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Solution Brief
Intel® AI Builders - Solution Brief
Knowledge Lens assists manufacturers and industries with Artificial Intelligence (AI), Industrial IoT, Big Data, and other technologies that help transform enterprises into Industry 4.0-grade operations. This brief highlights how Knowledge Lens worked with the AI Builders team to utilize OpenVINO optimization for multiple use cases we have incredible improvement in performance while not compromising accuracy.
Categories: 
Application Type - Machine Learning | Compute - Intel® Xeon® Scalable processor, Intel® Core™ processor | Deployment Channel - CSP - Amazon Web Services, CSP - Microsoft Azure, On-premise (Private Cloud, Other) | Industry - Transportation and Warehousing | Operating System - Linux | Solution Geographic Availability - Worldwide | Solution Type - AI Platform as a Service (AI PaaS) | Topology - Yolo, ResNet50 | Use Case - Video Surveillance and Analytics

Knowledge Lens assists manufacturers and industries with Artificial Intelligence (AI), Industrial IoT, Big Data, and other technologies that help transform enterprises into Industry 4.0-grade operations. This brief highlights how Knowledge Lens worked with the AI Builders team to utilize OpenVINO optimization for multiple use cases we have incredible improvement in performance while not compromising accuracy.

White Paper
Intel® AI Builders - White Paper
MaxQ AI uses the phrase ‘Data Industrialization’ to represent the end-to-end life cycle for data mining and treatment in support of software-based medical devices. This white paper explores the methods MaxQ uses to help ensure the utmost security during Data Industrialization within the use of their products.
Categories: 
Application Type - Deep Learning | Compute - Intel® Xeon® Scalable processor, Intel® Core™ processor | Industry - Healthcare | Intel® Distribution of OpenVINO™ Toolkit powered by oneAPI - Intel® Distribution of OpenVINO™ Toolkit powered by oneAPI | Model Training - Models can be trained - requires labeled data | Operating System - Windows | Solution Geographic Availability - Other - Europe and Africa, Other - North and South America | Topology - Unet, Proprietary, VGG-19 | Use Case - Medical imaging, analysis and diagnostics

MaxQ AI uses the phrase ‘Data Industrialization’ to represent the end-to-end life cycle for data mining and treatment in support of software-based medical devices. This white paper explores the methods MaxQ uses to help ensure the utmost security during Data Industrialization within the use of their products.

Solution Brief
Intel® AI Builders - Solution Brief
This Solution Brief highlights how Intel optimizations of Winning Health’s Bone Age Assessment (BAA) model helped greatly reduce image analysis time enabling large scalability of SaaS solution for hospitals and clinicians on cloud platforms.
Categories: 
Application Type - Deep Learning | Compute - Intel® Xeon® Scalable processor | Deployment Channel - CSP - Other, On-premise (Private Cloud, Other) | Industry - Healthcare | Intel® AI Analytics Toolkit powered by oneAPI - Intel® Optimization for PyTorch* | Intel® Distribution of OpenVINO™ Toolkit powered by oneAPI - Intel® Distribution of OpenVINO™ Toolkit powered by oneAPI | Model Training - Models cant be re-trained - Inference only | Operating System - Linux | Solution Geographic Availability - China (PRC) | Solution Type - AI Software/SaaS | Topology - Other, Proprietary | Use Case - Medical imaging, analysis and diagnostics

This Solution Brief highlights how Intel optimizations of Winning Health’s Bone Age Assessment (BAA) model helped greatly reduce image analysis time enabling large scalability of SaaS solution for hospitals and clinicians on cloud platforms.

