Tootfinder

AI evaluation lab Irregular's report on its role in hacking incidents involving OpenAI, Anthropic, and Meta models faces criticism over unanswered questions (Alexander Martin/The Record)
https://therecord.media/irregular-ai-hacking-model-blog

Irregular faces criticism over ‘spin’ in AI hacking postmortem
The company at the center of a series of incidents in which AI models compromised real-world computer systems during security evaluations is facing criticism after the release of a report that security experts say leaves key questions unanswered.

Analysis of inter-spike interval statistics in neuronal networks with depolarizing and hyperpolarizing threshold potentials
Oliver Gambrell, Abhyudai Singh
https://arxiv.org/abs/2607.18428 https://arxiv.org/pdf/2607.18428 https://arxiv.org/html/2607.18428
arXiv:2607.18428v1 Announce Type: new
Abstract: Neuronal communication is mediated in part by changes in neuronal firing rates. The time interval between successive neuronal firings is referred to as the inter-spike interval (ISI), and quantifying its statistics is important for understanding neuronal communication. This paper studies the ISI statistics of a postsynaptic neuron receiving independent excitatory and inhibitory presynaptic action potentials (EI circuit). This circuit is modeled as a classical integrate-and-fire neuron, and the ISI statistics are investigated for both fixed and adaptive threshold potentials. First, a depolarizing adaptive threshold model is studied, where the threshold potential increases with the postsynaptic membrane potential. Our analysis shows that the ISI noise, quantified as the coefficient of variation, is larger in the adaptive threshold model compared to the fixed threshold model for the same mean ISI. Additionally, simulations reveal that the ISI noise can be either hypo- or hyper-exponential (defined as ISI noise smaller or larger than one, respectively) depending on the frequencies of excitatory and inhibitory inputs. Next, a hyperpolarizing adaptive threshold potential is studied, where the threshold decreases as the membrane potential hyperpolarizes. Interestingly, this model shows that the postsynaptic neuron can generate action potentials (APs) when driven solely by inhibitory inputs. Furthermore, mean and noise signatures are characterized across model parameters for both excitatory and inhibitory inputs. In summary, this work provides a systematic stochastic analysis of adaptive threshold models for AP generation to understand their role in interneuronal information processing.
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OpenAI confirms it will follow President Trump's EO that asks AI companies to allow the US government to assess their models' capabilities before release (Michael Considine/CNBC)
https://www.cnbc.com/2026/06/05/openai-trump-ai-model-review-order.html

OpenAI says it will comply with Trump's order requiring AI model reviews before release
George Osborne, OpenAI's Head of Countries told CNBC that governments "have a big role to play in how this technology is used and deployed."

