Applications of AI Cloud

Some of the more common AI-based applications in the cloud include:

• Chatbot: Chatbot is one of the first software programs designed to simulate human communication and perform a customer service role. With the help of AI and cloud computing, the company can now use APIs to leverage large language models (LLM), giving them powerful chatbots that can understand human spoken or written language and detect the intent of user queries.
• Business intelligence (BI): Cloud computing vendors have long provided BI solutions for collecting, analyzing and interpreting data from internal and external sources to help businesses make decisions. With newer AI models, businesses can move from understanding what happened in the past to better predicting future outcomes.
• Internet of Things (IoT): The Internet of Things consists of devices that are connected to the internet and to each other. IoT devices are used in many industries, including trucking, agriculture and manufacturing, and require "edge computing" systems that place some critical decision-making functions close to the devices being managed, rather than back to cloud data centers. Now, businesses using sophisticated AI cloud services or AI built into SaaS applications can have their IoT devices learn from data and experience over time, continuously improving or suggesting improvements. .
• Generative AI: With the help of cloud computing, powerful LLM-centric generative AI (GenAI) models can now be implemented with just a single API. Businesses can use GenAI to accelerate research, brainstorm ideas, enhance customer service or help desk applications, and many other tasks. RAG helps cloud providers make GenAI more useful by enhancing the LLM’s knowledge base with clients’ latest and securely stored enterprise data.
• AI as a Service (AIaaS) – Public cloud providers now offer AI outsourcing services, allowing companies to test software and machine learning algorithms without risking major infrastructure. They can deploy off-the-shelf AI applications at a fraction of the cost of in-house AI, resulting in significant capital expenditure savings.
• Cognitive Cloud Computing – Cognitive computing uses AI models to replicate and simulate human thinking processes in complex situations. IBM, Google and other companies have built cognitive cloud platforms to provide enterprises with cognitive insight services and promote the application of this technology in finance, retail, healthcare and other industries.