Artificial intelligence delivery edge network
Approaches, techniques, and mechanisms are disclosed for accessing AI services from one region to another region. An artificial intelligence (AI) service director is configured with mappings from domain names of AI cloud engines to IP addresses of edge nodes of an AI delivery edge network. The AI cloud engines are located in an AI source region. The AI delivery edge network is deployed in a non-AI-source region. An AI application, which accesses AI services using a domain name of an AI cloud engine in the AI cloud engines located in the AI source region, is redirected to an edge node in the edge nodes of the AI delivery edge network located in the non-AI-source region. The AI application is hosted in the non-AI-source region. The AI services is then provided, by way of the edge node located in the non-AI-source region, to the AI application.
1. A computer-implemented method comprising:
configuring an artificial intelligence (AI) service director with one or more mappings from one or more domain names of one or more AI cloud engines to one or more internet protocol (IP) addresses of one or more edge nodes of an AI delivery edge network, wherein the one or more AI cloud engines are located in an AI source geographic region, wherein the AI delivery edge network is deployed in a non-AI-source geographic region other than the AI source geographic region;
redirecting an AI application, which accesses one or more AI services using a domain name of an AI cloud engine in the one or more AI cloud engines located in the AI source geographic region, to an edge node in the one or more edge nodes of the AI delivery edge network located in the non-AI-source geographic region, wherein the AI application is hosted in the non-AI-source geographic region;
providing, by way of the edge node located in the non-AI-source geographic region, the one or more AI services to the AI application;
causing the AI application to the edge node to invoke at least one of the one or more AI services to train a prediction model locally at the edge node.
2. The method of claim 1 , wherein at least one of the one or more AI services is provided in real time or near real time from an AI cloud engine in the one or more AI cloud engines in the AI source geographic region by way of an AI proxy service and an AI proxy agent.
3. The method of claim 1 , wherein at least one of the one or more AI services is provided in real time or near real time from an AI cloud engine in the one or more AI cloud engines in the AI source geographic region without communication mediation of an AI proxy service and an AI proxy agent.
4. The method of claim 1 , wherein at least one of the one or more AI services is provided in real time or near real time from a locally cached AI service stack accessible by the edge node.
5. The method of claim 1 , wherein AI data is exchanged between the AI application and the edge node, and wherein the AI data comprises one or more of: texts, messages, hyperlinks, images, audio, dialogs, audio scenes, videos, documents, AI model parameters, or machine learning (ML) model parameters.
6. The method of claim 1 , wherein the one or more AI services are based on one or more of: linear regression analyses, decision trees, non-linear regression analyses, Gaussian process regression analyses, data clustering, face detection, face recognition, neural networks, trend prediction, natural language processing, deep learning, auto learning one-stop AI algorithm stores, healthcare related AI models, or autonomous driving related AI models.
7. The method of claim 1 , wherein the AI application is in one or more non-AI-source computer networks in the non-AI-source geographic region that are separated from one or more AI source computer networks located in the AI source geographic region.
8. A non-transitory computer readable medium that stores computer instructions which, when executed by one or more computing processors, cause the one or more computing processors to perform:
configuring an artificial intelligence (AI) service director with one or more mappings from one or more domain names of one or more AI cloud engines to one or more internet protocol (IP) addresses of one or more edge nodes of an AI delivery edge network, wherein the one or more AI cloud engines are located in an AI source geographic region, wherein the AI delivery edge network is deployed in a non-AI-source geographic region other than the AI source geographic region;
redirecting an AI application, which accesses one or more AI services using a domain name of an AI cloud engine in the one or more AI cloud engines located in the AI source geographic region, to an edge node in the one or more edge nodes of the AI delivery edge network located in the non-AI-source geographic region, wherein the AI application is hosted in the non-AI-source geographic region;
providing, by way of the edge node located in the non-AI-source geographic region, the one or more AI services to the AI application;
causing the AI application to the edge node to invoke at least one of the one or more AI services to train a prediction model locally at the edge node.
