Artificial Intelligence (AI) is a technology for tackling complex problems such as answering questions. For instance, I got the following response when asking ChatGPT, an AI powered chat bot, "Why AI":
Why AIby ChatGPT
AI, or artificial intelligence, has the potential to revolutionize many aspects of our lives, from healthcare and transportation to entertainment and education. AI systems are capable of analyzing vast amounts of data, detecting patterns and insights that may be difficult or impossible for humans to discern. They can also automate tedious or dangerous tasks, freeing up humans to focus on more creative or fulfilling work.
AI has already made significant contributions to fields such as natural language processing, computer vision, and robotics. It has the potential to greatly improve medical diagnoses, personalized healthcare, and drug discovery. It can also help reduce energy consumption and waste in industries such as manufacturing and agriculture.
Overall, AI has the potential to create significant benefits for society, but it also raises important ethical and social concerns, such as job displacement and bias in decision-making. Therefore, it is important to approach AI development and deployment with caution and consideration for its potential impact on individuals and society as a whole.
1. Salesforce Einstein Prediction
Machine learning is a type of AI that enables computers to solve problems based on data examples. Einstein Prediction is based on an end-to-end automated machine learning engine developed by Salesforce. It is used to predict asset failure in Calem in the coming release of R2023a.
2. Calem Enterprise Lightning
Calem Enterprise Lightning is a a native application On the Salesforce platform™ for Enterprise Asset Maintenance Management (EAM/CMMS). It is available through Salesforce AppExchange since 2018.
3. Asset Failure Prediction
Asset Failure Prediction is implemented through an integration of Calem Enterprise with Calem Enterprise Lightning on the Salesforce platform™.
4. Asset Data Segmentation
Asset data is segmented based on Asset Failure status which is available from R2023a. Example data is prepared by data analysts of Calem customers so the prediction is trained for the customer assets.
|Asset Fail Status||Data Segmentation|
|Failed||These assets failed within lifespan. They are used as examples for failed assets.|
|Not-Failed||These assets do not fail within lifespan. They are used as examples for assets not failed.|
|Pending||These assets will be predicted for failure.|
|Not-Applicable||Ignore asset failure prediction for assets of this fail status.|
5. Einstein Prediction Builder
Go to Admin module of Calem Enterprise Lightning and search for "prediction". Einstein Prediction Builder will show. Launch the builder to create a prediction for asset failure.
That is all to create the asset fail prediction. It takes a while for Einstein to provision the prediction. You may come back to the prediction builder later to continue the prediction setup.
6. Evaluate Asset Fail Prediction
The evaluation of asset fail prediction help understand the prediction including answers for the questions below.
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