Integrating Multimodal Learning
Combine different types of data processing (e.g., text, images, sound, and physical interaction) into a unified system that mimics human sensory and cognitive integration.
Example: An AGI should understand a scene by combining visual input with language context, much like a human does.
Building Reasoning and Problem-Solving Skills
Enable AI to perform abstract reasoning, causal inference, and creative problem-solving, rather than relying solely on pattern recognition.
Research focus: Symbolic AI, neural-symbolic integration, and common-sense reasoning.
Achieving Self-Improvement
Design systems that can autonomously improve their own algorithms, learn from minimal data, and adapt to new environments without human intervention.
Example: Recursive self-improvement, where an AI refines its own code or learning process.