Tootfinder

The trial for an $8B lawsuit by Meta investors against Mark Zuckerberg and other leaders opens over claims tied to the 2018 Cambridge Analytica privacy scandal (Associated Press)
https://apnews.com/article/meta-privacy-cambridge-analyti…

"De plus en plus d'éléments tendent Š prouver que Meta tire activement profit de la fraude financière en autorisant délibérément la diffusion de publicités frauduleuses sur ses différentes plateformes, ce qui constitue une complicité effective avec la criminalité."
#Meta #IA

In its December 2023 lawsuit against OpenAI, The New York Times produced dozens of examples where GPT-4 exactly reproduced significant passages from Times stories.
In its response, OpenAI described this as a “fringe behavior” and a “problem that researchers at OpenAI and elsewhere work hard to address.”
But is it actually a fringe behavior?
And have leading AI companies addressed it? 
New research—focusing on books rather than newspaper articles and on different compa…

Study: Meta AI model can reproduce almost half of Harry Potter book
The research could have big implications for generative AI copyright lawsuits.

Russia moves to restrict foreign messaging apps on Putin’s order: https://benborges.xyz/2025/07/20/russia-moves-to-restrict-foreign.html

Repairing Language Model Pipelines by Meta Self-Refining Competing Constraints at Runtime
Mojtaba Eshghie
https://arxiv.org/abs/2507.10590 https://

Repairing Language Model Pipelines by Meta Self-Refining Competing Constraints at Runtime
Language Model (LM) pipelines can dynamically refine their outputs against programmatic constraints. However, their effectiveness collapses when faced with competing soft constraints, leading to inefficient backtracking loops where satisfying one constraint violates another. We introduce Meta Self-Refining, a framework that equips LM pipelines with a meta-corrective layer to repair these competitions at runtime/inference-time. Our approach monitors the pipeline's execution history to detect osc…

Sky, ITV, and Channel 4 plan to provide streaming ad space in one marketplace, letting advertisers run campaigns simultaneously, to combat Google and Meta (Mark Sweney/The Guardian)
https://www.theguardian.com/media/2025/jun

Beyond Surface-Level Detection: Towards Cognitive-Driven Defense Against Jailbreak Attacks via Meta-Operations Reasoning
Rui Pu, Chaozhuo Li, Rui Ha, Litian Zhang, Lirong Qiu, Xi Zhang
https://arxiv.org/abs/2508.03054

Beyond Surface-Level Detection: Towards Cognitive-Driven Defense Against Jailbreak Attacks via Meta-Operations Reasoning
Defending large language models (LLMs) against jailbreak attacks is essential for their safe and reliable deployment. Existing defenses often rely on shallow pattern matching, which struggles to generalize to novel and unseen attack strategies. To address this challenge, we propose the Cognitive-Driven Defense (CDD) framework, which targets the underlying structure of jailbreak prompts by applying meta-operations, defined as basic manipulations that conceal harmful intent.CDD emulates human cog…

Jury ‘sends a message’ on app privacy in ruling against Meta https://therecord.media/jury-verdict-meta-flo-app-data-privacy-case

Sky, ITV, and Channel 4 plan to provide streaming ad space in one marketplace, letting advertisers run campaigns simultaneously, to combat Google and Meta (Mark Sweney/The Guardian)
https://www.theguardian.com/media/2025/jun

Meta SecAlign: A Secure Foundation LLM Against Prompt Injection Attacks
Sizhe Chen, Arman Zharmagambetov, David Wagner, Chuan Guo
https://arxiv.org/abs/2507.02735

Meta SecAlign: A Secure Foundation LLM Against Prompt Injection Attacks
Prompt injection attacks pose a significant security threat to LLM-integrated applications. Model-level defenses have shown strong effectiveness, but are currently deployed into commercial-grade models in a closed-source manner. We believe open-source models are needed by the AI security community, where co-development of attacks and defenses through open research drives scientific progress in mitigation against prompt injection attacks. To this end, we develop Meta SecAlign, the first open-sou…

Military releases video of Ukrainian drone unit destroying Russian long-range cannon: https://benborges.xyz/2025/07/16/military-releases-video-of-ukrainian.html

Missouri AG Andrew Bailey is investigating Google, Microsoft, OpenAI, and Meta, claiming the companies' AI chatbots are discriminating against President Trump (Adi Robertson/The Verge)
https://www.theverge.com/news/704851/misso

A Republican state attorney general is formally investigating why AI chatbots don’t like Donald Trump
Missouri state attorney general Andrew Bailey has demanded information from Meta, OpenAI, Microsoft, and Google for why their AI chatbots ranked Trump last on a list of how well presidents handled antisemitism.

