客戶: RedHat UK
格式: 電子書
尺寸: 739 KB
語言: 英語
日期: 25.07.2024
Top considerations for building a production-ready AI/ML environment
The amount of data created is expected to reach more than 221,000 exabytes by 2026. In a digital world, your data can be a critical competitive advantage, but collecting data is only the starting point—how you use your data is the real differentiator.
Artificial intelligence (AI), machine learning (ML), and deep learning (DL) employ data to deliver business insights, automate tasks, and advance system capabilities. These technologies have the potential to transform all aspects of business, from customers and employees to development and operations.
Building AI/ML into your applications can help you achieve measurable business outcomes:
Artificial intelligence (AI), machine learning (ML), and deep learning (DL) employ data to deliver business insights, automate tasks, and advance system capabilities. These technologies have the potential to transform all aspects of business, from customers and employees to development and operations.
Building AI/ML into your applications can help you achieve measurable business outcomes:
- Increase customer satisfaction.
- Offer differentiated digital services.
- Optimize existing business services.
- Automate business operations.
- Increase revenue.
- Improve decision-making.
- Increase efficiency and reduce costs.
