ChatGPT – sentient AI or singularity. How close are we?

ChatGPT – sentient AI or singularity. How close are we?

An expert from RMIT University is available to talk to media about what makes ChatGPT more advanced than other AI language models and whether it’s nearing sentience.

Kok-Leong Ong, Director, Enterprise AI and Data Analytics Hub (03 9925 4147 or kok-leong.ong2@rmit.edu.au)

Topics: ChatGPT, GPT-3, artificial intelligence, AI, technology 

“ChatGPT is a large language model (LLM), however, its popularity is way further ahead of other LLMs because of its human-like responses.  

“ChatGPT in some instances is said to be sentient as it features attributes of human traits by answering follow-up questions, demonstrating complex scenarios with examples, and notifying users about inappropriate requests.

“On a technical level, ChatGPT is a non-sentient LLM that synthesizes information by mimicking human language, compared to GPT-3 which is trained on large text data including books, articles and websites. 

“ChatGPT’s unanticipated popularity could also be attributed to its super intelligent AI capabilities beyond human comprehension.  

“Due to the conversational design, ChatGPT exhibits human-like features. While GPT-3, despite having high volumes of data, seem less interactive and rather provide straightforward summaries for the queries.  

“Also, GPT-3 works with 175 billion parameters that require extensive computational resources and suitable for high-power devices. On the other hand, ChatGPT only requires 117 million parameters, therefore it is lightweight, device friendly and highly accessible.

“While ChatGPT is non-sentient, there is widespread scepticism about the conversational and argument building attribute of ChatGTP as this could lead to self-learning AI.   

“To create a super-intelligent AI, sentience is not a necessary condition. This leaves us to believe that singularity of technology might be edging closer but there is more work to be done.”

Kok-Leong Ong is a Professor of Business Analytics at RMIT University. His research focuses on analytics and machine learning translation into practice and the development of new techniques as required to meet individual business needs. He is also the Director of the Enterprise AI and Data Analytics Hub, a research centre focusing on using AI and Data Analytics to overcome business problems.

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Interviews: Kok-Leong Ong, 03 9925 4147, kok-leong.ong2@rmit.edu.au  

General media enquiries: RMIT Communications, 0439 704 077 or news@rmit.edu.au

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