Natural Language Processing

The words people use every day in conversations or books are called 'natural language.' While computers store letters as numeric codes, those codes alone don't explain what words actually mean or how they relate to one another.

To help a computer read, we must first break sentences into bite-sized pieces. For example, a sentence like 'I ate a delicious apple' is sliced into tokens (words, subwords, or punctuation marks), and each token receives a unique ID number. The exact slicing method depends on the model.

Next, the computer maps each word's meaning onto numerical coordinates. This technique is called embedding. By doing this, the computer can mathematically calculate the distance and relationships between words—learning that 'apple' and 'pear' are fruits that belong close together, while 'airplane' sits far away.

Thanks to these numerical coordinates, computers can treat human sentences like vast mathematical formulas, computing their meaning quickly and accurately.

Looking up words in a dictionary is not enough to truly understand human speech. Consider the word 'bank' in 'I sat on the river bank' versus 'I deposited money in the bank.' The spelling is identical, but the meanings are completely different.

Older rule-based systems relied on programmers manually entering thousands of grammatical rules. But human language has endless exceptions, slang, and evolving buzzwords, so this approach soon hit a wall.

Modern NLP advanced by using deep neural networks to look at the entire surrounding context at once. It calculates the statistical probability of how words connect across a whole sentence.

This allows computers to go far beyond single words, capturing the flow of an entire paragraph, spotting metaphors, and inferring subtle nuance and intent. Still, sarcasm and delicate irony can occasionally trip them up.

NLP springs into action the moment you wake up and ask your smartphone's voice assistant for the weather. It turns your voice into text, figures out your intent to check the forecast, and crafts a natural spoken response.

Machine translation that turns a foreign web page into fluent English at a single click, and summarization tools that condense long articles into three bullets, are also powered by this technology. Email services rely on it too, scanning sentence patterns to filter out spam.

Today's conversational AI chatbots are the product of massive NLP models trained on vast seas of text data. As computers master the art of understanding context and writing like people, tools from search engines to customer service are evolving at lightning speed.