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We all want to know what’s going on with technology. What’s new, what’s about to happen, what should I be learning, what companies are looking into?
You can learn all this with the 2023 Gartner Hype Cycle for Artificial Intelligence. The Gartner Hype Cycle provides you with graphic representations of technologies and applications, and what this means for real business problems and future opportunities.
The 2023 Gartner Hype Cycle™ for Artificial Intelligence (AI) identifies innovations and techniques that are currently providing us with significant benefits while also taking into consideration the risks that come with it.
Many of you have probably been wondering what will happen with technology now, especially since the rise of large language models (LLMs) such as ChatGPT. GenerativeAI is taking over, and we all want to know more! So what has the Gartner Hype Cycle informed us?
To start, Gartner suggests that there are two sides of Generative AI:
- Innovations that will be fueled by Generative AI
- Innovations that will fuel advances in Generative AI
Generative AI will change a lot of things, and some of the areas that it will fuel innovation in are:
- Artificial General Intelligence
- AI Engineering
- Autonomic Systems
- Cloud AI Services
- Composite AI
- Computer Vision
- Data-centric AI
- Edge AI
- Intelligent Applications
- Model Operationalization
- Operational AI Systems
- Prompt Engineering
- Smart Robots
- Synthetic data
So what are the areas that will fuel advances in Generative AI? They are:
- AI Simulation
- AI trust, risk and security management (AI TRiSM)
- Causal AI
- Data Labeling and Annotation
- First-principles AI (FPAI)
- Foundation Models
- Knowledge Graphs
- Multiagent Systems (MAS)
- Neurosymbolic AI
- Responsible AI
Want to know how long it will take for these innovations to trigger and plateau. Have a deeper look into the Gartner Hype Cycle visualization below:
Image by Gartner Hype Cycle
Gartner has provided us with a new way to look at what Generative AI can do for us and how it is going to shape our future. The visualizations give us an estimated time frame on what to expect in the future. Based on what you’ve learned in this article, would you challenge anything? Let us know in the comments.
Nisha Arya is a Data Scientist, Freelance Technical Writer and Community Manager at KDnuggets. She is particularly interested in providing Data Science career advice or tutorials and theory based knowledge around Data Science. She also wishes to explore the different ways Artificial Intelligence is/can benefit the longevity of human life. A keen learner, seeking to broaden her tech knowledge and writing skills, whilst helping guide others.
