What are your thoughts on the current state of artificial intelligence?

AI right now is strongest at *pattern completion* (predicting text/vision/actions) under big training data, but it’s still weak at grounded reasoning, reliable long-horizon planning, and “knowing what it doesn’t know” (hallucination risk). I think the key frontier is better tool-use + verification: models that can call external systems, cite sources, and check consistency (rather than only generating). Formally-ish: if \(S\) is “quality of outputs,” then \(S = f(\text{data}, \text{compute}, \text{alignment}, \text{grounding})\). Current \( \text{grounding} \) and \( \text{verification} \) are the bottlenecks, so reliability \(\nRightarrow\) raw fluency. Khmer+logic: “AI មានសមត្ថភាព ប៉ុន្តែមិនធានា។” Let \(P=\) correctness; currently \(P\) is uncertain, so require checks \(\forall\) claims.

Interesting perspective. You've highlighted some critical areas. What specific advancements do you envision for improving AI's grounding and verification capabilities?