Solution Brief
Intel® AI Builders - Solution Brief
This solution snapshot illustrates how Yellow Messenger virtual assistant needed to inference an intent classification model in under 100 ms to provide customers with optimal experiences. Optimizing Yellow Messenger’s intent classification model on 3rd Gen Intel® Xeon® Scalable processors reduced inferencing time to less than 100 ms. Optimization cuts latency and speeds throughput, delivering real-time, intelligent responses for optimal customer experiences.
Categories: 
Application Type - Machine Learning | Compute - Intel® Xeon® Scalable processor | Deployment Channel - CSP - Amazon Web Services, CSP - Google Cloud, CSP - Microsoft Azure | Industry - Cross-Industry, Finance and Insurance, Healthcare | Operating System - Linux | Solution Geographic Availability - India, Other - Asia Pacific | Solution Type - AI Platform as a Service (AI PaaS) | Topology - Other | Use Case - Conversational Bots and Voice Agents

This solution snapshot illustrates how Yellow Messenger virtual assistant needed to inference an intent classification model in under 100 ms to provide customers with optimal experiences. Optimizing Yellow Messenger’s intent classification model on 3rd Gen Intel® Xeon® Scalable processors reduced inferencing time to less than 100 ms. Optimization cuts latency and speeds throughput, delivering real-time, intelligent responses for optimal customer experiences.

Solution Brief
Intel® AI Builders - Solution Brief
This solution snapshot illustrates how accelerating tuning on 2nd Gen Intel® Xeon® Scalable processors allowed Nordigen needed to reduce the hyperparameter tuning time for their XGBoost model (part of the Scoring Insights product suite) in order to streamline their model search efforts. Nordigen to expand the parameter space and even run faster on 3rd Gen Intel Xeon Scalable processors.
Categories: 
Application Type - Machine Learning | Compute - Intel® Xeon® Scalable processor | Deployment Channel - CSP - Amazon Web Services, On-premise (Private Cloud, Other) | Industry - Finance and Insurance | Model Training - Models can be trained - data input only required | Operating System - Linux | Solution Geographic Availability - United Kingdom, United States, Other - Asia Pacific, Other - Europe and Africa, Brazil, Germany, India, Mexico | Solution Type - AI Software/SaaS | Use Case - Data Analytics

This solution snapshot illustrates how accelerating tuning on 2nd Gen Intel® Xeon® Scalable processors allowed Nordigen needed to reduce the hyperparameter tuning time for their XGBoost model (part of the Scoring Insights product suite) in order to streamline their model search efforts. Nordigen to expand the parameter space and even run faster on 3rd Gen Intel Xeon Scalable processors.

White Paper
Intel® AI Builders - White Paper
This white paper discusses ACCIPIO, a software device designed to be installed within healthcare facilities’ radiology networks to identify and prioritize NCCT scans based on algorithmically identified findings of acute intracranial hemorrhage (aICH).
Categories: 
Application Type - Deep Learning | Compute - Intel® Xeon® Scalable processor, Intel® Core™ processor | Industry - Healthcare | Intel® Distribution of OpenVINO™ Toolkit powered by oneAPI - Intel® Distribution of OpenVINO™ Toolkit powered by oneAPI | Model Training - Models can be trained - requires labeled data | Operating System - Windows | Solution Geographic Availability - Other - Europe and Africa, Other - North and South America | Topology - Unet, Proprietary, VGG-19 | Use Case - Medical imaging, analysis and diagnostics

This white paper discusses ACCIPIO, a software device designed to be installed within healthcare facilities’ radiology networks to identify and prioritize NCCT scans based on algorithmically identified findings of acute intracranial hemorrhage (aICH).

Solution Brief
Intel® AI Builders - Solution Brief
This solution brief highlights how NimbleBox’s platform utilizes Intel® Distribution of OpenVINO™ toolkit and Intel optimizations for machine learning frameworks and languages boost inferencing on popular AI models running on Intel CPUs.
Categories: 
Application Type - Deep Learning | Compute - Intel® Xeon® Scalable processor | Deployment Channel - CSP - Amazon Web Services | Industry - Education, Other | Intel® AI Analytics Toolkit powered by oneAPI - Intel® Distribution for Python* , Intel® Optimization for TensorFlow* | Intel® Distribution of OpenVINO™ Toolkit powered by oneAPI - Intel® Distribution of OpenVINO™ Toolkit powered by oneAPI | Model Training - Models cant be re-trained - Inference only | Operating System - Other (pls specify), Linux | Solution Geographic Availability - India | Solution Type - AI Platform as a Service (AI PaaS) | Topology - Yolo | Use Case - Other (pls specify)

This solution brief highlights how NimbleBox’s platform utilizes Intel® Distribution of OpenVINO™ toolkit and Intel optimizations for machine learning frameworks and languages boost inferencing on popular AI models running on Intel CPUs.

