OpenAI, a Microsoft-owned company, has introduced a specialised business edition of its AI-powered chatbot app called ChatGPT Enterprise. This new offering is designed to provide enhanced security, privacy, and a range of features tailored to meet the demands of enterprises. Among its highlights is unlimited access to higher-speed GPT-4, extended context windows for handling longer inputs, advanced data analysis capabilities, customisation options, and more.
“We believe AI can assist and elevate every aspect of our working lives and make teams more creative and productive. Today marks another step towards an AI assistant for work that helps with any task, is customised for your organisation, and that protects your company data,” OpenAI said in a blogpost on Monday.
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The company mentioned that ChatGPT Enterprise adheres to SOC 2 compliance, upholding stringent security standards. All conversations are encrypted both during transmission and while at rest, ensuring robust privacy measures.
Notably, ChatGPT Enterprise comes equipped with a new admin console, simplifying team member management for customers. This console offers domain verification, single sign-on (SSO), and usage insights, making large-scale deployment within enterprises streamlined and efficient.
In addition, ChatGPT Enterprise includes unrestricted access to Advanced Data Analysis, formerly known as Code Interpreter. This feature empowers ChatGPT to analyse data, generate charts, solve mathematical problems, and perform other tasks, including working with uploaded files.
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The company has also addressed the performance aspect. It claimed that ChatGPT Enterprise eliminates usage caps and offers improved speed, performing up to twice as fast. With an expanded context of 32k, users can process inputs or files that are four times longer.
The company has hinted at more features in the pipeline, with a commitment to introduce them as they’re ready. Meanwhile, OpenAI is using its powerful language models, such as GPT-4, to develop a content moderation system that is both scalable and customisable. This system is expected to not only aid in content moderation decisions but also contribute to policy development and iteration, significantly reducing the timeline involved.
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