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Cornell University Discovers a Huge Threat at the Core of ChatGPT

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Summary

Cornell University has recently discovered a huge threat at the core of ChatGPT, a popular Generative AI (GenAI) solution. This discovery has raised privacy concerns and has given researchers insight into one of the most unknown components of frontier AI models today. Embeddings are ubiquitous elements in today's AI and have been used to express non-numerical data in a way that machines can understand it. This discovery has been shared in the weekly newsletter, TheTechOasis.

Q&As

What is the threat posed by the GenAI solution?
The threat posed by the GenAI solution is a potential privacy concern.

What is the purpose of the vector database for GenAI models?
The purpose of the vector database for GenAI models is to provide the model with "long-term memory" and context required to answer the user inquiry.

What is the ubiquitous element of today's frontier AI?
The ubiquitous element of today's frontier AI is embeddings.

How did AI researchers solve the problem of non-numerical data?
AI researchers solved the problem of non-numerical data by expressing the information from the world so that machines can understand it using '1s' and '0s'.

What is the purpose of the TheTechOasis newsletter?
The purpose of TheTechOasis newsletter is to keep readers up-to-date with the frenetic world of AI and to provide content not present in any other platform, including Medium.

AI Comments

👍 This article provides a great insight into the core of chatGPT and the advances in generative AI. The discovery that Cornell researchers have made is remarkable and provides a great understanding of the complexities of AI.

👎 The article fails to provide any practical solutions to the memory problem mentioned. It also does not address any possible privacy concerns that may arise from the discovery.

AI Discussion

Me: It talks about the potential privacy concerns with using chatGPT, which is a type of Generative AI. Cornell University researchers discovered that the vector databases used to enable the model to have long-term memory can be a huge threat to privacy.

Friend: That's alarming. What kind of privacy concerns are we talking about?

Me: Well, the article suggests that the vector databases used by the model could potentially be accessed and exploited by malicious actors, leading to potential data breaches or unauthorized access to personal information. In addition, it also points out that the use of embeddings at the core of chatGPT models could cause further privacy issues due to the fact that the data stored in the vector databases is not secured and can be accessed by anyone.

Action items

Research the implications of the Cornell University discovery and the potential privacy concerns it raises.
Explore the use of embeddings in AI models and their potential applications.
Subscribe to TheTechOasis newsletter to stay up-to-date with the latest developments in AI.

Technical terms

Generative AI (GenAI): A type of artificial intelligence that is able to generate new data from existing data.
Vector Database: A database that stores data in the form of vectors, which are mathematical objects that can represent points in space.
Embeddings: A set of numerical values that represent a particular piece of data, such as a word or phrase.
Classical Computers: Computers that use binary code (1s and 0s) to represent data.