I can provide insights into some of the key trends and areas of focus in the field of next-generation AI:

1. Deep Learning Evolution: Next-generation AI is likely to continue the evolution of deep learning techniques, with more advanced neural network architectures and training methods. This could lead to improvements in natural language understanding, image recognition, and other AI applications.

2. Explainable AI (XAI): Addressing the "black-box" nature of deep learning models, XAI aims to make Next-Generation AI systems more transparent and understandable. It will be crucial in critical applications like healthcare and finance.

3. Federated Learning: This privacy-preserving AI approach allows models to be trained across decentralized data sources without sharing the data itself, enhancing data privacy and security.

4. AI at the Edge: The proliferation of IoT devices and the need for real-time processing are driving the development of AI models optimized for edge computing. These models can perform AI tasks on devices with limited computational resources.

5. Quantum Computing and AI: Quantum computing has the potential to significantly accelerate AI training and optimization tasks, offering a new frontier for AI research and development.