Discover the meanings of popular AI terms such as AGI and GPUs that have become part of our daily lexicon. Have you ever wondered about the significance of LLM or what a GPU actually is? As AI continues to advance, a new set of vocabulary is emerging, from concepts like AGI to prompt engineering, constantly expanding.
Refer to this comprehensive list of AI-related terminology to discuss the technology confidently. The integration of AI into our lives is becoming increasingly pervasive, yet understanding it can still be challenging. Terms like agentic AI and UBI are now commonplace, making it seem like tech leaders and policymakers are conversing in a different language.
Even if you don’t actively engage with AI technology, chances are it plays a role in your banking transactions, healthcare services, entertainment platforms, and even your vehicle. To effectively converse about AI, familiarize yourself with key individuals, organizations, and terms listed here in alphabetical order.
Essential AI Terminology:
– Agentic: An artificial intelligence category capable of autonomous decision-making with minimal human intervention.
– AGI: Stands for “Artificial General Intelligence,” denoting AI systems capable of complex cognitive tasks similar to human cognition.
– Alignment: An area of AI safety research focused on ensuring that AI systems align with human values and intentions.
– Bias: Reflects the tendency for AI models to adopt human biases present in the data they are trained on.
– Capability overhang: A term coined by Microsoft CTO Kevin Scott referring to the gap between AI model capabilities and their actual utilization.
– ChatGPT: OpenAI’s renowned chatbot that sparked significant interest upon its 2022 launch.
– Claude: Anthropic’s flagship model unveiled in March 2023.
– Compute: Resources required for training AI models and processing data.
– Data centers: Facilities housing numerous advanced computer chips and GPUs for processing tasks.
– Deepfake: Deceptive media generated by AI to appear authentic.
– Distillation: Process of transferring knowledge from a large AI model to a smaller one.
– Doomer: A term mocking skeptics wary of potential risks associated with AI development.
– Effective altruists: Advocates believing in universal equal value for all lives.
– Federal preemption: Debate over state versus federal authority in setting AI-related policies.
– Frontier models: Cutting-edge AI technology examples.
– Gemini: Google’s primary AI model initially known as “Bard” launched in 2023.
– Gigawatts: Unit measuring energy output capable of powering numerous homes.
– GPU: Graphics processing unit used by companies for training and deploying AI models.
– Hallucinations: Incorrect information generated by large language models presented as factual.
– Large language model: Complex program designed for human-like text generation and comprehension.
– Machine learning: Refers to self-adaptive AI systems capable of learning independently (also known as deep learning).
– Multimodal: Ability of AI models to process text, images, and audio simultaneously for outputs.
– Natural language processing (NLP): Encompasses various methods for interpreting and understanding human language within the field of AI.
– Neural network: Machine learning program mimicking human brain functions for learning purposes.
– Open-source: Term describing freely accessible and modifiable computer programs available to all users.
– Optical character recognition (OCR): Technology recognizing text within images electronically.
– Prompt engineering: Process involving querying chatbots to elicit desired responses effectively.
– Rationalists: Advocates employing logic, reason, and empirical evidence for understanding the world efficiently.
– Responsible scaling policies: Guidelines aiding AI developers in mitigating safety risks during scaling efforts.
– Singularity: The theoretical point where artificial intelligence surpasses human intelligence capabilities significantly.
Top Leaders and Companies in the AI Industry:
Various prominent figures shaping the landscape of artificial intelligence include:
Sam Altman – Co-founder and CEO of OpenAI;
Dario Amodei – CEO and co-founder of Anthropic;
Demis Hassabis – Co-founder of DeepMind now leading Google DeepMind;
Jensen Huang – CEO and co-founder of Nvidia;
Alex Karp – CEO and co-founder of Palantir;
Yann LeCun – Former chief scientist at Meta;
Mira Murati – CEO and co-founder at Thinking Machines;
Elon Musk – Tesla and SpaceX CEO who launched xAI in 2023;
Satya Nadella – Current CEO at Microsoft;
Sundar Pichai – CEO at Google;
Mustafa Suleyman – Co-founder at DeepMind;
Ilya Sutskever – Co-founder & chief scientist at Safe Superintelligence;
Alexandr Wang – Chief AI officer at Meta;
Liang Wenfeng – Hedge fund manager behind Chinese startup DeepSeek;
Mark Zuckerberg – Founder of Facebook, currently serving as Meta’s CEO.