Definitions
Artificial intelligence (AI): A broad branch of computer science that is involved with building smart machines that can perform tasks requiring human intelligence.
Machine learning (ML) model: A computer program that is designed to find patterns from an unanalyzed dataset.
ML algorithm: A computer program that helps computers understand hidden patterns in data, make predictions about the data, and recommend actions to take.
Machine Learning :
ML is a subset of AI. Computers use ML to learn from and make predictions based on data. ML models can forecast what might happen in the future (predictive analytics) and provide a course of action (prescriptive analytics).
These models become more accurate through a process called training. During training, applications run data through rules and constraints several times. This refines the model’s ability to make accurate recommendations. For example, Amazon.com uses ML to recommend products based on a customer’s purchase history.
Analytics for ML :
ML algorithms can analyze huge volumes of data much faster than humans. Algorithms can also be built to identify trends, correlations, and anomalies in datasets. ML automates the process of extracting insights and patterns from data, saving time and effort.
As the volume of data continues to grow, ML helps organizations to process vast amounts quickly, all while discovering meaningful patterns and using insights for better decision-making. ML is essential for analytics to uncover valuable knowledge and drive innovation across organizations.
ML on AWS:
With AWS AI and ML services, you can get deeper insights from your data while lowering costs. AWS AI and ML services make it convenient for developers to add intelligence to applications without needing ML expertise. You can use AWS pre-trained AI services to automate data extraction and analysis, personalize the customer experience, detect fraudulent online activity, and more. Amazon has two decades of experience developing real world AI and ML applications. Much of this accumulated technology has been packaged up for customer use as a suite of services.
When you build an ML-based workload in AWS, you can choose from three different levels of ML services.
- AWS AI Services AI services provides developers ready-made AI intelligence to integrate into their applications and workflows. AI services use the same deep learning technology that powers Amazon.com and Amazon ML services, so you get quality and accuracy from continuously learning APIs. AI services on AWS don’t require ML skills.
- ML Services ML services makes it convenient for any developer to accelerate their ML innovation with purpose-built ML tools, optimized for ML applications.
- ML Framework and Infrastructure ML practitioners can design their own tools and workflows to build, train, tune, and deploy models.
Generative AI on AWS
Generative AI is a type of ML model that creates new content and ideas from user prompts. Generative AI is not just outputting data, but generating content like conversations, stories, images, videos, and music.
What does it do:
Generative AI learns from existing data and then uses that knowledge to create new, original content. It is done through a type of ML called deep learning, which uses algorithms to mimic the structure of the human brain. These algorithms, called artificial neural networks, are inspired by the biological neurons of the human brain and are able to learn complex patterns from data.
Generative AI is powered by large, pre-trained models called foundation models. Generative AI models are trained on massive amounts of data, which can be anything from text to images to music. The model learns the patterns and structures of the data. It then uses that data to make predictions about what the content should look like, similar to the data it was trained on.
Gen AI Examples:
With the appropriate training, you can use generative AI models for the following:
- Use a generative AI model trained on a corpus of text to generate new text, such as news articles, blog posts, or poems.
- Use a generative AI model trained on a dataset of images to generate new images, such as paintings, photographs, or sketches.
- Use a generative AI model trained on a dataset of music to generate new music, such as songs, symphonies, or concertos.
Amazon CodeWhisperer
Amazon CodeWhisperer is a code generation service that analyzes your code and comments as you write code in your integrated development environment (IDE). It goes beyond code completion by leveraging natural language processing to write code by understanding the comments in the code.