LING 1010 Language and Mind: Artificial Intelligence and Human Language

Flashcards covering key concepts from the LING 1010 lecture on Artificial Intelligence and Human Language, including definitions of chatbots, LLMs, cognitive science, and concerns about AI.

What is a chatbot?

A computer program that simulates human conversation by returning a text response into a prompt input by the human user.

Which historical chatbot was created in the 1960s to simulate conversation with a therapist?

ELIZA.

How do recent chatbots, like ChatGPT, produce seemingly novel sentences?

They are based on Large Language Models (LLMs), which approach language production differently from symbolic rules.

What is Cognitive Science?

The interdisciplinary field that scientifically investigates information processing in the human brain, including perception, reasoning, problem-solving, language, and memory.

What is the specialized branch of Cognitive Science that focuses on language?

Linguistics.

What is the Classical Computational Theory of Mind?

A school of thought in Cognitive Science where the human mind is analogous to a digital computer, carrying out rule-governed computations on symbolic representations.

What is Connectionism in Cognitive Science?

A school of thought where the human mind is seen as a product of the human brain, with models inspired by neuronal wiring where information is distributed in neural networks without explicit symbols or rules.

What is Artificial Intelligence (AI)?

An engineering project to build computers and machines that are intelligent, typically by carrying out tasks like reasoning, problem-solving, language, and decision-making.

What branch of Artificial Intelligence specifically deals with language?

Natural Language Processing (NLP).

What is a language model?

Any NLP program that can take a sequence of words as input and predict the next word.

What does GPT stand for in the context of Large Language Models?

Generative Pre-trained Transformer.

How are Large Language Models (LLMs) trained?

They are trained on large datasets using artificial neural networks (ANNs), adjusting numerical 'weights' (parameters) to produce better outputs, rather than being symbolically programmed.

What is a significant consequence of the immense scale of LLMs like GPT-4?

Experts are not yet able to fully interpret their inner workings, making them largely 'black boxes'.

How do researchers test the linguistic abilities of LLMs?

Through benchmarking, such as using resources like BLiMP (The Benchmark of Linguistic Minimal Pairs), and testing based on 'surprisal'.

Why is it unclear whether LLMs ascribe any meaning to the text they generate?

They are typically trained only on texts and lack human-like conceptual grounding, leading some to argue 'no actual language understanding is taking place'.

What is a key difference between human language acquisition and LLM training?

LLMs are trained on datasets too vast for any human to process in a lifetime, vastly exceeding the word tokens heard by children who acquire language by age 6.

What happens when language models are restricted to human-scale data quantities?

They generally fail to reach human-level accuracy.

What are some human advantages in language acquisition compared to typical LMs?

Environmental sensorimotor stimuli, inter-agent interaction, environmental interaction, and prosody.

What are some model advantages in language processing compared to humans?

Quantity of text, text domain (edited writing), punctuation, numerical precision, and working memory capacity.

What is the 'stochastic parrot' view regarding LLMs' creativity?

That an LLM haphazardly stitches together sequences of linguistic forms observed in its training data according to probabilistic information, without reference to meaning.

What is a significant danger associated with LLMs parroting text from the internet?

The potential for LLMs to parrot back biases and prejudices found in their training data, with no reliable techniques for steering their behavior.

What course is recommended for learning about language models and related concepts?

LING 3000Q Introduction to Computational Linguistics.