Natural Language Processing (NLP)
The branch of AI focused on enabling computers to understand, interpret, and generate human language, encompassing tasks from translation to sentiment analysis to conversation.
NLP has been transformed by large language models, which have achieved near-human performance on many benchmarks. The NLP market is projected to exceed $43 billion by 2025. Key applications include machine translation (serving billions of queries daily), chatbots, search engines, and content moderation. The shift from rule-based to neural NLP began with word embeddings around 2013 and accelerated dramatically with transformers in 2017 and LLMs from 2020 onward.
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Related Terms
Artificial General Intelligence (AGI)
A hypothetical form of AI that can understand, learn, and apply knowledge across any intellectual task at or above human level, rather than being specialized for specific tasks.
AI Alignment
The research field focused on ensuring AI systems behave in accordance with human values and intentions, particularly as systems become more capable.
ChatGPT
OpenAI's conversational AI assistant, launched in November 2022, which catalyzed the current generative AI boom by demonstrating the capabilities of large language models to a mainstream audience.
Enterprise AI Adoption
The rate at which businesses integrate AI technologies into their operations, measured across functions like customer service, software development, marketing, and supply chain management.
Fine-Tuning
The process of further training a pre-trained AI model on a specific, smaller dataset to specialize it for a particular task or domain, requiring far less compute than training from scratch.
Foundation Model
A large AI model trained on broad data that can be adapted to a wide range of downstream tasks — examples include GPT-4, Claude, Gemini, and Llama.
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