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Language and Cognition

Language and Cognition

Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.

Language

Language

Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...

Components of Language

Components of Language

Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.

Language Development

Language Development

Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...

Higher Mental Functions of the Brain: Language

Higher Mental Functions of the Brain: Language

Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...

Translation

Translation

Lesson: Translation
Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of...

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Related Experiment Video

Updated: Dec 22, 2025

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

The Language of Innovation.

Andrea Tacchella^1,2, Andrea Napoletano^2,3, Luciano Pietronero^3,4

¹European Commission, Joint Research Centre (JRC), Seville, Spain.

|May 1, 2020

Summary

Predicting technological innovation is challenging. This study uses self-supervised learning and natural language processing techniques to forecast innovative patents by analyzing technology associations, outperforming standard methods.

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Area of Science:

Data Science
Innovation Studies
Intellectual Property Analysis

Background:

Innovation prediction is difficult due to its novel nature, precluding traditional supervised learning.
Patents represent a rich source of information on technological advancements and their associations.

Purpose of the Study:

To develop a novel strategy for predicting innovative patents.
To define innovations as previously unseen technology combinations and leverage self-supervised learning.

Main Methods:

Treating patent technological codes as a vocabulary within an evolving language corpus.
Employing Natural Language Processing techniques to embed technologies in a high-dimensional space.
Utilizing proximity in this embedding space as a predictor for innovation events.

Main Results:

Proximity in the learned technological space effectively predicts specific innovation events.
The proposed method demonstrates superior performance compared to standard link-prediction metrics.
Analysis reveals complex dynamics and patterns in the success of patented innovations.

Conclusions:

Self-supervised learning and NLP offer a new paradigm for understanding and forecasting innovation.
The embedding approach provides a powerful tool for analyzing technological relationships and predicting future breakthroughs.
This research opens new avenues for innovation analytics and strategic applications.