Archives de catégorie : Non classé

The Example of Deploying YOLOv7 Pre-trained Model Based on the OpenVINO™ 2022.1 C++ API

How to deploy the YOLOv7 official pre-trained model based on the OpenVINO™ 2022.1 tool suite.

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Solving Hard Optimization Problems with Energy Efficient Neuromorphic Technology

At Intel, we are exploring stochastic spiking neural networks (SSNN) on our second-generation Loihi chip, which transmits data through patterns of pulses (or spikes) between neurons.

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Intel and Intel Labs Develop New AI Methods to Restore Trust in Media

Intel Labs’ trusted media research team investigates new approaches to help determine the authenticity of media content.

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The Power of Intel® Hardware for Billion-Scale Similarity Search

In this blog, we describe a solution that reaches new heights along all of these dimensions by leveraging the computational capabilities of Intel® Xeon® and the access characteristics of Optane™ Persistent Memory

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Optimizing Graph Neural Network Training Performance on Intel® Xeon®

In this article, we focus on the performance of GNN training for node classification on modern, general-purpose compute engines – the Intel® Xeon® family of CPUs.

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Intel Labs’ Validate on Sim, Detect on Real (VSDR) Narrows Sim2Real Gap in Robot Learning

Intel Labs, in collaboration with the Technion – Israel Institute of Technology, developed a “Validate on Sim, Detect on Real” (VSDR) approach for learning robotic skills. 

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Celebrating Hispanic Heritage: Javier Turek’s Story from Intel Labs

During Hispanic Heritage Month, we proudly celebrate the culture and contributions of the Latinx community.

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Kid Space: Re-imagining the Potential of Technology-Mediated Learning

Kid Space incorporates audio and vision hardware components and AI technologies to create an adaptive and engaging learning environment.

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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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