According to statistics, over 40% of all global companies use AI in their business.
Moreover, 40% of marketers utilize artificial intelligence to conduct research to gain insights into products, markets, and customer experiences.
Such stats are enough to prove the significance and popularity of artificial intelligence and machine learning.
So, with the changing trends and demands, from individuals to decision makers and big businesses, all are adopting new technologies that help in having data-driven analysis and decision-making.
This helps them drive business growth and stay ahead of the competition.
Talking about web development, AI and ML are playing their part by integrating AI and ML-powered data analysis tools in various development frameworks, including Ruby on Rails.
This not only enhances the customer experience but also promotes quality decision-making and enhances business intelligence.
Machine Learning and Artificial Intelligence in RoR
Let’s now look into how Rails utilizes the powers of AI and ML.
Ruby on Rails is popular for its web development features, but it is also integrable with artificial intelligence and machine learning.
RoR can be the finest solution to handle the backend of ML and AI-powered web applications while having a user-friendly, responsive interface.
Moreover, it can manage complex tasks with the assistance of ML and AI tools and libraries.
Reasons to Use Ruby for ML and AI
There can be a long list of reasons and benefits for choosing Ruby to integrate AI and ML.
However, we are going to state a few prominent reasons that drive businesses to opt for Ruby to couple with AI or ML.
Some of the key reasons include:
1. Rapid Development
The reason for Ruby’s popularity is its development speed.
Ruby follows the convention-over-configuration approach that enables developers to prototype and build applications quickly.
Moreover, working with AI and ML models requires you to have a high-development-speed environment, which Ruby provides. It assists in iterating on data pipelines, model integration, etc.
2. Effortless Integration
Rails is a flexible framework that provides ease of integration. So, it is well-suited for machine learning and artificial intelligence projects.
Regardless of your approach, Ruby provides flexibility in integrating with the best available tools, especially when you hire AI developers who are experienced in working with ML libraries and Ruby frameworks.
3. Strong Ecosystem
Everyone knows that Rails is a stable framework that is here to stay, as around 664,337 live websites are built on this platform. It comes with a robust set of built-in tools that make it easier to manage complex projects.
Additionally, the active community of Rails contributes to Ruby Gems and tools that assist developers in developing intricate applications, such as AI or ML-powered applications.
4. Scalable Infrastructure
Ruby on Rails is capable of building small to large and enterprise-level applications easily.
When integrating artificial intelligence or machine learning models, real-time data handling and infrastructure scaling become crucial.
Despite this, Ruby handles high traffic efficiently while ensuring the high performance of AI and ML models in production environments.
Case Study: How does Netflix use AI to improve user engagement?
Netflix faced issues with user engagement.
They deployed machine-learning algorithms to analyze user behavior. As a result, this increased their viewer retention.
Libraries and Tools For Integrating RoR with ML and AI
For our readers’ ease, here are the top libraries and tools commonly used while you integrate Ruby with AI or ML.
- TensorFlow.rb
It is a popular machine-learning library that is run on Ruby applications. Its core job is developing machine learning models, helping in training, deploying models, etc.
- PyCall
PyCall assists Ruby developers in calling Python functions and scripts directly from Ruby code. Using this in Ruby allows you to utilize powerful Python libraries like Keras, Scikit-learn, etc.
- Rserve
You might have heard about R, a popular statistical analysis and machine learning language. Rserve plays its part in integrating R with Ruby. With Rserve, Ruby applications communicate with R, allowing you to run complex ML models and statistical analysis.
- Torch.rb
It is a deep-learning library that offers Ruby applications to couple with the popular Torch framework. It plays its role in neural network training. Furthermore, it makes it easier to integrate artificial intelligence into RoR applications.
Final Words
In conclusion, AI and ML are the key players in the web development industry, especially with Ruby on Rails. It helps businesses drive growth and achieve success by using the capabilities of AI-driven analytics. Moreover, it assists in decision-making, which helps organizations stay ahead of the competition.
