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- Intel® AI for Enterprise Inference as a Deployable Architecture on IBM Cloud
Intel® AI for Enterprise Inference as a Deployable Architecture on IBM CloudAuthored by: Pai […]
- Intel® Xeon® 6 Processors: The Smart Total Cost of Ownership Choice
The latest Intel® Xeon® 6 processors deliver performance advantages across key enterprise […]
- Next-Gen AI Inference: Intel® Xeon® Processors Power Vision, NLP, and Recommender Workloads
Intel® Xeon® processors can deliver a CPU-first platform built for modern AI workloads without […]
- Intel® AI for Enterprise Inference as a Deployable Architecture on IBM Cloud
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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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