arXiv:2601.14476v1 Announce Type: new Abstract: Probabilistic computing using probabilistic bits (p-bits) presents an efficient alternative to traditional CMOS logic for complex problem-solving, including simulated annealing and machine learning. Realizing p-bits with emerging devices such as magnetic tunnel junctions (MTJs) introduces device variability, which was expected to negatively impact computational performance. However, this study reveals an unexpected finding: device variability can not only degrade but also enhance algorithm performance, particularly by leveraging timing variability. This paper introduces a GPU-accelerated, […]

Ver mais

Catastrophic forgetting is not an engineering failure. It is a mathematical consequence of storing knowledge as global parameter superposition. Existing methods, such as regularization, replay, and frozen subnetworks, add external mechanisms to a shared-parameter substrate. None derives retention from the learning dynamics themselves. This paper introduces the Informational Buildup Framework (IBF), an alternative substrate for continual learning, based on the premise that information is the achievement of structural alignment rather than stored content. In IBF, two equations govern […]

Ver mais

arXiv:2603.28781v1 Announce Type: new Abstract: GPU nodes are central to modern HPC and AI workloads, yet many failures do not manifest as immediate hard faults. While some instabilities emerge gradually as weak thermal or efficiency drift, a significant class occurs abruptly with little or no numeric precursor. In these detachment-class failures, GPUs become unavailable at the driver or interconnect level and the dominant observable signal is structural, including disappearance of device metrics and degradation of monitoring payload integrity. […]

Ver mais

Half the questions I got asked when I interviewed in 2022 are irrelevant now. Here are the ones I’d ask today. The BI engineering interview hasn’t caught up with the job. I’ve been on both sides of the table. I’ve answered questions about star schemas, slowly changing dimensions, and the difference between OLAP and OLTP. I’ve also asked those questions. And here’s what I’ve realized: most BI interview question lists were written for a world where the job […]

Ver mais

Artificial intelligence is no longer limited to competition or innovation, it is now about being ready for what is about to come. AI systems are growing more powerful and widespread each day, the rewards are high but so are the risks. Changes like job disruption and high energy demand are more of a systemic shift and not just a tech upgrade anymore.  The current economic and infrastructure systems may not be built for what’s coming next. The concern […]

Ver mais

arXiv:2603.24797v1 Announce Type: new Abstract: To fully capture the meaning of a sentence, semantic representations should encode aspect, which describes the internal temporal structure of events. In graph-based meaning representation frameworks such as Uniform Meaning Representations (UMR), aspect lets one know how events unfold over time, including distinctions such as states, activities, and completed events. Despite its importance, aspect remains sparsely annotated across semantic meaning representation frameworks. This has, in turn, hindered not only current manual annotation, but […]

Ver mais

arXiv:2603.19108v1 Announce Type: cross Abstract: This report examines numerical aspects of constructing Karhunen-Lo`{e}ve expansions (KLEs) for second-order stochastic processes. The KLE relies on the spectral decomposition of the covariance operator via the Fredholm integral equation of the second kind, which is then discretized on a computational grid, leading to an eigendecomposition task. We derive the algebraic equivalence between this Fredholm-based eigensolution and the singular value decomposition of the weight-scaled sample matrix, yielding consistent solutions for both model-based and […]

Ver mais

The Protocol The magnetic rack hissed. Kael let go of the plasma torch. Click. The green light on the wall turned solid. The tool was secured. His hands were empty. For the first time in ten years, Kael didn’t check his pockets for inventory. He didn’t pat his hip for a weapon. He just stood there, the weight gone, his hands trembling slightly from the absence of a burden. Vvvvt. The bone-conduction implant behind his ear vibrated. “PROTOCOL […]

Ver mais

We study the algorithmic task of testably learning general Massart halfspaces under the Gaussian distribution. In the testable learning setting, the aim is the design of a tester-learner pair satisfying the following properties: (1) if the tester accepts, the learner outputs a hypothesis and a certificate that it achieves near-optimal error, and (2) it is highly unlikely that the tester rejects if the data satisfies the underlying assumptions. Our main result is the first testable learning algorithm for […]

Ver mais