Tootfinder

Heute aufgebaut: Zürcher Wellenschrank 💪
Was ich nicht wusste: das ist ne eigene Gattung? Und über 250 Jahre alt 😲
Zu zweit ne Stunde. Inkl. zwischendurch noch mal zurückbauen weil Beschriftung falsch gelesen (naja, gar nicht gelesen 🙃)
Er sucht ein neues Zuhause, braucht aber etwas Pflege. Wo findet man denn jemand interessierten? Bis Ende August?
Ist nicht mein Schrank, frage tatsächlich für einen Freund
Und: Ist das Nussbaum?

Contemporary AI foundation models increase biological weapons risk
Roger Brent, T. Greg McKelvey Jr
https://arxiv.org/abs/2506.13798 https://

Contemporary AI foundation models increase biological weapons risk
The rapid advancement of artificial intelligence has raised concerns about its potential to facilitate biological weapons development. We argue existing safety assessments of contemporary foundation AI models underestimate this risk, largely due to flawed assumptions and inadequate evaluation methods. First, assessments mistakenly assume biological weapons development requires tacit knowledge, or skills gained through hands-on experience that cannot be easily verbalized. Second, they rely on im…

Das Ende des Thirty Meter Telescopes? – US-Kongress soll kein Geld mehr geben
2024 hat die National Science Foundation erklärt, dass das Geld nur für ein US-Riesenteleskop reicht. Nun soll das Thirty Meter Telescope leer ausgehen.

Beyond Overconfidence: Foundation Models Redefine Calibration in Deep Neural Networks
Achim Hekler, Lukas Kuhn, Florian Buettner
https://arxiv.org/abs/2506.09593

Beyond Overconfidence: Foundation Models Redefine Calibration in Deep Neural Networks
Reliable uncertainty calibration is essential for safely deploying deep neural networks in high-stakes applications. Deep neural networks are known to exhibit systematic overconfidence, especially under distribution shifts. Although foundation models such as ConvNeXt, EVA and BEiT have demonstrated significant improvements in predictive performance, their calibration properties remain underexplored. This paper presents a comprehensive investigation into the calibration behavior of foundation mo…

Now personally, I'm not invested in the law and I reject the logical underpinnings of the whole thing. The US is founded on land that already had people on it, that already had multiple systems of authority, so there can be no claim that it has any legal authority to exist at all.
But it's hard to ignore the inconsistency here. Accepting the logic from the Declaration of Independence and the Constitution, there is no way in which the current state can be legitimate and which Trump has the authority to do anything. The last legal president, again, following the logic that assumes such a thing even possible, was Barak Obama. Since the transfer of power, the country has failed to enforce the law.
If the executive cannot complete their oath, then they are considered vacant under the 25th amendment. If the cabinet fails to invoke article 4, then they too are involved in the insurrection (again, simply following the logic outlined pretty clearly here) as are any who would fail to support the invocation.
Since a full takeover of the federal government by insurrectionists wasn't really planned for, I'm guessing that it would necessarily go to the states, being the only remaining legal authority.

Multimodal Modeling of CRISPR-Cas12 Activity Using Foundation Models and Chromatin Accessibility Data
Azim Dehghani Amirabad, Yanfei Zhang, Artem Moskalev, Sowmya Rajesh, Tommaso Mansi, Shuwei Li, Mangal Prakash, Rui Liao
https://arxiv.org/abs/2506.11182

Multimodal Modeling of CRISPR-Cas12 Activity Using Foundation Models and Chromatin Accessibility Data
Predicting guide RNA (gRNA) activity is critical for effective CRISPR-Cas12 genome editing but remains challenging due to limited data, variation across protospacer adjacent motifs (PAMs-short sequence requirements for Cas binding), and reliance on large-scale training. We investigate whether pre-trained biological foundation model originally trained on transcriptomic data can improve gRNA activity estimation even without domain-specific pre-training. Using embeddings from existing RNA foundati…

Distillation of atomistic foundation models across architectures and chemical domains
John L. A. Gardner, Daniel F. Thomas du Toit, Chiheb Ben Mahmoud, Zo\'e Faure Beaulieu, Veronika Juraskova, Laura-Bianca Pa\c{s}ca, Louise A. M. Rosset, Fernanda Duarte, Fausto Martelli, Chris J. Pickard, Volker L. Deringer
https://arxiv.or…

Distillation of atomistic foundation models across architectures and chemical domains
Machine-learned interatomic potentials have transformed computational research in the physical sciences. Recent atomistic `foundation' models have changed the field yet again: trained on many different chemical elements and domains, these potentials are widely applicable, but comparably slow and resource-intensive to run. Here we show how distillation via synthetic data can be used to cheaply transfer knowledge from atomistic foundation models to a range of different architectures, unlocking mu…

On quadratic persistence and Pythagoras numbers of totally real projective varieties
Jong In Han, Jaewoo Jung, Euisung Park
https://arxiv.org/abs/2506.13247

On quadratic persistence and Pythagoras numbers of totally real projective varieties
In this paper, we study the relationship between quadratic persistence and the Pythagoras number of totally real projective varieties. Building upon the foundational work of Blekherman et al. in arXiv:1902.02754, we extend their characterizations of arithmetically Cohen-Macaulay varieties with next-to-maximal quadratic persistence to arbitrary case. Our main result classifies totally real non-aCM varieties of codimension $c$ and degree $d$ that exhibit next-to-maximal quadratic persistence in t…

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things
Kai Li, Conggai Li, Xin Yuan, Shenghong Li, Sai Zou, Syed Sohail Ahmed, Wei Ni, Dusit Niyato, Abbas Jamalipour, Falko Dressler, Ozgur B. Akan
https://arxiv.org/abs/2505.23792

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things
This paper focuses on Zero-Trust Foundation Models (ZTFMs), a novel paradigm that embeds zero-trust security principles into the lifecycle of foundation models (FMs) for Internet of Things (IoT) systems. By integrating core tenets, such as continuous verification, least privilege access (LPA), data confidentiality, and behavioral analytics into the design, training, and deployment of FMs, ZTFMs can enable secure, privacy-preserving AI across distributed, heterogeneous, and potentially adversari…

Übrigens, wer meine (soweit Neuerblühtes vorhanden täglichen) #blühklex Fotos ausm #klexenhaus mag: dieses Jahr versuche ich sie konsequent in einem eigenen nur dafür gedachten Instagram Account zu sammeln, wer mag, findet den unter https://www.instagram.com/bluehklex/profilecard/?igsh=MWg0d3QyNmFtbjBxdQ==.
(ja, Instagram böse, ich weiß, klei mi büdde anne fööt)