Artificial Intelligence
Artificial intelligence (AI) is a field of computer science concerned with creating systems capable of performing tasks that require human intelligence. The field was formally established in 1956 at the Dartmouth Workshop, where the term "artificial intelligence" was coined and the discipline's foundational questions were defined[^c1].
After decades of alternating progress and setbacks, AI underwent a transformative shift in the 2010s driven by deep learning. The AlexNet architecture's victory in the 2012 ImageNet competition sparked the deep learning revolution in computer vision[^c2], while the introduction of the Transformer architecture in 2017 enabled unprecedented advances in natural language processing and became the foundation for nearly all modern AI systems[^c3]. Subsequent models such as BERT, GPT-4, Stable Diffusion, Claude, and Gemini demonstrated rapid scaling of capabilities across language understanding, text generation, and image synthesis. By mid-2026, frontier models had reached levels of autonomous reasoning and software engineering that compressed months of human work into days, with models independently conducting scientific research and generating novel drug design candidates. New architectural approaches also emerged: the first cognitive models demonstrated that small-parameter systems could match thousand-billion-parameter frontier performance in multi-agent tasks, while Google's Open Knowledge Format standardized Markdown-based enterprise knowledge management for LLM deployment[^c8][^c10]. Meta's release of the proprietary Muse Spark model signaled a shift away from open-weight distribution by major AI labs[^c9].
The AI boom of the 2020s attracted enormous investment, with companies such as OpenAI, Anthropic, and Nvidia reaching valuations in the hundreds of billions of dollars[^c4]. The rapid advancement of AI capabilities prompted international policy responses, including the Bletchley Declaration on frontier AI safety and the EU AI Act's comprehensive regulatory framework[^c5][^c6]. Studies estimated that generative AI could affect hundreds of millions of jobs globally while also boosting economic productivity[^c7]. The broader historical arc of these developments is documented in the [[History of Artificial Intelligence]].