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Top 5 AI Cloud Services to Learn in 2024

PLUS: The Future of Apple’s Vision Pro

In Today’s Cloudbites:

🤓 Top 5 AI Cloud Services to Learn

🛠️ Build a Project with Amazon PartyRock

☁️ Online Cloud Events to Look Forward to

🤫 PLUS: The Future of Apple’s Vision Pro

Read time: 6 minutes

Hi friends, welcome back to Cloudbites

Today, I’ll talk about 5 AI Cloud platforms in 2024 that you can learn to improve your understanding of AI in the Cloud. I’ll also share some resources to help develop your Cloud skills, and the latest update on Apple’s Vision Pro.

CLOUD COMPUTING ☁️

🤓 Top 5 AI Cloud Services to Learn

Many businesses are adopting AI to streamline operations, enhance customer experiences, and innovate products. As a Cloud learner, mastering AI Cloud services could help you advance in your career.

Here are 5 AI Cloud platforms that you could explore:

#1 Azure Machine Learning

Azure Machine Learning (ML) is a platform for building, training, and deploying ML models by Microsoft. 

It seamlessly integrates with Azure’s ecosystem, facilitating scalable data processing and deployment through services like Azure DevOps for CI/CD pipelines. 

In real-life, it is used in the healthcare industry to develop predictive models that assist in diagnosing diseases, improving treatment outcomes.

Whether you’re a beginner or professional, Azure ML is an ideal platform to learn and streamline AI project development and management.

#2 AWS SageMaker

Another AI Cloud service is AWS SageMaker, which provides a complete environment to build, train, and deploy models at scale. 

What makes it different is its built-in algorithms, automated ability for model tuning, and workflow automation.

Some financial institutions utilize SageMaker to automatically analyze transaction patterns in real-time to detect potential fraud. 

As SageMaker supports popular frameworks like TensorFlow, it often becomes firms’ chosen platform to accelerate operational efficiency with AI. 

#3 Google Cloud Vertex AI

Google Cloud Vertex AI simplifies the ML lifecycle from data preparation to model deployment. 

It utilizes Google Cloud’s infrastructure for scalable training and integrates seamlessly with BigQuery for data analysis and storage. 

Retail companies leverage Vertex AI to personalize customer recommendations and enhance customer satisfaction as well as sales by analyzing past purchase behavior.

What’s unique about this service is its ability to leverage AI across their operations with advanced features like Explainable AI for understanding model decisions.

#4 IBM Watson Studio

Another platform is IBM Watson Studio that empowers people to collaborate on AI projects effectively. 

It supports multiple programming languages, enables automating model development and deploying models across hybrid Cloud environments. 

For example, insurance companies work with Watson Studio to predict trends and optimize pricing strategies for risk mitigation. 

With features for interactive exploration and model prototyping, IBM Watson Studio will help enhance your productivity in AI development. 

#5 AWS Amazon Bedrock

Last but not least, AWS Amazon Bedrock is an advanced AI Cloud service designed to provide comprehensive tools for ML model development and deployment.

The service consists of automated model training and seamless integration with the AWS environment, enabling you to easily streamline deployment workflows.

With Amazon Bedrock, developers build and innovate generative AI applications from creating an AI research assistant to a web-based image generator. 

That being said, it could support you to practice your Cloud skills and innovate across diverse industries.

🛠️ Build Your Own App With PartyRock AI

Are you interested in creating a Generative AI application but too sure where to start?

I would recommend you to start with PartyRock AI, an AWS AI Cloud service that could help you easily build applications.

What I like the most about this platform is that you don’t need any prior experience nor any high-level tech expertise to get started. 

To learn more about how to begin, check out my latest YouTube video tutorial to create your own application: Build With Me: PartyRock AI Application | AWS Project.

☁️ Online Cloud Events to Look Forward to

#1 Azure – Data Fundamentals (July 8 & 9)

Learn about Azure relational database services and Azure Storage for non-relational data, and discover the benefits of Azure Cosmos DB, a fast NoSQL database with open APIs for any scale.

Click here to register. 

#2 AWS – Machine Learning Basics (July 11)

An overview of the concepts, terminology, and processes of the exciting field of machine learning.

Click here to register.

#3 Google Cloud – Best Practices for LLM & ML Models (July 11)

Get expert tips on model optimisation, deployment strategies, and continuous monitoring for long-term success.

Click here to register.

ARTIFICIAL INTELLIGENCE 🤖

🤫 PLUS: The Future of Apple’s Vision Pro

Bloomberg recently reported that Apple is integrating AI features from Apple Intelligence to the Vision Pro headsets.

Source: Apple

💡Here’s what you should know:

  • Apple Intelligence was initially planned to be integrated for Mac, iPhone, and iPad, but is now in talks to be included in the Vision Pro headset

  • This update is expected to result in upgrades on Siri, Apple Intelligence’s writing tools, and the OpenAI-powered chatbot

  • The Apple Intelligence integration is not likely to happen in this year’s Vision Pro production batch, but you may expect it to launch in the near future

THAT’S A WRAP

Thanks for reading! 😊

P.S. How was today's email? Reply directly with your feedback, or DM me on Twitter @techwithlucy