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Bhavish Aggarwal's Krutrim AI chatbot says it was created by OpenAI; company replies...

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Jaya Vishwakarma
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Krutrim AI chatbot says it was created by OpenAI

Imagine this: You're chatting with a new AI buddy, Krutrim, thinking it's the latest tech marvel from India. But then, out of the blue, it drops a bombshell - "Actually, I was made by OpenAI." Wait, what? That's the wild ride users got with Krutrim, Ola's new AI, which got a bit mixed up about who made it.

Bhavish Aggarwal founded India's fastest and only AI unicorn, Krutrim recently launched the beta version of AI chatbot 'कृत्रिम Assistant', which some people called similar to Sam Altman-led OpenAI's ChatGPT.

Following this, Many people started trying Krutrim AI's chatbot. Among these Raghav Arora took to X (formerly known as Twitter), to share a screenshot of the AI stating it was an OpenAI creation.

"Something seem super fishy @KrutrimAI says it was created by OpenAI," Arora wrote. 

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This unexpected response sparked debates over whether Krutrim was merely a "wrapper" for ChatGPT and using OpenAI's responses as its own. It's worth noting that Krutrim recently turned unicorn after raising $50 million in funding at a valuation of $1 billion.

Such implications wasn't limited to Raghav, many other users also shared the same response which they received from Krutrim AI.

Responding to this, Krutrim acknowledged the issue, attributing it to a "data leakage" from an open-source dataset used during the language model's fine-tuning process. 

"Hey, thanks for bringing this to our notice. We were able to identify the root cause of a data leakage issue from one of the open-source datasets used in our LLM fine-tuning. As a result, some users saw a message "I am created by OpenAI". The dataset was immediately removed," the company wrote.

Despite this quick fix, the incident has left lingering doubts about the methods employed in developing Krutrim AI. The startup had previously boasted about its model being trained on a vast dataset of two trillion tokens, yet specifics about its research, training methods, and the nature of its dataset remained undisclosed.

Pratik Desai, the founder of KissanAI, offered advice on addressing the attribution error, suggesting techniques like Differential Privacy Optimization (DPO) or replacing OpenAI mentions with Krutrim identifiers.

"Unsolicited advice to @Krutrim team. If you're fine-tuning an OSS base model, use DPO to remove OpenAI mentions. If you're doing it from scratch, a simple ‘cat’ command can replace all OpenAI mentions in a dataset with Krutrim," Desai wrote.

In response to Desai’s advice, Krutrim acknowledged the issue and provided insights into the root cause.

"Hey Pratik, You are correct about the approach. Thanks for sharing this, it is very helpful and will help improve our product. We investigated the issue and found the root cause to be a data leakage issue from one of the open-source datasets used in our LLM fine-tuning," Krutrim wrote in response to Desai's advice. 

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