Does More Training Data Always Improve Results?
The claim sounds simple: if a model learns from examples, then giving it more examples should always make it better. This assumption shows up everywhere, from…
Category: AI-Myths
Is Open Source AI Really Free? What It Costs in Practice
The claim “open source AI is completely free” shows up everywhere—from GitHub threads to product comparisons to budget planning for startups. It sounds clean and binary:…
Does Fine-Tuning Always Improve Model Accuracy?
“Fine-tuning always improves accuracy” sounds like a reasonable rule of thumb: you take a capable base model, show it more examples from your domain, and it…
Will AI Replace Developers Completely?
The claim that “AI will replace developers completely” shows up whenever code generation gets noticeably better. It feels plausible because writing code is a visible output,…
Do More Parameters Always Mean Better AI?
The idea sounds simple: if an AI model has more parameters, it must be “smarter.” Parameter count is easy to compare, easy to market, and often…