The Key AI Technologies
- [Sydney Harbor Bridge and Opera House, Sydney, Australia - Photologic]
- Overview
Artificial intelligence (AI) has many sub-technologies and applications, from biometrics and computer vision to smart devices and self-driving cars. These AI technologies, coupled with abundant data, computing power, and cloud processing innovations, have fueled dramatic growth in AI adoption.
Companies now have access to unprecedented amounts of data, including dark data they didn’t know they had. It turns out that these treasure troves are a boon to the development of AI.
Although AI has long been recognized as a source of business innovation, it can only add value if used correctly. To do this, we need to understand the core technology behind the AI process.
However, AI is not the same thing. It is a combination of technologies that enable machines to perceive, understand, act and learn with human-like intelligence. The field of AI includes technologies such as machine learning (ML), natural language processing (NLP), and computer vision.
- Highly Efficient AI is Vital to the World
As the energy demands of AI increase, advances in hardware and software are necessary for sustainable growth. As AI becomes increasingly integrated into daily life and global infrastructure, the need to make these systems energy efficient becomes ever more urgent.
High-performance AI is not just optional; This is the only way forward if we are to sustainably realize the potential of AI. That means rethinking everything from the chips that power AI to the software that runs on them, ensuring workloads are processed where they make the most sense - whether in the cloud or on-premises. Specialized hardware, optimized software, and innovative frameworks are all at the core of reducing AI’s energy footprint.
- The Core AI Technologies
- Edge AI
- Enterprise LLM
- Digital Twins
- AI-Augmented Development
- Artificial Intelligence Agent (AI Agent)
- Hybrid AI
- 6G and low-orbit satellites
- System integration optimized for large language model deployment
- AI trust, risk and security management
- False message detection
- The Key Components of AI Applications
Artificial intelligence applications typically involve data, algorithms, and human feedback. Ensuring that every component is properly built and validated to develop and implement AI applications is critical.
- Data
- Algorithms
- Human Feedback
