Federated Learning: Training AI Without Moving Private Data
Federated learning is a machine learning approach that trains an algorithm across multiple decentral ...
Voice Cloning for Content Creators: Ethics and Tools
The landscape of content creation is continually evolving, driven by technological advancements that ...
Constitutional AI: Embedding Values into Model Behavior
Constitutional AI: Embedding Values into Model Behavior The field of artificial intelligence (AI) h ...
The Impact of AI on Junior Developer Roles and Coding Bootcamps
The growing prevalence of artificial intelligence (AI) has initiated a significant reevaluation of v ...
Visual Transformers (ViTs) vs CNNs for Image Recognition
Image recognition, the task of identifying and classifying objects within images, has seen signifi ...
AI Hallucinations: New Techniques for Grounding and Fact-Checking
Large language models (LLMs), while capable of generating human-like text, can produce outputs that ...
Local LLMs: Running Llama 3 and Mistral on Consumer Hardware
The proliferation of Large Language Models (LLMs) has opened new avenues for artificial intelligence ...
Copyright Lawsuits and the Future of Fair Use in Training Data
The intersection of copyright law and artificial intelligence (AI) has become a prominent legal batt ...
Model Collapse: What Happens When AI Trains on AI-Generated Data?
AI models are trained on vast datasets. For a long time, this meant data collected from the real wor ...
The Ethics of AI Companions and Digital Intimacy
The increasing sophistication of artificial intelligence (AI) has led to the development of AI compa ...