OpenAI chief Sam Altman thinks otherwise. “There is no wall,” he said regarding the conversation around LLMs hitting a wall.

Abstract: Recent research has revealed that traditional machine learning methods, such as semi-supervised label propagation and K-nearest neighbors, outperform Transformer-based models in artifact ...

This valuable study investigates how the neural representation of individual finger movements changes during the early period of sequence learning. By combining a new method for extracting features ...

RIT Assistant Professor Alexander Ororbia published a paper on smarter and greener artificial intelligence in Science ...

This method improves the accuracy and reliability of hyperspectral ... The first model, the Attenuation Correction and Unmixing Network (ACU-Net) is a supervised deep-learning architecture designed to ...

The balance between securing transactions and enabling growth is key to long-term success in the evolving world of payments risk management.

Binjumah, W. (2024) The Role of Machine Learning and Deep Learning Approaches to Improve Optical Communication Systems.

The autonomy revolution is progressing. Helm.ai's unsupervised learning and generative AI approach offers scalability, ...

We also integrate uncertainty estimation from the evidential learning into cross-supervised training ... and ACDC datasets demonstrate that ETC-Net surpasses other state-of-the-art methods for ...

Household cleaning brand Method was rated as a sustainable brand by 77% of Which? members who had recently bought from it, in our survey asking customers what they make of companies' sustainability.

MIT researchers have created a versatile training method that combines diverse data to help robots learn new skills, inspired by large language models. The method aligns data from diverse domains, ...