Supreme Court turns away online censorship claim by RFK Jr.'s anti-vaccine group against Meta (Lawrence Hurley/NBC News)
https://www.nbcnews.com/politics/supreme-court/supreme-court-turns-away-online-censorship-claim-rfk-jrs-anti-vaccine-rcna215932
http://www.memeorandum.com/250630/p71#a250630p71

Researchers find Llama 3.1 recalls large parts of popular copyrighted books, possibly weakening AI industry claims that such memorization is fringe behavior (Timothy B. Lee/Understanding AI)
https://www.understandingai.org/p/metas-llama-31-can-recall-42-perc…

Meta's Llama 3.1 can recall 42 percent of the first Harry Potter book
New research could have big implications for copyright lawsuits against generative AI.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis
Ming Wang, Zhaoyang Duan, Dong Xue, Fangzhou Liu, Zhongheng Zhang
https://arxiv.org/abs/2507.08050 https://arxiv.org/pdf/2507.08050 https://arxiv.org/html/2507.08050
arXiv:2507.08050v1 Announce Type: new
Abstract: The labor-intensive nature of medical data annotation presents a significant challenge for respiratory disease diagnosis, resulting in a scarcity of high-quality labeled datasets in resource-constrained settings. Moreover, patient privacy concerns complicate the direct sharing of local medical data across institutions, and existing centralized data-driven approaches, which rely on amounts of available data, often compromise data privacy. This study proposes a federated few-shot learning framework with privacy-preserving mechanisms to address the issues of limited labeled data and privacy protection in diagnosing respiratory diseases. In particular, a meta-stochastic gradient descent algorithm is proposed to mitigate the overfitting problem that arises from insufficient data when employing traditional gradient descent methods for neural network training. Furthermore, to ensure data privacy against gradient leakage, differential privacy noise from a standard Gaussian distribution is integrated into the gradients during the training of private models with local data, thereby preventing the reconstruction of medical images. Given the impracticality of centralizing respiratory disease data dispersed across various medical institutions, a weighted average algorithm is employed to aggregate local diagnostic models from different clients, enhancing the adaptability of a model across diverse scenarios. Experimental results show that the proposed method yields compelling results with the implementation of differential privacy, while effectively diagnosing respiratory diseases using data from different structures, categories, and distributions.
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Meta shareholders overwhelmingly rejected a proposal to explore adding Bitcoin to the company's treasury, with less than 1% voting in favor of the measure (Kyle Baird/DL News)
https://www.dlnews.com/articles/markets/meta-bitcoi…

Meta’s Bitcoin treasury play flops as 99% of shareholders say no
Meta shareholders rejected the Bitcoin plan with less than 1% in favour. The proposal called Bitcoin a hedge against inflation and weak bonds. GameStop and Metaplanet are among firms copying Saylor’s Bitcoin play.

Meta and Anthropic prevailed in copyright suits against them, but the rulings have major caveats and don't address when AI output might infringe copyright (Adi Robertson/The Verge)
https://www.theverge.com/analysis/694657/ai-copyright-rulings-anthr…

Did AI companies win a fight with authors? Technically
Meta and Anthropic both triumphed in a pair of copyright cases, but with major caveats.

A Sharp and Robust Test for Selective Reporting
Stefan Faridani
https://arxiv.org/abs/2506.20035 https://arxiv.org/pdf/2506.20035

A Sharp and Robust Test for Selective Reporting
This paper proposes a test that is consistent against every detectable form of selective reporting and remains interpretable even when the t-scores are not exactly normal. The test statistic is the distance between the smoothed empirical t-curve and the set of all t-curves that would be possible in the absence of any selective reporting. This novel projection test can only be evaded in large meta-samples by selective reporting that also evades all other valid tests of restrictions on the t-curv…