Does Tanium AEM platforms use AI? And where?

Tanium Autonomous Endpoint Management (AEM) extensively uses AI throughout its platform. The AI integration is evident in several key areas:

Real-time Cloud Intelligence: Tanium AEM leverages AI to analyze sensor trends, impact changes, and user usage patterns across millions of endpoints in real-time. It uses a special cloud-scale, multi-model stream processing architecture that can mix different analytical and AI models based on the insight needed.
Automation and Orchestration: Tanium Automate, a component of AEM, uses AI to create and execute system-wide, endpoint-level automation playbooks. These playbooks can be created with low-code and no-code experiences.
Autonomous Insights: AEM uses large language models to learn and adapt to environments, identifying and prioritizing risks based on asset criticality and recommending operator actions.
Autonomous Workflows: AI is used to automatically generate context-based workflows by learning from operation actions to understand how IT systems are organized and how various endpoints and systems are related.
Autonomous Remediation: AEM employs AI to produce high-confidence response models and can take subsequent actions without requiring intervention.
Tanium Ask: This is an AI-powered natural language interface that queries data from millions of endpoints in seconds, eliminating the need to understand complex syntax.
Tanium Guide: This feature uses AI to globally benchmark and analyze a customer's dynamic IT environment in real-time, recommending the next best actions and changes for their endpoints.

The technology's autonomous capabilities are delivered by leveraging multiple AI techniques, including natural language processing, machine learning, predictive AI, and generative AI. These AI-driven features are designed to enhance efficiency, improve customer service, and drive tangible business outcomes across Tanium AEM's platform.

What AI does Tanium AEM use? ChatGPT, etc.?

Tanium Autonomous Endpoint Management (AEM) utilizes a variety of AI technologies.

The AI technologies employed by Tanium AEM include:

Large Language Models (LLMs): These are used for autonomous insights, learning and adapting to environments, identifying and prioritizing risks, and recommending operator actions
Machine Learning (ML): Tanium has been using ML techniques to provide insights and improve its platform's capabilities
Natural Language Processing (NLP): This is used in features like Tanium Ask, an AI-powered natural language interface that queries data from millions of endpoints
Predictive AI: Used in conjunction with other AI techniques to enhance the platform's autonomous capabilities
Generative AI: Tanium mentions using newer generations of AI models, which likely includes some form of generative AI