The number of internet-connected devices (IoT) is exploding, creating a vast network of smart devices. Artificial intelligence (AI) is playing an increasingly important role in analyzing the data from these devices, leading to the rise of AIoT. This combination is having a big impact in areas like wearables, smart cities, and smart homes. Processing data at the edge of the network, closer to where it's generated, is becoming increasingly important due to the vast amount of data collected by these devices. This approach reduces latency and improves performance. AI is being used at the edge to filter data and identify important signals. As the number of connected devices continues to grow, so will the importance of AI and edge computing.

The EU is proposing new regulations for AI, especially high-risk uses like facial recognition. This has caused mixed reactions. Some fear it will stifle innovation, while others believe it will build trust in AI. The regulations would limit police use of facial recognition and create a list of high-risk uses of AI. The proposal faces a long road to approval.

Businesses today face a complex and ever-changing world. Cognitive computing systems can help them deal with this complexity by identifying root causes, fostering better collaboration, and integrating data. However, cognitive computing is just one tool; a successful approach requires a multi-faceted strategy.

This article provides a glossary of terms related to artificial intelligence (AI). It emphasizes that while AI is a popular term, it’s important to understand the different technologies that fall under this umbrella. The article defines terms like machine learning, natural language processing, and deep learning.