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Building AI Applications in Ruby
- Ruby is often not mentioned in the context of AI applications compared to Python, but it can be a better language for building web apps with AI integration, as it offers simplicity and developer happiness.
- The complexity in modern web apps, especially with single-page applications (SPAs) like MERN stack, has led to longer development times and higher costs.
- Ruby on Rails (Rails) is highlighted as a framework suited for rapid development of quality apps with AI integration, offering simplicity and efficiency compared to Django in some aspects.
- For AI integration, modern Rails tools like Hotwire, Turbo, and Stimulus allow crafting SPA-like experiences without heavy JavaScript, providing a mix of ease and functionality.
- The rise of microservices architecture in contrast to monoliths has added complexity to app development, yet it offers scalability and the flexibility of a polyglot tech stack.
- Python and Ruby, though unique in philosophy and design principles, share similarities like high-level interpretation, dynamic typing, object-oriented programming, readable syntax, and wide package ecosystems.
- Recent AI-based gems in Ruby, such as RubyLLM for multi-turn conversations, Neighbors for nearest-neighbors search, Async for non-blocking I/O tasks, and Torch.rb for training deep learning models, are making waves in the Ruby community.
- Building web applications with AI integration rapidly and cost-effectively often demands a monolithic architecture focusing on quality apps delivered speedily, with Ruby on Rails emerging as a favorable choice.
- Research in AI or training ML models from scratch may still favor Python due to its ecosystem and libraries; however, for integrating LLMs into web apps, Ruby is considered a superior option.
- Overall, choosing between Python and Ruby for AI applications depends on the project's requirements, with Ruby offering simplicity and efficiency for web development with AI integration.
- The article concludes with a hint at a forthcoming part three, diving into a simple experiment on building a web app with AI integration, encouraging readers to explore Ruby's potential for their projects.
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