I feel like street-view data is surprisingly underused for geospatial intelligence.
With current-gen multimodal LLMs, you could very easily query and plot things like "broken windows," "houses with front-yard fences," "double-parked cars," "faded lane markers," etc. that are difficult to generally derive from other sources.
For any reasonably-sized area, I'd guess the largest bottleneck is actually the Maps API cost vs the LLM inference. And ideally we'd have better GIS products for doing this sort of analysis smoothly.
With current-gen multimodal LLMs, you could very easily query and plot things like "broken windows," "houses with front-yard fences," "double-parked cars," "faded lane markers," etc. that are difficult to generally derive from other sources.
For any reasonably-sized area, I'd guess the largest bottleneck is actually the Maps API cost vs the LLM inference. And ideally we'd have better GIS products for doing this sort of analysis smoothly.