Developer Resources from Intel and IBM*
Optimize Performance of IBM Watson* Natural Language Processing (NLP) Library
The Watson* NLP Library for Embed provides high-performance acceleration with Intel® AI software integration on the new Intel® Xeon® Scalable processors. This results in faster response times and shorter model inference time, making it quicker to surface real-time actionable insights to provide users with the tools they need to pull metadata and patterns from massive troves of data.
The new IBM* watsonx data and AI platform runs on Red Hat OpenShift* platform everywhere.
AI Developer Tools
AI tools from Intel and the Intel® Gaudi® AI accelerator empower IBM to deliver high-performance AI workloads.
AI Tools
Accelerate end-to-end data science and machine learning pipelines using popular tools based on Python* and frameworks optimized for performance and interoperability.
Resources
Documentation
- How Intel® oneAPI Tools Accelerate the Watson NLP Library
- IBM to Help Businesses Scale AI Workloads for All Data, Anywhere
- How Watson NLP Delivers Increased Performance with Intel Optimizations
- Improve Watson with Libraries from Intel
- Improve Watson NLP Performance in IBM Products through Intel Optimizations
- Performance Gains When Combining Watson Natural Language Understanding (NLU) with Intel® oneAPI Deep Neural Network Library (oneDNN)
- Natural Language Processing: How Intel® Tools are Accelerating IBM Watson NLP Library
- Technical and How-To Articles for AI Tools
Do It Yourself
Intel® Gaudi® Processor
These accelerators are high-performance, high-efficiency accelerators purpose-built for deep learning training.
Resources
Documentation
Training
More Resources
AI Machine Learning Portfolio
Explore all Intel® AI content for developers.
AI Tools
Accelerate end-to-end machine learning and data science pipelines with optimized deep learning frameworks and high-performing Python* libraries.
Intel® AI Hardware
The Intel portfolio for AI hardware covers everything from data science workstations to data preprocessing, machine learning and deep learning modeling, and deployment in the data center and at the intelligent edge.