Key takeawaysUnlike traditional bots, AI-powered agents continuously learn, adapt and refine their strategies in ...

In 2017, a significant change reshaped Artificial Intelligence (AI). A paper titled Attention Is All You Need introduced ...

This valuable study presents a mouse gastruloid model that can be used to generate hematopoietic progenitors as well as leukemic cells. However, in its current form, the manuscript is inadequate ...

This talk uses 3D asset libraries to argue that the pathways by which natural models show up in games, cinema and architecture remain largely invisible and under-theorised. How might a closer ...

Researchers developed a PV-RNN model that learns like children, integrating language and action to uncover mechanisms of compositionality in neural networks.

Artificial intelligence (AI) writing tools have been exploding in popularity. Automated rewriting tools, or text generators, or article spinners, these algorithms claim to generate human-like content ...

While conventional spiking neural networks (SNNs) provide low power consumption, they often lack of sufficient long-term memory capabilities. To address this, we propose the Plastic Recurrent Mushroom ...

A Fortran-based feed-forward neural network library. Whilst this library currently has a focus on 3D convolutional neural networks (CNNs), it can handle most standard hidden layer forms of neural ...

LLMs, founded on a transformer network architecture ... By contrast, the new model is based on a PV-RNN (Predictive coding inspired, Variational Recurrent Neural Network) framework, trained ...

Previously, skin corrosion assessments required animal testing; however, differences in skin architecture and ethical concerns regarding animal models have fostered the advancement of alternative ...

Google’s Titans ditches Transformer and RNN architectures LLMs typically use the RAG system to replicate memory functions Titans AI is said to memorise and forget context during test time ...