AI-generated text is permeating all corners of our digital life. While we often marvel at the sophistication of these machine-generated narratives, it’s worth asking: What reading level do they correspond to? Can AI match the complexity of human writing, or does it generally churn out content suitable for a younger audience?
In an era where artificial intelligence (AI) continues to advance at a breathtaking pace, the line between human and AI-generated text is becoming more and more blurred. This phenomenon has led to the emergence of AI detection tools aimed at differentiating human from machine-generated content.
The video “AI Art: How artists are using and confronting machine learning | HOW TO SEE LIKE A MACHINE” by The Museum of Modern Art presents a comprehensive exploration of the intersection of AI and art. It features insights from three artists—Kate Crawford, Trevor Paglen, and Refik Anadol—who engage with AI and machine learning in their art practices.
In the continuous quest to explore how artificial intelligence grasps and generates different artistic styles, we again turned to Stable Diffusion, leveraging the capabilities of DreamStudio. This time, however, our approach was twofold: a comparative analysis between Stable Diffusion 1.5 (SD 1.5) and Stable Diffusion 2.1 (SD 2.1). In both iterations, the same styles were tested, enabling us to discern how different versions of the AI model fared with the same prompts.
AI’s prowess in generating poetry has been put to the test in our latest experiment – initiating poetic compositions through conversational prompts. Our guide through this exploration, ChatGPT, was tasked to respond to a variety of requests, all presented in a casual conversational manner, as if from a friend or a curious reader.
Welcome back to Neural Imaginarium, where we continue to explore the fascinating world of AI-generated art. As your Senior AI Writer, I’m here to guide you through some of the most innovative tools available for creating unique and captivating pieces of art. Let’s dive in!
The arena of Artificial Intelligence (AI) and Large Language Models (LLMs) continues to be an ever-evolving landscape. In a recent article, the focus was on how even the most advanced AI language models like Google’s BERT and OpenAI’s ChatGPT grapple with one fundamental aspect of human language: negation.