A survival guide to the words behind the AI boom

The artificial intelligence landscape has exploded in recent years, making it nearly impossible to overlook its presence. However, deciphering the language surrounding AI can be quite a challenge. Tech leaders, financial analysts, and politicians often seem to communicate in a complex jargon that evolves as rapidly as the technology itself. Even if you’re not directly involved with AI, it’s likely that industries such as finance, healthcare, streaming services, and even automotive sectors are integrating AI into their operations. To help you navigate this intricate terminology, here’s a comprehensive alphabetical guide to key AI concepts, personalities, and organizations. **Agentic AI** refers to a form of artificial intelligence that can autonomously make decisions with minimal human intervention, functioning continuously without fatigue. This concept has gained traction, particularly with tools like OpenClaw, marking a significant milestone in generative AI since the emergence of ChatGPT. **Artificial General Intelligence (AGI)** is a much-anticipated goal in AI development, representing the ability of machines to perform complex cognitive tasks akin to human reasoning, including self-awareness and critical thinking. Many industry experts are pursuing this theoretical benchmark. **Alignment** focuses on ensuring AI systems' objectives and actions align with human values and intentions, addressing concerns about safety and ethical implications. **Bias** is a critical issue, as AI models can inherit the biases present in the training data created by humans. These biases can distort outcomes and include various forms such as prejudice, measurement, cognitive, and exclusion biases. The concept of **Capability Overhang**—coined by Microsoft's CTO Kevin Scott—describes the disparity between the potential capabilities of AI models and their current practical applications. **ChatGPT**, OpenAI's flagship chatbot, made waves upon its launch in 2022, often heralded as the catalyst for the current AI race. **Claude**, created by Anthropic, debuted in March 2023 and has garnered attention for its coding capabilities, significantly impacting the tech industry’s stock fluctuations in early 2026. **Compute** encompasses the computational resources essential for training AI models, which include GPUs, cloud services, and data processing infrastructures. As of 2026, many organizations have begun modifying their pricing structures due to resource limitations. A **Context Window** refers to the capacity of a large language model to recall information based on user prompts, with larger context windows reducing the chances of generating hallucinations and enabling richer dialogues. **Data Centers** are vast facilities housing thousands of advanced computer chips and GPUs, necessary for managing extensive data and executing complex AI tasks. With the increased demand for AI, these centers are expanding, raising concerns about energy consumption and space. **Deepfake** technology utilizes AI to create hyper-realistic images, videos, or voices, often used to mislead audiences. This technology has raised significant ethical and legal questions, particularly regarding privacy and consent. **Distillation** is a method for transferring the knowledge from a larger AI model to a smaller one, allowing for the replication of advanced capabilities. Accusations have arisen against some companies, particularly in China, for employing unethical tactics to enhance their models. **Effective Altruists** advocate for deploying AI in ways that maximize societal benefits, addressing issues like climate change and poverty, although the movement has faced criticism recently. Discussions of **Federal Preemption** revolve around whether AI regulations should be nationally standardized or left to individual states, a contentious topic in U.S. politics. **Frontier Models** denote the cutting-edge AI technologies, while **Gemini**, Google's flagship model launched in 2023, has drawn comparisons to ChatGPT for its capabilities. Understanding **Gigawatts** is crucial when considering the energy demands of AI data centers, with one gigawatt capable of powering approximately 750,000 homes. In summary, as AI continues to reshape our world, familiarizing oneself with these foundational terms can help demystify the ongoing revolution. Engaging with these concepts will not only enhance your understanding but also prepare you to participate in essential conversations around this transformative technology.