From AI To Gen AI: How Cloud Computing Is Accelerating Intelligent Automation

Over the past few years, AI has gone from being a future idea to a basic technology used by many industries. AI allows organizations in both customer service and manufacturing to streamline their workflows and make better decisions. Our shift to Gen AI in AI is bringing about an increased use of intelligent automation, made stronger by cloud computing.

When Gen AI is linked to cloud computing, it affects more than technology; it also reforms how enterprises work, experiment and reach their targets. Still, what roles does cloud computing play in this development? How can we help professionals keep up with these evolving trends? We’re ready to get started.

Being aware of the stance from AI to Gen AI

To truly value cloud computing, you must be familiar with the movement of AI into Gen AI.

AI systems that use traditional approaches receive training from organized data, then look for patterns and generate predictions or decisions. You might think about machine learning algorithms that distinguish images, estimate sales or recognize fraud.

Generative AI is an even bigger development than creating repetitive text. It does not limit itself to understanding or forecasting; it also makes original work. With help from GPT and diffusion models for image generation, Gen AI generates text that reads like what a human would write, as well as types of coding, musical pieces, videos and anything else viable.

Because of this capability, AI is starting to carry out creative and thought tasks that people previously did alone — writing advertisements, designing models and providing data for training other models.

Cloud Computing Supports the Main Framework for Intelligent Automation

Although Gen AI has a lot of promise, it takes a lot of effort and resources to create and implement these models. Very large language models (LLMs) cannot be trained unless one has a lot of data, powerful computers and enough storage — and all of these are readily available through cloud computing.

Here’s why cloud platforms are speeding up the Gen AI revolution for automation.

1. Easily Scalable Resources for Model Training and Using the Model

GPT-4 and Google’s Gemini need billions of parameters and a large amount of data to develop their models. The way organizations run on their own servers is not flexible enough to tackle today’s requirements. People working in AI can quickly increase or reduce compute power (AWS EC2, Google TPUs, Azure VMs) from the cloud as needed.

This way, AI is accessible to startups, educational places, as well as technology leaders, since they can test and use the cloud or pay as needed.

2. Qlouds offers a straightforward way to use pre-made models and APIs.

Providers of cloud technology now make Gen AI models accessible via application programming interfaces. You can access OpenAI’s models on Azure, as well as Google’s PaLM models from Vertex AI. By doing this, Gen AI now allows developers to build apps using existing models, instead of having to build and train their own.

It only takes calling an API for businesses to add tasks such as summarization, translation or the generation of images into their processes, resulting in much shorter development times.

3. Artificial Intelligence development with integrated toolchains

Developing AI in the cloud is supported by complete platforms used along the entire process. Such resources consist of data import tools, places to train models (for example, SageMaker and Azure ML Studio), tracking experiments, versions of the models and MLOps pipelines.

With this integration, automated solutions are developed more easily as data science, engineering and operations teams work together without as many problems.

4. Organizations should focus on Security, Compliance and Governance.

Because AI is now central to business operations, data privacy and the integrity of models are very important. Thanks to advanced security measures, identity verification, logs for everything and compliance certifications, businesses can rely on the AI they create.

Intelligent Automation in Real Business Settings

Take a look at these ways in which Gen AI and the cloud are supporting intelligent automation:

Gen AI courses are used to train agents of AI on specific information, letting them address consumer concerns with natural speech which reduces work for people.

Developers can now use GitHub Copilot which uses Gen AI, to make programming faster and help avoid making errors.

IDP systems supported by Gen AI enable people in financial services to retrieve information from invoices, contracts and KYC documentation much faster with fewer mistakes.

AI diagnostics in healthcare work with cloud records and images to notice diseases early and form fitting treatment plans just for each person.

Gaining new knowledge for the age of AI and the Cloud

Since there is an upsurge in Gen AI-powered automation by companies, skilled people who can handle both AI and cloud are needed more than ever. All types of developers and data professionals need to learn more about these areas to stay important.

Join an artificial intelligence course to gain solid knowledge of machine learning, deep learning and natural language processing. Most of these programs involve doing projects with data that is typical within a company setting.

Find courses that cover large language models, prompt engineering, ethical AI and building things with APIs from companies including OpenAI, Cohere and Anthropic.

Don’t forget the basics — take on cloud computing courses to master cloud architecture, creating code for your infrastructure, dockerization and the services provided by AWS, Azure and Google Cloud.

Connecting information from these three parts of engineering helps professionals build solutions that truly matter.

What’s ahead: Introducing the New Wave of Co-Pilots

The future will see cloud computing and Gen AI working together as the main drivers of new digital change. We are headed toward having AI assistants at our sides in many fields such as HR, finance, law and creative industries.

Not only will these systems take care of routine activities, but they will also work together with people to make work more effective and encourage new ideas. More mature quantum computing and edge AI will fuel the growth of cloud platforms as the central system for this smart enterprise.

Conclusion

Cloud computing is playing a big role in the growth of intelligent automation from AI to Gen AI. Because of this combination, businesses are able to invent more quickly, expand more wisely and use their resources more effectively.

As technology advances, anyone focused on learning both AI, Gen AI and cloud computing will help design the future. No matter if you’re new to AI or seeking greater expertise, now is the best time to look for the right courses on artificial intelligence, dabble in gen ai classes and build a stronger base with cloud computing courses.