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Articles récents
- Curious Case of Chain of Thought: Improving CoT Efficiency via Training-Free Steerable Reasoning
- Intel Labs Works with Hugging Face to Deploy Tools for Enhanced LLM Efficiency
- AI’s Next Frontier: Human Collaboration, Data Strategy, and Scale
- Efficient PDF Summarization with CrewAI and Intel® XPU Optimization
- Rethinking AI Infrastructure: How NetApp and Intel Are Unlocking the Future with AIPod Mini
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Neural networks news
Intel NN News
- Curious Case of Chain of Thought: Improving CoT Efficiency via Training-Free Steerable Reasoning
Researchers from the University of Texas at Austin and Intel Labs investigated chain-of-thought […]
- AI’s Next Frontier: Human Collaboration, Data Strategy, and Scale
Ramtin Davanlou, CTO of the Accenture and Intel Partnership, explores what it really takes for […]
- Intel Labs Works with Hugging Face to Deploy Tools for Enhanced LLM Efficiency
Large Language Models are revolutionizing AI applications; however, slow inference speeds continue […]
- Curious Case of Chain of Thought: Improving CoT Efficiency via Training-Free Steerable Reasoning
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Archives mensuelles : août 2022
Intent Prediction Improves Human-robot Collaboration Task Fluency
Intel Labs will present the paper “Intuitive & Efficient Human-Robot Collaboration via Real-time Approximate Bayesian Inference” at IROS 2022 in Kyoto.
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Distributed Large-Scale Graph Training on Intel CPUs Presented at MLSys 2022
We present our open sourced Sequential Aggregation and Rematerialization (SAR) scheme, which achieves impressive results on common graph learning benchmarks in terms of speed and memory efficiency.
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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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Accelerate Deep Learning with Intel® Optimization for TensorFlow*
Intel and Google* have been collaborating to deliver optimized implementations of some of the most compute-intensive TensorFlow operations.
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Conceptualization as a Basis for Cognition — Human and Machine
To pursue this path to better AI, it is essential to understand what “understanding” really means for the human brain.
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Best Practice for Text-Classification with Distillation Part (4/4)
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.
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