KUALA LUMPUR, June 30 (Bernama) -- Mattermost Inc has launched “OpenOps”, an open-source approach to accelerating the responsible evaluation of artificial intelligence (AI)-enhanced workflows and usage policies while maintaining data control and avoiding vendor lock-in.
Launched at the 2023 Collision Conference, OpenOps emerges at the intersection of the race to leverage AI for competitive advantage and the urgent need to run trustworthy operations, including the development of usage and oversight policies and ensuring regulatory and contractually-obligated data controls.
It aims to help clear key bottlenecks between these critical concerns by enabling developers and organisations to self-host a “sandbox” environment with full data control to responsibly evaluate the benefits and risks of different AI models and usage policies on real-world, multi-user chat collaboration workflows.
In a statement, Mattermost Chief Executive Officer, Ian Tien said the company created OpenOps to help organisations responsibly unlock their potential with the ability to evaluate a broad range of usage policies and AI models in their ability to accelerate in-house workflows in concert.
The system can be used to evaluate self-hosted large language models (LLMs) listed on Hugging Face, including Falcon LLM and GPT4All, when usage is optimised for data control, as well as hyperscaled, vendor-hosted models from the Azure AI platform, OpenAI ChatGPT and Anthropic Claude when usage is optimised for performance.
The first release of the OpenOps platform enables evaluation of a range of AI-augmented use cases including Automated Question and Answer; Discussion Summarisation; Contextual Interrogation; Sentiment Analysis; and Reinforcement Learning from Human Feedback (RLHF) Collection.
The OpenOps framework recommends a four phase approach to developing AI-augmentations namely Self-Hosted Sandbox; Data Control Framework; Trust, Safety and Compliance Framework; and Pilot and Production.
Furthermore, the OpenOps framework includes capabilities such as Self-Hosted Operational Hub; AI Bots with Interchangeable AI Backends; Full Data Control; Free and Open Source; as well as Scalability.
-- BERNAMA
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