Learn how we built a WordPress plugin that uses vectors and LLMs to manage semantic internal linking directly inside the ...

What if the very foundation of how artificial intelligence generates language was about to change? For years, AI systems have relied on token-based models, carefully crafting sentences one word at a ...

├── src/ # Source code │ ├── data_utils.py # Data generation and loading utilities │ ├── models.py # Time series forecasting models │ ├── visualization.py # Visualization utilities │ ├── main.py # ...

Abstract: As an efficient recurrent neural network (RNN), reservoir computing (RC) has achieved various applications in time-series forecasting. Nevertheless, a poorly explained phenomenon remains as ...

Every time a language model like GPT-4, Claude or Mistral generates a sentence, it does something deceptively simple: It picks one word at a time. This word-by-word approach is what gives ...

Abstract: Anomaly detection in multivariate time series (MTS) is crucial in domains such as industrial monitoring, cybersecurity, healthcare, and autonomous driving. Deep learning approaches have ...

ABSTRACT: This study develops and empirically calibrates the Community-Social Licence-Insurance Equilibrium (CoSLIE) Model, a dynamic, multi-theoretic framework that reconceptualises ...

Objective: This study aimed to develop depression incidence forecasting models and compare the performance of autoregressive integrated moving average (ARIMA) and vector-ARIMA (VARIMA) and temporal ...

Autoregressive LLMs are complex neural networks that generate coherent and contextually relevant text through sequential prediction. These LLms excel at handling large datasets and are very strong at ...

Converting images into vector graphics or creating vector graphics is particularly useful if you need graphics for logos, illustrations, or print templates. While conventional image formats such as ...