digitado

This position paper argues that in software-defined dry-lab AI research, the one-person laboratory (OPL) is the relevant minimum accountable unit under compressed coordination and should be treated as a first-class unit of evaluation wherever bounded verification and public contestability hold. We develop three propositions. P1 (descriptive): public research-agent systems and laboratory-shaped benchmarks suggest that the minimum efficient research unit is moving downward in parts of AI research. P2 (causal, conditional): the relevant gains are narrower than common “AI […]

Ver mais

We present a self-contained exposition of the Lyons carabiner, focusing on the triple obstruction mechanism arising in Section~ref{sec:triple}. Three independent numerical obstructions—phantom coupling $pi$, holonomy defect $rho$, and braid deficit $beta$—together form the triple $(pi,rho,beta)=(3,4,9)$, which uniquely recovers the MDS code $[6,4,3]_5$ over $mathbb{F}_5$. This identification is not a postulate but a provable consequence of the weight distribution and the complement involution. We then develop the Pontryagin–Heegner bridge: phantom weights are “silent frequencies” in the Pontryagin dual of […]

Ver mais

I saw many discussions about TMLR and other journals lately and how their review processes are considered fairer and less random. My question is, how much does it hurt one’s chance much of getting interviewed/hired as a ML research scientist if they choose to publish at only journals like TMLR, JMLR, or Neurocomputing, instead of conferences? Edit: just to clarify, I mean corporate research scientist positions instead of academic positions. submitted by /u/dontknowwhattoplay [link] [comments]

Ver mais

Deep learning (DL) has become a cornerstone of modern machine learning (ML) praxis. We introduce the R package mlr3torch, which is an extensible DL framework for the mlr3 ecosystem. It is built upon the torch package, and simplifies the definition, training, and evaluation of neural networks for both tabular data and generic tensors (e.g., images) for classification and regression. The package implements predefined architectures, and torch models can easily be converted to mlr3 learners. It also allows users […]

Ver mais

Rabies remains a major public health concern across many African and Asian countries, where accurate diagnosis is critical for effective epidemiological surveillance. The gold standard diagnostic methods rely heavily on fluorescence microscopy, necessitating skilled laboratory personnel for the accurate interpretation of results. Such expertise is often scarce, particularly in regions with low annual sample volumes. This paper presents an automated, AI-driven diagnostic system designed to address these challenges. We developed a robust pipeline utilizing fluorescent image analysis through […]

Ver mais

In this quiz, you’ll test your understanding of How to Conceptualize Python Fundamentals for Greater Mastery. By working through this quiz, you’ll revisit a framework for forming a clear mental picture of Python concepts, including defining ideas in your own words, finding real-world and software analogies, comparing similar concepts, and learning by teaching. With this framework in hand, you’ll be better equipped to approach new Python topics with confidence. [ Improve Your Python With 🐍 Python Tricks 💌 […]

Ver mais

I’m tired of training a lot of models and trying different datasets but still my model is trash and can’t detect clearly it sometimes has mAP50 pf 80% but it is only in numbers not practical, what can i do to have a good model that can be used? I trained using YOLO11n to use it in RPI5 16GB RAM no AI hat, but still can’t get the results i want, i tried searching and learning what could […]

Ver mais