Product Brief
Intel® AI Builders - Product Brief
This solution brief highlights how GIGABYTE was able to improve their AI workloads by implementing a TensorFlow framework with Intel Distribution of OpenVINO toolkit and utilizing 2nd Gen Intel Xeon Scalable processors with Intel DL Boost in a GIGABYTE system.
Categories: 
Application Type - Deep Learning | Compute - Intel® Xeon® Scalable processor | Industry - Government, Retail, Cross-Industry | Intel® AI Analytics Toolkit powered by oneAPI - Intel® Optimization for TensorFlow* | Intel® Distribution of OpenVINO™ Toolkit powered by oneAPI - Intel® Distribution of OpenVINO™ Toolkit powered by oneAPI | Model Training - Models can be trained - requires labeled data | Solution Geographic Availability - Worldwide | Solution Type - AI Platform as a Service (AI PaaS) | Use Case - Facial Detection / Recognition / Classification, Video Surveillance and Analytics | Solution Geographic Availability - Worldwide

This solution brief highlights how GIGABYTE was able to improve their AI workloads by implementing a TensorFlow framework with Intel Distribution of OpenVINO toolkit and utilizing 2nd Gen Intel Xeon Scalable processors with Intel DL Boost in a GIGABYTE system.

Product Brief
Intel® AI Builders - Product Brief
This solution brief highlights how, to help optimize the performance of the full-cycle AI medical imaging solution, Intel offered HYHY technologies such as 2nd Gen Intel® Xeon® Scalable processors with Intel® Deep Learning Boost (Intel® DL Boost) as the core processing engine of this solution, and software optimization tools such as the OpenVINO™ toolkit and Intel® Distribution for Python with HYHY seeing significant improvements to inference speed in image analysis scenarios such as COVID-19 screening and breast cancer detecting.
Categories: 
Application Type - Deep Learning | Combatting Covid-19 - Combatting Covid-19 | Compute - Intel® Xeon® Scalable processor | Deployment Channel - CSP - Other, On-premise (Private Cloud, Other) | Industry - Healthcare, Software | Intel® AI Analytics Toolkit powered by oneAPI - Intel® Optimization for TensorFlow*, Intel® Optimization for PyTorch* | Intel® Distribution of OpenVINO™ Toolkit powered by oneAPI - Intel® Distribution of OpenVINO™ Toolkit powered by oneAPI | Model Training - Models can be trained - requires labeled data | Operating System - Linux | Solution Geographic Availability - Worldwide | Solution Type - AI Software/SaaS | Topology - Unet, Proprietary | Use Case - Medical imaging, analysis and diagnostics

This solution brief highlights how, to help optimize the performance of the full-cycle AI medical imaging solution, Intel offered HYHY technologies such as 2nd Gen Intel® Xeon® Scalable processors with Intel® Deep Learning Boost (Intel® DL Boost) as the core processing engine of this solution, and software optimization tools such as the OpenVINO™ toolkit and Intel® Distribution for Python with HYHY seeing significant improvements to inference speed in image analysis scenarios such as COVID-19 screening and breast cancer detecting.

Product Brief
Intel® AI Builders - Product Brief
This snapshot shares the success achieved from Baosight and Intel team in building an unsupervised time series anomaly detection project, using long short-term memory (LSTM) models on Analytics Zoo
Categories: 
Application Type - Deep Learning | Compute - Intel® Xeon® Scalable processor | Deployment Channel - On-premise (Private Cloud, Other) | Industry - Cross-Industry, Manufacturing | Model Training - Models can be trained - requires labeled data | Solution Geographic Availability - China (PRC) | Solution Type - AI Platform as a Service (AI PaaS) | Topology - LSTM, RNN | Use Case - Predictive maintenance and analytics, Anomaly Detection

This snapshot shares the success achieved from Baosight and Intel team in building an unsupervised time series anomaly detection project, using long short-term memory (LSTM) models on Analytics Zoo