Get Started with Rust: Traits A trait is a basic language concept for defining shared behavior on types. Traits describe an interface that types can implement. Rust traits are a sibling of Scala traits and Haskell type classes, as well as a cousin of C++ and Java interfaces. This article will show you how to use traits in Rust. After reading it, you’ll be able to answer these questions: What is a trait? Why do we use traits […]
Background: Artificial intelligence (AI) has moved from research labs into the everyday work of clinicians and software engineers. In healthcare, AI systems now shape triage, imaging interpretation, risk prediction and documentation workflows, while in computer science and AI development, models are increasingly used to generate code, tests and even other AI systems [1–4,7,10,11,76–82]. Early governance frameworks framed “human oversight” as a high-level ethical injunction but provided limited operational guidance on how humans should interact with data-intensive, adaptive AI […]
The Federal Bureau of Investigation has so far been unable to access data from a Washington Post reporter’s iPhone because it was protected by Apple’s Lockdown Mode when agents seized the device from the reporter’s home, the US government said in a court filing. FBI agents were able to access the reporter’s work laptop by telling her to place her index finger on the MacBook Pro’s fingerprint reader, however. This occurred during the January 14 search at the […]
Author(s): Ayo Akinkugbe Originally published on Towards AI. Defining Scope, Hypotheses, and Contribution Boundaries for Clarity, Testability, and Impact in AI & ML Research Photo by Omar:. Lopez-Rincon on Unsplash Snapshot A thesis statement is the central claim of your dissertation or research. It articulates the core idea your entire AI/ML project is designed to test and validate. It is your intellectual anchor, guiding every methodological decision and framing the contribution you aim to make to the field. […]
I’m a data scientist with experience in demand forecasting (operations / supply chain). I’m starting a more advanced deep learning class and I’m hoping to pivot toward more frontier-oriented work other fields: climate/environment, multimodal ML, and human health (wearables/digital biomarkers, biotech, clinical AI), or more later. Right now I’m missing the domain context: I don’t have a good mental map of what the real problems are in these areas today, what the data and constraints look like, and […]
So I just ended a Bachelor’s in chemical engineering, and for my thesis I created an environment for test control strategies, one of them was reinforcement learning, specifically I used SAC, I ended up using stable baselines since the system model was already using a lot of files, and I lowkey dislike to not have organization on a project. However. The point is that this environment works using a driving cycle dataset (i.e., UDDS) as the velocity for […]
arXiv:2502.01226v3 Announce Type: replace-cross Abstract: Gaussian process (GP) bandits provide a powerful framework for performing blackbox optimization of unknown functions. The characteristics of the unknown function depend heavily on the assumed GP prior. Most work in the literature assume that this prior is known but in practice this seldom holds. Instead, practitioners often rely on maximum likelihood estimation to select the hyperparameters of the prior – which lacks theoretical guarantees. In this work, we propose two algorithms for […]
arXiv:2601.16455v1 Announce Type: new Abstract: Integrated sensing and communication (ISAC) have been widely recognized as a key enabler for future wireless networks, where the Cram’er-Rao bound (CRB) plays a central role in quantifying sensing accuracy.In this paper, we present the first study on CRB minimization in flexible intelligent metasurface (FIM)-enabled ISAC systems.Specifically, we first derive an average CRB expression that explicitly depends on FIM surface shape and demonstrate that array reconfigurability can substantially reduce the CRB, thereby significantly […]
A system that enables blind or visually impaired users to access comics/manga would introduce a new medium of storytelling to this community. However, no such system currently exists. Generative vision-language models (VLMs) have shown promise in describing images and understanding comics, but most research on comic understanding is limited to panel-level analysis. To fully support blind and visually impaired users, greater attention must be paid to page-level understanding and interpretation. In this work, we present a preliminary benchmark […]
arXiv:2601.09883v1 Announce Type: new Abstract: Most existing Large Language Model (LLM)-based Multi-Agent Systems (MAS) rely on predefined workflows, where human engineers enumerate task states in advance and specify routing rules and contextual injections accordingly. Such workflow-driven designs are essentially rule-based decision trees, which suffer from two fundamental limitations: they require substantial manual effort to anticipate and encode possible task states, and they cannot exhaustively cover the state space of complex real-world tasks. To address these issues, we propose […]