Over the past decade, Artificial Intelligence (AI) technology has evolved into the linchpin of innovation, catalyzing significant transformations in various sectors, including health, finance, and automotive. AI’s success in facilitating decision-making, data analysis, and automation has positioned it as a pivotal element in the technological landscape.
A recent advancement in AI development is the concept of “Hypermodal AI.” Hypermodal AI combines various types of sensor data and multimodal information, such as text, images, sound, and physical sensor data, with advanced AI technology. This integration empowers AI to comprehend and respond in deeper and more complex ways than ever before. In this article, we delve into the intricacies of Hypermodal AI and how it aids businesses in dealing with complexity.
What is Hypermodal AI?
Hypermodal AI is a concept that encompasses the creation of AI systems capable of comprehending and integrating multiple sensory data types or modalities. These modalities include text, images, sound, video, sensor data, and information from diverse sources. The core idea behind Hypermodal AI is to craft an AI system that is more versatile and possesses a profound understanding of the “real world.” This enables AI to process and amalgamate information from multiple modalities to yield a richer understanding of specific situations or environments.
In the realm of Hypermodal AI, Dynatrace stands as one of the pioneers, introducing the first Hypermodal AI solution. By amalgamating data from various source modalities, Dynatrace assists companies in optimizing their operations and gaining profound insights for informed decision-making.
Dynatrace Unveils Davis AI as the Industry’s First Hypermodal AI Solution
Dynatrace has introduced Davis AI as the industry’s inaugural Hypermodal AI solution. This innovative AI platform integrates predictive AI, causal AI, and generative AI techniques to enhance efficiency across all facets of operations, security, and business development.
Davis AI can handle a wide array of data modalities, including metrics, traces, logs, behavior, topology, dependencies, events, and other data types. This approach equips Davis AI to furnish precise predictions and in-depth insights tailored to business requirements.
Here, we succinctly outline some of the capabilities provided by Dynatrace Davis AI:
Davis Predictive AI
Capable of dynamically foreseeing future behavior based on historical data patterns.
Davis Causal AI
Harnesses real-time business data to offer accurate and automated solutions. This is instrumental in preempting issues, conducting thorough root cause analyses, and seamlessly automating risk mitigation.
Davis CoPilot Generative AI
Equipped with predictive and causal AI technologies, CoPilot Generative AI can automatically offer recommendations for crafting workflows and integrated dashboards. This empowers users to navigate and complete tasks more efficiently using natural language.
Observability and Security with Dynatrace Davis AI
Source: dynatrace.com
In addition to the previously mentioned capabilities, Dynatrace Davis AI offers a powerful combination of AI techniques to tackle complex observability and security challenges. This platform seamlessly integrates predictive and causal AI models, empowering users to predict events and pinpoint root causes with precision and efficiency.
Predictive AI Models
Davis AI can foresee future behavior based on historical data patterns, enhancing proactive responses to potential issues.
Causal AI Models
Leveraging real-time data, these models provide accurate and intelligent answers, vital for preventing problems and automating risk control.
Davis CoPilot Accelerates Onboarding
Davis CoPilot, an integral component of Dynatrace Davis AI, not only offers coding suggestions for workflow automation but also expedites the onboarding process. Users of varying technical backgrounds can quickly optimize the platform for improved business performance and security.
Example: How Dynatrace Davis AI Works with Hypermodal AI
Let’s explore the steps that Dynatrace Davis AI takes to complete a specific task.
1. Understanding the Question
The initial step involves comprehending the context and meaning of the questions asked.
2. Identifying User Sessions and Required Services
Smartscape tools identify user sessions with conversion metrics and pinpoint the services necessary for the user’s journey through the system topology.
3. Service Behavior Prediction and Monitoring
Through historical data analysis, the solution predicts how services will perform under different loads and identifies services nearing capacity limits using topology metrics.
4. Historical Problem Analysis and Corrective Action
The AI identifies services that caused problems in the past and uses this data to create dashboards and queries. Subsequently, it determines the necessary corrective actions based on existing findings, providing real-time solutions to emerging issues.
How Dynatrace Davis AI Benefits Industries
1. Root Cause Analysis
Davis AI automatically detects user-facing issues, assesses their impact on the business and related users, and precisely identifies the root cause using context such as topology, transactions, and code-level information.
2. Natural Language Queries
Dynatrace Query Language (DQL) enables data exploration, pattern identification, anomaly detection, statistical modeling, and more based on data stored in Dynatrace Grail.
3. Auto-coded Workflows
Davis CoPilot simplifies the creation of workflows using natural language input. It streamlines automation in ChatOps, DevOps, and ITSM environments.
4. Predictive Operations
It allows for the automatic prediction and identification of unusual issues (anomalies) within the system. Afterward, Davis AI can generate a report regarding the problem.
The actions taken can vary, ranging from notifying the team about the issue to executing an automated process for its resolution.
5. Automatic Quality Checks
Dynatrace Site Reliability Guardian uses ML technology, anomaly detection, and Root Cause Analysis (RCA) to facilitate code quality inspection during the delivery process.
6. AI-Based Application Security
Automatically assesses risks, detects threats, and recommends remediation strategies. It simplifies security analysis using natural language queries.
7. Visual Analytics from Natural Language
Utilizes dependency and topology data to create dashboards and notebooks based on natural language input.
8. AI Assistance for Platform Usage
Davis CoPilot leverages a custom-designed Large Language Model to boost productivity, streamline onboarding, and democratize open access for all organization members.
Central Data Technology: Your Trusted Dynatrace Partner in Indonesia
Central Data Technology (CDT), an esteemed partner of Dynatrace in Indonesia, is dedicated to delivering comprehensive IT solutions tailored to your specific business requirements. Our professional, experienced, and certified IT team is committed to guiding you through every stage, from consultation and deployment to management and post-sales support. With our assistance, you can seamlessly implement the Dynatrace Davis AI solution without the hassle of trial and error.
Interested in harnessing the power of Dynatrace Davis AI for your business? Reach out to us today by clicking the link.
Author: Ary Adianto
Content Writers CTI Group
