computational linguistics

Shattering Sentences: The Art of Tokenization

6 min read

Before any AI can understand language, it must first shatter sentences into pieces through a process called tokenization. This crucial first step is far more complex than it seems, presenting unique linguistic puzzles across different languages, from English contractions to German compound nouns and Chinese text that has no spaces. This invisible labor, where computer science meets linguistics, is the foundational work that powers our entire digital world.

AI Future Evolutionary Linguistics Computational Linguistics

Speaking to Themselves: The Unsettling Rise of Inter-AI Languages We Can’t Understand

6 min read

When two AI systems are tasked to work together, they often develop their own optimized, private language to communicate more efficiently—a language we can’t understand. This phenomenon of emergent AI communication offers a fascinating and unsettling look into non-human “cognition.” By exploring these alien tongues, we confront profound questions about the nature of language and the future of our relationship with artificial intelligence.

AI Computational Linguistics

The Unseen World of Linguistic Annotation: The Human Hands Behind AI Language Models

6 min read

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Before an AI can understand language, a human has to teach it. This work is done by linguistic annotators, the unsung heroes who manually tag text with grammatical and semantic information, creating the training data for models like GPT. This intricate process of “treebanking” and resolving linguistic ambiguity forms the very foundation of the AI revolution.

Technology Linguistics Future Computational Linguistics

The Billion-Word Crystal Ball: How Corpus Linguistics Predicts the Future of Language

6 min read

Ever wonder how new words like ‘rizz’ make it into the dictionary or why grammar rules seem to change over time? The answer lies in corpus linguistics, a fascinating field that uses massive, billion-word databases to analyze language as it’s actually used. This data-driven approach not only chronicles our language’s past but can even help predict its future.

History Linguistics Writing Computational Linguistics

The World’s Most Mysterious Book: Can Linguistics Ever Decipher the Voynich Manuscript?

6 min read

Filled with otherworldly plants and an indecipherable script, the 15th-century Voynich Manuscript has stumped cryptographers for over a century. Linguistic analysis reveals that the text mimics the statistical patterns and structure of a real language, yet it corresponds to no known tongue on Earth. Is it a lost language, a brilliant cipher, or the world’s most elaborate and beautiful hoax?

AI Psycholinguistics Computational Linguistics

The ELIZA Effect: Why We Talk to Chatbots Like They’re Human

6 min read

Have you ever found yourself saying “please” and “thank you” to a chatbot or voice assistant? This is the ELIZA effect, our tendency to unconsciously attribute human-like intelligence and empathy to computer programs that mimic conversation. This post dives into the psychology behind this phenomenon, its origins with a 1960s “digital therapist,” and the clever linguistic tricks developers use to make machines feel more human.

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Building Languages for Machines: The Linguistic Principles Behind Programming Languages

6 min read

We think of Python or Java as “computer languages,” but they are fundamentally constructed languages built on core linguistic principles. This article explores the hidden grammar of code, from the strict rules of syntax to the unambiguous meaning of semantics. Discover how the same principles that govern human communication are used to build the digital world we rely on.

AI Linguistics Computational Linguistics

The Ghost in the Machine: How Linguists Teach Computers to Understand Ambiguity

6 min read

Ever wonder how your phone knows you mean the band Queen, not a monarch? This post explores the linguistic challenge of ambiguity and the clever statistical methods, like n-grams and vector semantics, that linguists use to teach machines how to make educated guesses about human meaning. It’s a deep dive into the “ghost in the machine” that powers our everyday AI interactions.