Tag: GPT-4

  • OpenAI | Delivering High-Performance Customer Support

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    Decagon, powered by OpenAI’s models like GPT-3.5 and GPT-4, provides fast and flexible automated customer support, enabling companies to handle inquiries with high accuracy globally. By quickly evaluating and integrating new models, Decagon maintains efficient support workflows, exploring future voice-enabled interactions to advance customer service automation. Source: Here

  • Arco Educação | OpenAI　Arco Educação leverages GPT-4 to enhance education in Brazil

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    Arco Educação, Brazil’s largest educational operating system, is partnering with OpenAI to create tools that allow teachers to focus on student learning. By using GPT-4, Arco has achieved 90% accuracy in generating and assessing pedagogical content in Brazilian Portuguese, improving both efficiency and educational quality. The “Teacher Assistant” tool helps teachers create customized lesson plans,…

  • Ada｜Using GPT-4 to Deliver a New Customer Service Standard

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    Ada, a customer service automation platform, has utilized OpenAI’s GPT-4 to shift from the traditional “containment rate” to a new metric called “resolution rate,” which measures how well customer queries are resolved. With this approach, Ada has significantly improved service quality, achieving resolution rates above 80% for some clients. Additionally, Ada has leveraged OpenAI’s fine-tuning…

  • New Compliance and Administrative Tools for ChatGPT Enterprise

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    OpenAI, July 18, 2024 OpenAI announced new tools to support managing compliance programs, enhancing data security, and securely scaling user access for ChatGPT Enterprise. The new tools include the Enterprise Compliance API and SCIM integration, along with expanded GPT controls. These enhancements aim to help enterprise customers in regulated industries meet logging and audit requirements…

  • Finding GPT-4’s mistakes with GPT-4 | OpenAI

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    OpenAI has developed CriticGPT, a model based on GPT-4, to catch errors in ChatGPT’s code output. This model helps AI trainers spot mistakes, improving error detection by 60%. The model will be integrated into the RLHF labeling process, and future tools will aim to handle more complex tasks. Source (Published: June 27, 2024)