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AI Innovation

Gartner Hype Cycle™ for Artificial Intelligence 2022

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The Gartner Hype Cycle™ for Artificial Intelligence (AI) 2022 identifies the most important innovations in AI technologies and techniques. These are innovations that go beyond everyday AI.

„Notably, the AI Hype Cycle is full of innovations expected to drive high or even transformational benefits. Pay particular attention to innovations expected to hit mainstream adoption in two to five years, including composite AI, decision intelligence and edge AI. Early adoption of these innovations can drive significant competitive advantage and business value and ease problems associated with the fragility of AI models.“

Afraz Jaffri, Director Analyst at Gartner

The AI innovations outlined in the Gartner Hype Cycle™ 2022 represent priorities in four main categories:

  • Data-centric AI: When developing AI solutions, the optimization of AI models plays a very key role. Data-centric AI should focus on data preparation, enrichment, and selection. The systematic generation of synthetic data is also a central component of data-centric AI, since in many cases the relevant data are not initially available.
  • Model-centric AI: Even though data-centric AI is becoming more important, AI models are still not to be neglected. For the desired results, these must be further developed and optimized. In particular, this includes composite AI, generative AI, casual AI or deep learning.
  • Application-centric AI: AI engineering, decision intelligence, operational AI systems, AI cloud services, natural language processing (NLP), intelligent applications or computer vision are innovations to be assigned to this category.
  • Human-centered AI: Within the scope of this category, innovations regarding the aspects of ethics, risk and responsibility of AI, among others, are concerned.

It is now widely accepted that artificial intelligence (AI) can help solve business processes. However, often one technology or innovation alone cannot solve the problem. Rather, a well thought-out interplay of multiple approaches must be brought into closer consideration. We also made this experience very early on with SonarBox in the context of customer projects and transferred the principles to SdbHub as well.

This interaction has been officially named Composite AI by Gartner in the Gartner Hype Cycle™ for Artificial Intelligence 2020. We use the term Hybrid AI for this purpose. Hybrid AI is generally understood to be the combination of techniques from machine learning with methods from the field of expert systems.

At its core, it is about finding answers to complex business processes. Complexity doesn’t just require the use of multiple technologies. Rather, it is to strive for a functioning interaction of Machine Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) and other methods.

Classification of SdbHub

At Datalyxt, we develop solutions using various AI methods. The focus is on reducing the workload of employees. We refer to these types of applications as digital assistants or intelligent applications.

The Gartner Hype Cycle™ helps to understand other perspectives and create possible uniform terminology. We are happy to discuss these with our customers. After all, many clients dealing with AI are very familiar with the Gartner Hype Cycle™.

Like many AI companies, each phase of solution development at Datalyxt also has its own unique focus. Subordinate to the human and application aspects are the other categories of data and models. While the data aspect is given special attention at the beginning of the implementation, this focus shifts to the corresponding models and their optimization as the implementation progresses.

SdbHub is an intelligent application that has already been available to companies as a cloud solution since the end of 2019. It integrates many of the innovations mentioned in the Gartner Hype Cycle™. It confirms that we recognized market trends in good time and have a head start of several years here. There are two main reasons for this: Customer proximity and the urge to want to solve tomorrow’s problems today.