Archives de catégorie : Non classé

Beyond Input-Output Reasoning: Four Key Properties of Cognitive AI

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

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VL-InterpreT: An Interactive Visualization Tool for Interpreting Vision-Language Transformers

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.

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A Guide to AI Partner and Accelerator Programs for Startups

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

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Enabling AI Developers on Their Journey to Scale with Intel AI

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

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Multimodality: A New Frontier in Cognitive 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.

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Intel Labs Enables AI Innovation with Hardware-Aware Automated Machine-Learning Tools

Intel Labs’ hardware-aware AI-based automation tools (AutoX) enable rapid adoption of AI models for different deployments to address productivity challenges. 

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LM!=KM: Five Reasons Why Language Models Fail to Support Knowledge Model Requirements of Next-Gen AI

This post will discuss the five capabilities that make up an advanced KM and how these areas cannot be easily addressed by LMs in their present form. These capabilities are Scalability, Fidelity, Adaptability, Richness and Explainability.

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Sentence Transformer Fine-Tuning (SetFit)

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.

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Intel® Labs’ Graph Neural Networks Research Featured as Groundbreaking Work in AI

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

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No One Rung to Rule Them All: Addressing Scale and Expediency in Knowledge-Based AI

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

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