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Why AI and Machine Learning Have Cases Outside of Cloud

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Cloud computing has been a key part of the rise of AI, but as more organizations look to improve their capabilities, they're moving toward a hybrid approach that includes both cloud and edge computing. Since cloud computing is often thought of as another term for all-in-one solutions, you might wonder why companies want to move away from it at all. The fact is, there are many reasons why customers are choosing hybrid approaches over purely cloud-based architectures. AI Lurking in the Shadows You might not know it, but AI has been in the cloud for a long time. Amazon, Microsoft, Google and other cloud providers have been offering machine learning services as a service (SaaS) for years. These services make it easy for developers to build applications that use machine learning models without having to worry about how those models are trained or implemented. For example, if you want to build an e-commerce site that recommend

Key Value Pair Performance Awareness In C#

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Traversing a long and distinguished career in various roles in software development it is common to reuse several "killer" patterns or structures over and over again as their application and benefits has been proven multiple times over. One of those "killer" patterns involve the use of various key/value pair data structures that are available within the .NET framework, each having their own personality and use case. While there are many benefits of using these in-memory data stores we have seen the most benefit in using a key/value pair as a dynamic caching mechanism that can significantly reduce the cost of accessing a database to obtain values that often times don't see much change or volatility, or in a simpler case, accessing an expensive item of value and retaining for quick access later. Key/Value Defined A key value pair is a data structure that consists of two pa

Why The Agile Model Of Software Development Doesn't Work For ERP Projects

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ERP software applications are critical for many businesses. They're used to manage business processes, make better decisions, and provide a global view of data. However, ERP systems are not positioned to be implemented or customized using the Agile development model. This often leads companies that want an Agile approach to find themselves in trouble during implementation. The Agile model is a software development approach that focuses on close collaboration between different parts of the organization, iterative development and frequent testing during the process. The idea behind this is that it allows for quick feedback which can help developers make changes as needed so that they don't end up with inefficient code or poor-quality products. However, Agile doesn't work well for enterprise resource planning (ERP) applications because these are typically large projects with comple