"Al-Masry Al-Youm, a daily newspaper in Egypt, built a chatbot to help its readers navigate its archive of over 3 million stories. Key to the pilot was partnering with Miso.ai, a third-party vendor that offers "AI search engine" products. Al-Masry Al-Youm wanted to move beyond basic keyword search on its site, and the Miso team was able to integrate a combination of semantic search algorithms and generative AI into its experimental chatbot."
"Readers could ask the chatbot simple questions and get responses that linked to Al-Masry Al-Youm's past articles. First, the team created a "sandbox" to test the chatbot on 100,000 articles, before widening it to cover the publication's entire archive. Importantly, Miso was able to help the publication fine-tune its models for the Arabic language and customize its UI to read from right to left."
AI Launchpad engaged 16 major newsrooms across Europe, the Middle East, and Africa from June to December. Many participants began exploring generative AI back-end tools such as headline generators and automated taggers to streamline editorial workflows. Several newsrooms pivoted to build conversational AI chatbots for readers to boost engagement and enable new archive interactions. Some chatbots also handled customer service queries, reducing staff burden. Al-Masry Al-Youm partnered with Miso.ai to create a right-to-left Arabic chatbot, testing on 100,000 articles before scaling to an archive of over three million stories.
Read at Nieman Lab
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