Affective Computing: Should AIOS Possess 'Empathy' or Maintain 'Tool Neutrality'?
Emotion: A Function or an Intervention? Affective Computing was once a staple of science fiction. Today, AIOS is gradually gaining this capability: …
| No. | Category | Sub-topic | Core Question |
|---|---|---|---|
| 1-1 | Modeling Paradigm & Dynamics | Multi-Physics Field Coupling | How to collaboratively model energy exchange between microscopic particles and macroscopic fluids? |
| 1-2 | Modeling Paradigm & Dynamics | Stochastic Dynamics & Risk Quantification | With highly uncertain environmental parameters, how can stochastic mathematics predict the probability of system evolution? |
| 1-3 | Modeling Paradigm & Dynamics | Chaotic Evolution in Complex Systems | How do tiny deviations in initial conditions cause long-term prediction failure, and what is the underlying topological mathematical structure? |
| 2-1 | Discrete Structure & Logic | Topological Robustness in Complex Networks | How does discrete graph theory define the fragility and self-healing capacity of global distribution networks? |
| 2-2 | Discrete Structure & Logic | Combinatorial Optimization & NP-Hardness | When search spaces grow exponentially, how can mathematical structures help algorithms find approximate global optima? |
| 2-3 | Discrete Structure & Logic | Logic Algebra & Formal Verification | How does predicate logic transform into the safety verification cornerstone for autonomous driving or kernel design? |
| 3-1 | Dynamic Control & Hybrid Systems | Stability Analysis of Switching Systems | When a physical system switches between multiple operating modes, how do you ensure continuous trajectories do not diverge? |
| 3-2 | Dynamic Control & Hybrid Systems | Impulsive Control & Non-Continuous Scheduling | How can high-frequency non-continuous control commands achieve minimum-error coverage of precise continuous motion? |
| 3-3 | Dynamic Control & Hybrid Systems | Collaborative Modeling in Hybrid Automation | What is the mathematical coordination mechanism of AI discrete decisions and physical continuous execution in hybrid dynamic systems? |
| 4-1 | Signal Processing & Frequency Domain | Quantum Reconstruction of Signal Processing | How can quantum algorithms reduce the complexity of traditional digital signal processing from polynomial to logarithmic order? |
| 4-2 | Signal Processing & Frequency Domain | Wavelet Analysis & Feature Resolution | For non-stationary signals, how can variable-step translation achieve ultra-precise capture of local information? |
| 4-3 | Signal Processing & Frequency Domain | Compressive Sensing & Information Sparsity | How to break the Nyquist sampling theorem and reconstruct complete high-dimensional information from very few observations? |
Emotion: A Function or an Intervention? Affective Computing was once a staple of science fiction. Today, AIOS is gradually gaining this capability: …
Background The butterfly effect reveals that deterministic equations can produce essentially unpredictable states due to extreme sensitivity to …
The Death of Memory: From "How to Do" to "What is Wanted" In the GUI era, proficiency was equivalent to the memory of operation …
Background Modern automation involves the deep fusion of discrete decision-making and continuous physical execution. Hybrid automation uses the Hybrid …
Background Problems like TSP, set cover, and knapsack involve search spaces that explode factorially or exponentially. Modern engineering relies on …
Background Nyquist-Shannon sampling requires rates over twice the bandwidth. Compressive Sensing (CS) subverts this by proving that sparse signals can …
Background Real physical systems in nature rarely follow a single physical law in isolation; rather, they are the result of intertwined interactions …
The End Game of Interaction: When Life Ceases, Intent Persists Traditional operating systems only manage processes of the “living.” …
Materialization of Interaction: From Pixels to Atoms For a long time, human-machine interaction was imprisoned behind screens. Even in MR (Mixed …
The End of Prompts Early Generative AI gave rise to “Prompt Engineering.” Users acted like debuggers of primitive code, attempting to …