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OpenAI Unveils ChatGPT With Enhanced User and Interaction Memory


OpenAI is testing an option to allow ChatGPT to remember details from users’ previous conversations.

Users can ask the generative artificial intelligence (AI) chatbot to retain specific information from one exchange to the next, Bloomberg said on Tuesday (Feb. 13), citing a blog post from OpenAI. ChatGPT will also be able to automatically determine what information from a user’s conversations should be remembered, Bloomberg added.

OpenAI will initially make the features available to hundreds of thousands of free and paid ChatGPT users. The company plans to review feedback before offering it on a wider scale, the company told Bloomberg.

OpenAI will notify users if they gain access to the feature, the company said, per the report. Those with the feature will be able to delete individual details that were saved, clear all of it at once, or choose to turn off the option. Users can also ask ChatGPT what it remembers to get an idea of the information it has retained.

The new feature is OpenAI’s latest attempt to make ChatGPT more useful and personalized amid an increasingly crowded chatbot market, Bloomberg said.

Despite a growing number of rivals, OpenAI is leading the market, reportedly surpassing $2 billion in annualized revenue in December, according to a PYMNTS report last week.

Additionally, the company believes it can more than double this number next year, citing strong interest from business customers who want to use its generative AI tools in the workplace, according to a Financial Times report.

The company also has its sights set on boosting the global supply of computer chips that power its software.

CEO Sam Altman is reportedly pitching a multitrillion dollar project to investors, including the government of the United Arab Emirates, to raise funds for an initiative that would increase the planet’s chip-building capabilities and AI abilities, PYMNTS reported Sunday (Feb. 11).

Altman’s goal of reducing the scarcity of AI chips used to train large language models (LLMs) could mean raising between $5 trillion to $7 trillion, a staggering figure more than the market capitalization of Apple and Microsoft combined.