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Published August 16, 2022 Image credit: James Thew via Adobe Stock. Gadi Singer is Vice President and Director of Emergent AI Research at Intel Labs leading the development of the third wave of AI capabilities. The Necessity of World Model, … Continuer la lecture →

We developed VL-InterpreT, an interactive tool that provides novel visualizations and analysis for interpreting the attentions and hidden representations in multimodal transformers. Our paper on VL-InterpreT won the Best Demo Award at CVPR 2022.

What to look for in AI Partner and Accelerator Programs for Startups and Collaborating with Intel on AI

Overview and link to Ramtin Davanlou, from Accenture* presentation at the oneAPI DevSummit for AI.

In this blog, we will introduce the concept of multimodal learning along with some of its main use cases, and discuss the progress made at Intel Labs towards creating of robust multimodal reasoning systems.

In this work, we demonstrate Sentence Transformer Fine-tuning (SetFit), a simple and efficient alternative for few-shot text classification. The method is based on fine-tuning a Sentence Transformer with task-specific data and can easily be implemented with the sentence-transformers library.

Research finds that reversible Graph Neural Networks (RevGNNs) significantly outperform existing methods on multiple datasets and improve large models’ memory efficiency for AI applications.

Published October 26, 2021  Image adapted from Elentaris Photo / Shutterstock.com Gadi Singer is Vice President and Director of Emergent AI Research at Intel Labs leading the development of the third wave of AI capabilities. Cognitive AI, hierarchy of knowledge, … Continuer la lecture →

In this post, I present Tango architecture, a simple cascade student-teacher model, and exploit the simplicity of task instances to gain maximum throughput for text classification.  

To pursue this path to better AI, it is essential to understand what “understanding” really means for the human brain.