9. The medium of claim 8 , wherein at least one of the one or more AI services is provided in real time or near real time from an AI cloud engine in the one or more AI cloud engines in the AI source geographic region by way of an AI proxy service and an AI proxy agent.
10. The medium of claim 8 , wherein at least one of the one or more AI services is provided in real time or near real time from an AI cloud engine in the one or more AI cloud engines in the AI source geographic region without communication mediation of an AI proxy service and an AI proxy agent.
11. The medium of claim 8 , wherein at least one of the one or more AI services is provided in real time or near real time from a locally cached AI service stack accessible by the edge node.
12. The medium of claim 8 , wherein AI data is exchanged between the AI application and the edge node, and wherein the AI data comprises one or more of: texts, messages, hyperlinks, images, audio, dialogs, audio scenes, videos, documents, AI model parameters, or machine learning (ML) model parameters.
13. The medium of claim 8 , wherein the one or more AI services are based on one or more of: linear regression analyses, decision trees, non-linear regression analyses, Gaussian process regression analyses, data clustering, face detection, face recognition, neural networks, trend prediction, natural language processing, deep learning, auto learning one-stop AI algorithm stores, healthcare related AI models, or autonomous driving related AI models.
14. The medium of claim 8 , wherein the AI application is in one or more non-AI-source computer networks in the non-AI-source geographic region that are separated from one or more AI source computer networks located in the AI source geographic region.
15. An apparatus, comprising:
one or more computing processors;
a non-transitory computer readable medium that stores computer instructions which, when executed by the one or more computing processors, cause the one or more computing processors to perform:
configuring an artificial intelligence (AI) service director with one or more mappings from one or more domain names of one or more AI cloud engines to one or more internet protocol (IP) addresses of one or more edge nodes of an AI delivery edge network, wherein the one or more AI cloud engines are located in an AI source geographic region, wherein the AI delivery edge network is deployed in a non-AI-source geographic region;
redirecting an AI application, which accesses one or more AI services using a domain name of an AI cloud engine in the one or more AI cloud engines located in the AI source geographic region, to an edge node in the one or more edge nodes of the AI delivery edge network located in the non-AI-source geographic region, wherein the AI application is hosted in the non-AI-source geographic region;
providing, by way of the edge node located in the non-AI-source geographic region, the one or more AI services to the AI application;
causing the AI application to the edge node to invoke at least one of the one or more AI services to train a prediction model locally at the edge node.
16. The apparatus of claim 15 , wherein at least one of the one or more AI services is provided in real time or near real time from an AI cloud engine in the one or more AI cloud engines in the AI source geographic region by way of an AI proxy service and an AI proxy agent.
17. The apparatus of claim 15 , wherein at least one of the one or more AI services is provided in real time or near real time from an AI cloud engine in the one or more AI cloud engines in the AI source geographic region without communication mediation of an AI proxy service and an AI proxy agent.
18. The apparatus of claim 15 , wherein at least one of the one or more AI services is provided in real time or near real time from a locally cached AI service stack accessible by the edge node.
19. The apparatus of claim 15 , wherein AI data is exchanged between the AI application and the edge node, and wherein the AI data comprises one or more of: texts, messages, hyperlinks, images, audio, dialogs, audio scenes, videos, documents, AI model parameters, or machine learning (ML) model parameters.
20. The apparatus of claim 15 , wherein the one or more AI services are based on one or more of: linear regression analyses, decision trees, non-linear regression analyses, Gaussian process regression analyses, data clustering, face detection, face recognition, neural networks, trend prediction, natural language processing, deep learning, auto learning one-stop AI algorithm stores, healthcare related AI models, or autonomous driving related AI models.
21. The apparatus of claim 15 , wherein the AI application is in one or more non-AI-source computer networks in the non-AI-source geographic region that are separated from one or more AI source computer networks located in the AI source geographic region.