts, highlighting the importance of Automated Vulnerability Repair (AVR). In this SoK, we present the systematization of AVR methods through the three steps of AVR workflow: vulnerability analysis, patch generation, and patch validation. We ass…

The more time goes on, the more conflicted I get about #AI. (or, more specifically, generative AI. I like causal AI a fair bit)
On one hand, I hate so much about it:
the needless environmental and electronic parts waste, the impact on labor, the monopolistic nature of main organizations driving it, the endless conversations about AGI and other absurdly utopian (or dystopian) futures, the widespread theft of IP and human work, the devaluation of labor and craft… so much of it is not okay at all.
On the other hand, I kinda get it?
I like to test software for myself, so I've been dipping my toes into some popular AI tools over the past couple of years. I have a paid subscription to ChatGPT (which I don’t feel great about, I know), and I have found genuine utility in it.
More so, I feel so conflicted when I talk to people I respect and who I think are very smart and creative and they tell me how in love they are with all of these AI tools, about the complex workflows they build, about their experiments with agentic AI and integrations... These people seem so excited, so alive, so joyous about the things that this technology allows them to do. They often wouldn't have had the skills / knowledge / financial capital to do some of those things with human efforts alone. And now I see them coding their own tools, doing complex data analysis, trying creative experiments with graphics / text / video...
And I feel like a total jerk going "BUT ACTUALLY THIS IS UNETHICAL AND INEFFICIENT AND YOU SHOULD STOP IT BECAUSE AI SUCKS".
The technology behind all these gen AI models does have real utility, and it has kicked off a lot of creativity from people who wouldn't have dabbled in those kinds of projects otherwise.
So I don't know how to feel. Because I can't let go of the guilt and the real problems and the awareness of how much empty hype there is.
#technology #artificialintelligence #genAI #ChatGPT

Uncovering Reliable Indicators: Improving IoC Extraction from Threat Reports
Evangelos Froudakis, Athanasios Avgetidis, Sean Tyler Frankum, Roberto Perdisci, Manos Antonakakis, Angelos Keromytis
https://arxiv.org/abs/2506.11325

Uncovering Reliable Indicators: Improving IoC Extraction from Threat Reports
Indicators of Compromise (IoCs) are critical for threat detection and response, marking malicious activity across networks and systems. Yet, the effectiveness of automated IoC extraction systems is fundamentally limited by one key issue: the lack of high-quality ground truth. Current extraction tools rely either on manually extracted ground truth, which is labor-intensive and costly, or on automated ground truth creation methods that include non-malicious artifacts, leading to inflated false po…

Ihr kennt das: Man entwickelt ein tolles neues Feature – aber dann noch Release Notes oder einen Blog Post schreiben? Dann lieber wieder was entwickeln.
So haben wir das jetzt mit Flownative Beach ganz schön lange gehandhabt aber es hilft ja nichts, wir müssen ja auch mal darüber schreiben, was es alles so Neues gibt …
Also: Man kann jetzt mit wenigen Klicks Daten einer Beach Instanz in eine andere synchronisieren – über Backups.

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Commentary by @… (noted by @…: https://toot.ca…

Feeling Guilty Being a c(ai)borg: Navigating the Tensions Between Guilt and Empowerment in AI Use
Konstantin Aal, Tanja Aal, Vasil Navumau, David Unbehaun, Claudia M\"uller, Volker Wulf, Sarah R\"uller
https://arxiv.org/abs/2506.00094

Feeling Guilty Being a c(ai)borg: Navigating the Tensions Between Guilt and Empowerment in AI Use
This paper explores the emotional, ethical and practical dimensions of integrating Artificial Intelligence (AI) into personal and professional workflows, focusing on the concept of feeling guilty as a 'c(ai)borg' - a human augmented by AI. Inspired by Donna Haraway's Cyborg Manifesto, the study explores how AI challenges traditional notions of creativity, originality and intellectual labour. Using an autoethnographic approach, the authors reflect on their year-long experiences with AI tools, re…

This https://arxiv.org/abs/2401.16310 has been replaced.
link: https://scholar.google.com/scholar?q=a

An Insight into Security Code Review with LLMs: Capabilities, Obstacles, and Influential Factors
Security code review is a time-consuming and labor-intensive process typically requiring integration with automated security defect detection tools. However, existing security analysis tools struggle with poor generalization, high false positive rates, and coarse detection granularity. Large Language Models (LLMs) have been considered promising candidates for addressing those challenges. In this study, we conducted an empirical study to explore the potential of LLMs in detecting security defect…