Part 3/17:
A core challenge in understanding AI is its vague terminology. Originating in 1956 with John McCarthy’s coinage, "artificial intelligence" was initially a plea for research funding rather than a scientific term. Today, “AI” encompasses a vast array of technologies—from simple speech assistants like Siri to sophisticated language models like GPT-4.
Most current industry efforts, particularly at giants like OpenAI, Google, and Meta, focus on deep learning systems. These models use neural networks trained on massive datasets to identify patterns, enabling tasks like text generation and predictions. However, the umbrella term "AI" is a “suitcase word”—a container for diverse, often unrelated technologies—contributing to misconceptions and misaligned policies.