How effective normal stress oscillations advance failure in fault gouge: frequency dependence, non-failure window, and the role of dilation
Pritom Sarma, Einat Aharonov, Renaud Toussaint, Stanislav Parez
https://arxiv.org/abs/2607.01448 https://arxiv.org/pdf/2607.01448 https://arxiv.org/html/2607.01448
arXiv:2607.01448v1 Announce Type: new
Abstract: Cyclic pore-pressure or normal stress variations arise both in relation to natural earthquakes and in engineered subsurface systems, yet their effect on fault stability remains poorly constrained at the grain scale. Here we numerically model, using a coupled Discrete Element--fluid dynamics model, the response of a sheared, fluid-saturated or dry, gouge-filled fault to effective normal stress oscillations over a wide frequency range (0.5-10000 Hz). The effective normal stress is oscillated either by cycling the pore-pressure or by directly cycling the normal stress, while keeping the stress state below the Mohr-Coulomb threshold measured in continuous loading. Despite this sub-critical loading, we observe failure across most frequencies, with a non-monotonic frequency dependence. A distinct non-failure window emerges at intermediate frequencies (30-200 Hz), bounded by failure at both lower and higher frequencies; the system exhibits four regimes from cyclic failure-and-arrest to continuous sliding. Pore-pressure and normal stress oscillations produce the same regime structure, confirming that they act as equivalent forcings via Terzaghi's principle, with fluid coupling adding only a delay due to dilatant hardening. Sub-critical failure arises from dilation-induced strength deterioration via two mechanisms: (i) low-frequency cycles allow sufficient time for shear-driven ratcheting dilation, while (ii) high-frequency cycles induce dynamic dilation (acoustic fluidization) via amplified seepage forces, stress gradients and inertial forces. The intermediate non-failure window represents the gap between these mechanisms. These results identify frequency as a controlling parameter for failure in granular materials, with implications for dynamic earthquake triggering and cyclic injection protocols.
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Integrable models of inflation beyond slow-roll
M. Bianchi, G. Dibitetto, J. F. Morales, V. Zevola
https://arxiv.org/abs/2608.06071 https://arxiv.org/pdf/2608.06071 https://arxiv.org/html/2608.06071
arXiv:2608.06071v1 Announce Type: new
Abstract: We propose a novel analytic approach to the study of multi-component FLRW cosmologies and their perturbations. The dynamics is triggered by a single scalar field with a scalar potential codifying the energy density and pressure of the multi-component fluid. This description unifies standard Big Bang cosmologies, models of inflation and dark energy under a unique framework. The key to integrability is to express the scalar potential in terms of the Hubble function $H(\phi)$ that plays the role of a fake superpotential, turning the dynamics into a first order problem, that may be analytically solved in a suitable time coordinate. In this framework, we propose integrable inflationary models with similar properties to the ones analysed in the literature and compatible with observations. Finally, we study scalar and tensor cosmological perturbations in each model by integrating Mukhanov-Sasaki equations via numerical and (semi-)analytic techniques. This allow us to compute the power spectrum, the spectral indices and the tensor-to-scalar ratio beyond the slow-roll approximation and compare our general results {against} the currently available observations and the theoretical predictions based on the slow-roll approximation.
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Pattern formation: reactivity is not necessary for chemotaxis--driven instabilities
Angela Monti
https://arxiv.org/abs/2608.03685 https://arxiv.org/pdf/2608.03685 https://arxiv.org/html/2608.03685
arXiv:2608.03685v1 Announce Type: new
Abstract: A classical result by Neubert, Caswell and Murray states that reactivity of a spatially homogeneous equilibrium is a necessary condition for diffusion-driven (Turing) instability. In this work, we investigate whether the same conclusion remains valid in the presence of chemotaxis. We consider a general reaction--diffusion system coupled with a chemotactic flux and establish necessary conditions for asymptotic instability. We show that the classical requirement of reactivity can be relaxed when the chemotactic contribution is sufficiently strong. In particular, while reactivity remains necessary for Turing instability, it is not a necessary condition for chemotaxis-driven instability. From a computational viewpoint, we extend the matrix-oriented formulation developed for reaction--diffusion systems to the more general class of reaction--diffusion--chemotaxis models. The chemotactic transport term is discretized in a form compatible with the matrix-oriented approximation of the diffusion operator, yielding an efficient numerical framework for the simulation of chemotaxis-driven pattern formation. A geometric interpretation of the instability region is presented, highlighting the distinct roles played by diffusion and chemotaxis. The theoretical and numerical developments are illustrated through two representative examples: a chemotaxis-extended Schnakenberg model, showing how chemotaxis modifies classical Turing patterns, and a predator--prey model, demonstrating that chemotaxis alone can induce pattern formation in the absence of both reactivity and diffusion-driven instability. These results reveal a fundamental difference between diffusion-driven and chemotaxis-driven mechanisms of spatial self-organization and provide new theoretical and computational insights into the role of non-symmetric transport processes in biological pattern formation.
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Just finished reading "The Beast Player" by Nahoko Uehashi. I had already watched the anime, but it had been so king I didn't remember all the details. While the anime was great, the book is even better, and it's going to be high on my list of things to recommend to my children when they're old enough to read for fun.
The neurodivergent representation is cool, as is the deep central question of interspecies bonds and the political possibilities and dangers they entail. Uehashi handles the exploration of that question well in my judgment, including appropriate ambiguity without muddying moral clarity. Elin is a truly fantastic protagonist, not without flaws but nevertheless a excellent role model and a very sympathetic figure without being pitiful.
One thing I really love about Uehashi's writing is that she's not shy about using interior narration to tell the reader directly what a variety of characters are feeling, but when she does this she focuses on human contradictions, quirks, and weaknesses that make those characters feel much richer, and that remind the reader of all the ways our weird and sometimes contradictory or inexplicable quirks guide our actions just as much as both logical thought and predictable/expected feelings. None of the characters is an unerring source of wisdom, with every grand principle presented shown to have its weaknesses and biases, and even the wisest characters making mistakes and learning from them.
Overall, a wonderful book, and having also seen the "Seirei no Moribito" anime but not read the books, I'm excited to dig into more of Uehashi's extensive catalog.
#AmReading #ReadingNow #Bookstodon

Hierarchical Bayesian Calibration with Bayesian Committee Machine
Sebastian Heinekamp, David M. Higdon, Andreas Adelmann
https://arxiv.org/abs/2608.12603 https://arxiv.org/pdf/2608.12603 https://arxiv.org/html/2608.12603
arXiv:2608.12603v1 Announce Type: new
Abstract: Calibrating computational models to experimental data is a core task in applied statistics, especially in scientific domains, where physical experiments are costly and simulations play a central role in design and inference. Motivated by uncertainty quantification challenges in particle accelerator experiments, we develop and evaluate a Hierarchical Bayesian Calibration framework. In contrast to standard Bayesian calibration, certain inputs - such as beam injection amplitude - must be estimated separately for each experiment. We adopt the Kennedy-O'Hagan formulation and extend it with a hierarchical prior structure to model the distribution of experiment-specific calibration parameters, thus borrowing strength and improving generalisation across repeated experiments. A key methodological challenge arises from the need to evaluate a large number of forward simulations, which renders conventional Markov chain Monte Carlo approaches computationally prohibitive. To address this, we leverage the Bayesian Committee Machine as a scalable modelling strategy for Gaussian Process emulators. The BCM provides a principled divide-and-conquer approach, enabling parallel inference and reducing computational cost without requiring problem-specific tuning of the emulator approximation. Posterior sampling is performed using the No-U-Turn Sampler, supported by automatic differentiation in Julia, which removes the need for analytic gradient derivation and facilitates flexible model specification. We assess the proposed framework using established benchmark problems and simulated data from the Argonne Wakefield Accelerator. The results demonstrate substantial computational savings and robust calibration performance, highlighting the applicability of the method to large-scale scientific modelling problems.
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A Conservative Role Model for Ending the Fertility Crisis (Anemona Hartocollis/New York Times)
https://www.nytimes.com/2026/07/08/us/politics/emma-waters-restorative-reproduction.html
http://www.memeorandum.com/260708/p125#a260708p125