On
November 30, a tool called ChatGPT was released on the internet. It created
quite
a stir especially among the artificial intelligence (AI) crowd because
this tool
‘knew’
every topic under the sun; it could answer questions and carry on a
conversation.
Experts in the AI community call this an epochal moment, stressing
how
powerful ChatGPT is. This tool interacts with humans in natural language
and
is impressive because aside from answering general queries, it has many other
functions.
ChatGPT has been developed by OpenAI, which is a research institute
and
company that focuses on developing artificial intelligence technology
responsibly and safely. It was founded in 2015 by a group of entrepreneurs and
researchers,
including Elon Musk, Sam Altman, and Greg Brockman.
Language
models
ChatGPT
is much more than a chatbot. For example, you can ask it to write a
program
or even a simple software application. It can also do creative tasks such
as
writing a story. It can explain scientific concepts and answer any question
that
needs
factual answers. ChatGPT is what is called a Language Model, rather than a
chatbot.
A language model is software that prints out a sequence of words as
output
that are related to some words given as input with appropriate semantic
relation;
in practical terms, it means that it can perform tasks like answering
questions
and carrying on a conversation with humans. It is often used in natural
language
processing (NLP) applications, such as speech recognition, automatic
translation,
and text generation.
The
Development ofChatGPT
ChatGPT
follows a generation of language models that were released by OpenAI
in
2018. In 2018, OpenAI released the Generative Pre-Training (GPT)
language
model. With the transformer technique mentioned above, GPT was
improved,
and “Generative Pre-trained Transformer 2” or GPT-2 was released in
2019.
GPT-3 with even more sophisticated neural networks was launched in 2020.
In
early 2022, GPT3.5 was released and ChatGPT is a successor to GPT3.5. Each
successive
generation is more advanced than its predecessor. For example, GPT-3
was
trained with 175 billion parameters. These large language models have looked
at
almost all text available on the internet and many other text documents,
thereby
making
them highly informed.
The
Conversational AI
The
accuracy of ChatGPT or any language model can be measured using standard
techniques.
One such technique is “Recall-Oriented Understudy for Gisting
Evaluation”
or the ROUGE metric which compares ChatGPT’s output of content
against
a standard expected content and measures the overlap as a success
percentage.
For language models like GPT that are also used in translation,
another
metric called the BLEU metric (Bilingual Evaluation Under Study) is
employed;
this metric compares overlap in translated content with a standard
