Discover how Lovable, a low-code tool, empowers designers like Thiago Carneiro to build impressive applications like Texture Wizard and YouTube Preview tool, despite limited coding experience. This review explores the code quality of Lovable-generated projects, revealing a consistent tech stack (Vite, React, Tailwind) and clean, componentized code. See how easily you can extend Lovable projects with tools like VS Code and GitHub, as demonstrated by the Flyby demo, which experiments with natural language filtering using Chrome's Built-in Prompt API. Try the Flyby demo and see for yourself.
Explore the evolving role of AI in software development and the critical question of code ownership. Is AI-generated code truly "owned" by developers, or is the focus shifting to prompt engineering? This article delves into the challenges of reproducibility, the need for rigorous review, and how AI's impact on coding skills is reshaping the developer landscape.
Build a full client-side toxicity detection solution using Transformers.js, ONNX Runtime, and the `all-MiniLM-L6-v2` model. Train a custom model on the Kaggle Toxic Comment Classification Challenge dataset, convert it to ONNX, and run it in the browser for fast, private text analysis. Get 98% accuracy with this approach, see the code, and try the live demo.
Learn how to build and deploy a custom sentiment analysis model for the web using PyTorch and Google's LiteRT! This guide walks you through the process of creating a model from scratch, training it on a YouTube comments dataset, converting it to a browser-friendly format, and running it in the browser with TensorFlow Lite and the Google Gen AI JavaScript library. Perfect for web developers looking to leverage custom AI models.
Understand how temperature affects Large Language Model (LLM) output. Learn how temperature parameter changes probability distribution of next-token predictions, impacting creativity and predictability. Explore a visualization tool demonstrating the effects of temperature and top-k parameters on LLM responses.