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Publisher Day 2024: The road ahead for scholarly publishing

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In the lead up to the London Book Fair, on Monday 11th March we held our annual Digital Science Publisher Day. Guided by the overarching theme of ‘The Road Ahead’, the in-person event provided an opportunity to explore what the future roadmap for scholarly publishing may hold. It was an action-packed day for the publishing community, with keynotes, panel discussions, and plenty of networking!  After a welcome and introduction from Digital Science’s MD of Publisher Sales, Helen Cooke , we kicked off the day with a keynote from Mark Hanhel , our VP of Open Research. Mark shared where he predicts experimentation will lead in the ever-changing global academic publishing landscape, and what Digital Science can do to support publishers with data, tools and insights.  Mark Hahnel, VP of Open Research, speaking at Digital Science Publisher Day. Following Mark’s keynote, we had a series of lightning talks to share product updates and roadmaps for our publisher solutions. Amye Kedall , VP o

International Research Awards on New Science Inventions

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  News: DeepMind AI with built-in fact-checker makes mathematical discoveries International Research Awards on New Science Inventions Visit:  nesin.sciencefather.com The AI company DeepMind claims it has developed a way to harness the creativity of chatbots to solve mathematical problems while filtering out mistakes Visit Our Website:  https://new-science-inventions.sciencefather.com/ Conference Nomination:  https://x-i.me/nesiabst2 Award Nomination:  https://x-i.me/abdunews Contact us:  nesinenquiry@sciencefather.com Google DeepMind claims to have made the first ever scientific discovery with an AI chatbot by building a fact-checker to filter out useless outputs, leaving only reliable solutions to mathematical or computing problems. Previous  DeepMind  achievements, such as using AI to  predict the weather  or  protein shapes,  have relied on models created specifically for the task at hand, trained on accurate and specific data. Large language models (LLMs), such as GPT-4 and Google’