Advanced deep learning architectures, particularly recurrent neural networks (RNNs), have been widely applied in audio, bioacoustic, and biomedical signal analy...
Federated Learning is a popular approach for distributed learning due to its security and computational benefits. With the advent of powerful devices in the net...
We present Conformer-based decoders for the LibriBrain 2025 PNPL competition, targeting two foundational MEG tasks: Speech Detection and Phoneme Classification....
Serverless Large Language Models (LLMs) have emerged as a cost-effective solution for deploying AI services by enabling a 'pay-as-you-go' pricing model through ...
OpenAI and NORAD are bringing new magic to “NORAD Tracks Santa” with three ChatGPT holiday tools that let families create festive elves, toy coloring pages, and...
Accenture and OpenAI are collaborating to help enterprises bring agentic AI capabilities into the core of their business and unlock new levels of growth....
OpenAI takes an ownership stake in Thrive Holdings to accelerate enterprise AI adoption, embedding frontier research and engineering directly into accounting an...
This paper introduces a new family of multi-parent recombination operators for Genetic Algorithms (GAs), based on normalized Pascal (binomial) coefficients. Unl...
In this paper we investigate a neural network model in which weights between computational nodes are modified according to a local learning rule. To determine w...
The Machine Consciousness Hypothesis states that consciousness is a substrate-free functional property of computational systems capable of second-order percepti...
Inference over large-scale foundation models within heterogeneous edge environments necessitates a fundamentally reconfigurable orchestration substrate. Static ...
Opening the black box of ML models, step by step, directly in Excel The post The Machine Learning and Deep Learning “Advent Calendar” Series: The Blueprint appe...
