Hi, r/MachineLearning: has much research been done in large-scale training scenarios where undesirable data has been replaced before training, such as any instances of violence, lying, or deception in the dataset? Most controllability work, like RLHF or constitutional AI, seems to be done post-training. What I’m considering is intentionally training models on more carefully chosen data, and not letting it train on undesirable data at all. This is a literal application of Mo Gawdat’s proposal to “raise AI […]

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These glasses are a step back from an ambitious plan that once called for Apple to launch a variety of mixed and augmented reality devices.

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arXiv:2602.00905v1 Announce Type: new Abstract: Although the stabilization of underactuated systems remains a challenging problem, the total energy shaping approach provides a general framework for addressing this objective. However, the practical implementation of this method is hindered by the need to analytically solve a set of partial differential equations (PDEs), which constitutes a major obstacle. In this paper, a rotary inverted pendulum system is considered, and an interconnection and damping assignment passivity-based control (IDA-PBC) scheme is developed by […]

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Self-driving car companies have long boasted about eliminating road injuries and fatalities caused by human error. However, the capabilities of Level 3 autonomy are still unproven at scale. It will take time and coordinated effort to change things.

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Ayahuasca is a visionary “brain cocktail” brewed from two secret jungle plants. Part medicine, part spiritual telephone, it connects humans to nature’s hidden wisdom. This ancient partnership suggests we are students of a grand, green symbiosis—perhaps even guided by chatty extraterrestrial spores whispering cosmic secrets.

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Explainable Boosting Machines (EBMs) provide transparent predictions through additive shape functions, enabling direct inspection of feature contributions. However, EBMs can learn non-physical relationships that reduce their reliability in natural hazard applications. This study presents a domain-informed framework to improve the physical consistency of EBMs for lateral spreading prediction. Our approach modifies learned shape functions based on domain knowledge. These modifications correct non-physical behavior while maintaining data-driven patterns. We apply the method to the 2011 Christchurch earthquake dataset and […]

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arXiv:2602.24083v1 Announce Type: cross Abstract: Cox processes model overdispersed point process data via a latent stochastic intensity, but both nonparametric estimation of the intensity model and posterior inference over intensity paths are typically intractable, relying on expensive MCMC methods. We introduce Neural Diffusion Intensity Models, a variational framework for Cox processes driven by neural SDEs. Our key theoretical result, based on enlargement of filtrations, shows that conditioning on point process observations preserves the diffusion structure of the latent […]

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arXiv:2604.07360v1 Announce Type: new Abstract: Edge AI is often framed as model compression and deployment under tight constraints. We argue a stronger operational thesis: Edge AI in realistic deployments is necessarily adaptive. In long-horizon operation, a fixed (non-adaptive) configuration faces a fundamental failure mode: as data and operating conditions evolve and change in time, it must either (i) violate time-varying budgets (latency/energy/thermal/connectivity/privacy) or (ii) lose predictive reliability (accuracy and, critically, calibration), with risk concentrating in transient regimes and […]

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arXiv:2602.09213v1 Announce Type: new Abstract: Non-contact current monitoring has emerged as a prominent research focus owing to its non-intrusive characteristics and low maintenance requirements. However, while they offer high sensitivity, contactless sensors necessitate sophisticated design methodologies and thorough experimental validation. In this study, a Giant Magneto-Resistance (GMR) sensor is employed to monitor the instantaneous currents of a three-phase 400-volt overhead line, and its performance is evaluated against that of a conventional contact-based Hall effect sensor. A mathematical framework […]

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