Scientists trained an AI model using an IBM quantum computer — and it answered questions correctly that the base model couldn't

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Summary

Researchers used an IBM quantum computer to reduce uncertainty in an AI model, achieving the first demonstration of quantum enhancement in a pretrained large language model, allowing it to answer questions correctly where the base model failed.

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# Scientists trained an AI model using an IBM quantum computer — and it answered questions correctly that the base… Source: [https://www.livescience.com/technology/quantum/scientists-trained-an-ai-model-using-an-ibm-quantum-computer-and-it-answered-questions-correctly-that-the-base-model-couldnt](https://www.livescience.com/technology/quantum/scientists-trained-an-ai-model-using-an-ibm-quantum-computer-and-it-answered-questions-correctly-that-the-base-model-couldnt) Researchers have developed a method to reduce uncertainty in[artificial intelligence](https://www.livescience.com/technology/artificial-intelligence/what-is-artificial-intelligence-ai)\(AI\) systems by tapping into the power of[quantum computers](https://www.livescience.com/quantum-computing)\. They say their work represents the first demonstration of "quantum enhancement" in a production\-scale, pretrained large language model \(LLM\)\. One of the key metrics used to measure the quality and capabilities of AI systems such as Anthropic's Claude, OpenAI's ChatGPT and similar services is a unit known as "perplexity" — often expressed as PPL\. This measures a system's general ability to properly predict the next word in a sentence or sequence of words\. Get the world’s most fascinating discoveries delivered straight to your inbox\.

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