> Bellwether, a moonshot at Alphabet's X, is using Earth AI to provide hurricane predictions insights for global insurance broker McGill and Partners. This enables McGill's clients to pay claims faster so homeowners can start rebuilding sooner.
Seems plausible to me. It would allow them to start contracting CAT adjusters as soon as a hurricane is expected, before other insurers start bidding for them.
Will this actually pay off for them? Who knows. But insurers are quite into ML for claims/underwriting these days, so I'd believe they're giving it a try.
Could be a nice expensive contractor option for replacing the NOAA's public data that we lost. But it probably wont be picked up because it has to study the climate, which is a bad word now.
You can totally create a private version of NOAA so long as you keep the messaging about insurance intelligence and never, ever speculate out loud about the causes of hurricanes. And if that's not enough, just do what Meta did and hire some shmuck like Robby Starbuck to signal that you're on the right team.
What they want is for the government to run the satellites and provide the data on the taxpayers' dime, but only let private companies interpret that data so they can sell their forecasting
Instead of all this stuff, I'd like to see Google use their ML chops to "solve" weather forecasting and deliver ultra accurate predictions a few days ahead.
I have found that using LLMs to generate queries for Overpass (Open street map query language) works really well. Great alternative if you don't care to deal with corporate nonsense.
I have some old screenshots of interesting locations from Google Earth circa 2006-2012 that I've never been able to track down. I wonder if something like this would be capable of geolocating them somehow -- like reverse image search for landscapes.
There's a whole community (with world tournaments [1]) around finding places from pictures: geoguessers. The top people are absolutely incredibly [2]. There are also AI trained for this purpose. Although, the perspective they use is usually from street level.
A few people recommended Geoguessr (and people like Rainbolt are definitely amazing), but yeah I reckon they're hyperspecialized on reading clues in actual street view imagery, not natural satellite footage like this.
Out of interest: have you already tried using GPT 5 (reasoning / thinking) for that? I've had quite some success in the past using them to track down such places.
Yeah, that and Gemini 2.5. They actually were able to help identify a handful based on context clues, or at least narrow it down enough that I could find it myself. But there were three I couldn't crack -- even a forum dedicated to solving GE puzzles came up empty:
"This looks almost certainly like a satellite view of a region in Western Australia, such as the Pilbara or the Hamersley Range. The dark areas are likely ancient, iron-rich rock formations (ironstone), and the surrounding soil is iconic of what's known as Australia's "Red Centre."
In 2001 we used Erdas Imagine to do this type of work. It required humans to train the software using heads-up digitizing. Dare I say machine learning on Pentium workstations?
edit, looks like they have ai too now. could be neat to play with after how long has it been. jeesh.
Guess which corporation just announced they're profiting off of the government shutdown of vital environmental and climate agencies? I wonder why they failed to mention any of that in this press release.
> Bellwether, a moonshot at Alphabet's X, is using Earth AI to provide hurricane predictions insights for global insurance broker McGill and Partners. This enables McGill's clients to pay claims faster so homeowners can start rebuilding sooner.
Hm, I'm quite skeptical about this claim.
Seems plausible to me. It would allow them to start contracting CAT adjusters as soon as a hurricane is expected, before other insurers start bidding for them.
Will this actually pay off for them? Who knows. But insurers are quite into ML for claims/underwriting these days, so I'd believe they're giving it a try.
Wdym by 'bid for them'? Won't the MGA want to get rid of their contracts in an area that's about to be hit by a hurricane ASAP?
Could be a nice expensive contractor option for replacing the NOAA's public data that we lost. But it probably wont be picked up because it has to study the climate, which is a bad word now.
You can totally create a private version of NOAA so long as you keep the messaging about insurance intelligence and never, ever speculate out loud about the causes of hurricanes. And if that's not enough, just do what Meta did and hire some shmuck like Robby Starbuck to signal that you're on the right team.
I see the humor in this but you'd still need to operate your own satellites.
What they want is for the government to run the satellites and provide the data on the taxpayers' dime, but only let private companies interpret that data so they can sell their forecasting
https://www.cnn.com/2017/10/14/politics/noaa-nominee-accuwea... (note: old news)
> McGill and Partners
Hi, I'm Saul Goodman. Did you know that you have hurricanes? The constitution says you do! And so do AI.
Haha yeah. Perhaps a marketing gimmick with an asterisk..
Instead of all this stuff, I'd like to see Google use their ML chops to "solve" weather forecasting and deliver ultra accurate predictions a few days ahead.
But then who’s gonna spend all day Googling stuff when the weather changes their plans again?
It shifts from map layers to answer “what/where/why now?” rather than just “show me X.”
And the Gemini-in-Google Earth bit could lower the barrier for non-GIS folks.
I have found that using LLMs to generate queries for Overpass (Open street map query language) works really well. Great alternative if you don't care to deal with corporate nonsense.
I have some old screenshots of interesting locations from Google Earth circa 2006-2012 that I've never been able to track down. I wonder if something like this would be capable of geolocating them somehow -- like reverse image search for landscapes.
There's a whole community (with world tournaments [1]) around finding places from pictures: geoguessers. The top people are absolutely incredibly [2]. There are also AI trained for this purpose. Although, the perspective they use is usually from street level.
[1] https://www.youtube.com/watch?v=u3sVtwexp0o
[2] https://www.youtube.com/@georainbolt
A few people recommended Geoguessr (and people like Rainbolt are definitely amazing), but yeah I reckon they're hyperspecialized on reading clues in actual street view imagery, not natural satellite footage like this.
Out of interest: have you already tried using GPT 5 (reasoning / thinking) for that? I've had quite some success in the past using them to track down such places.
Yeah, that and Gemini 2.5. They actually were able to help identify a handful based on context clues, or at least narrow it down enough that I could find it myself. But there were three I couldn't crack -- even a forum dedicated to solving GE puzzles came up empty:
https://googleearthcommunity.proboards.com/thread/10731/ulti...
Maybe Geoguessr players would be good at identifying them as well?
First photo could be Namibia? 29°40'04"S 18°11'12"E
Hmm, plausible... though I'll have to go back in time and kick myself if it turns out I captioned it with the wrong continent!
Gemini says:
"This looks almost certainly like a satellite view of a region in Western Australia, such as the Pilbara or the Hamersley Range. The dark areas are likely ancient, iron-rich rock formations (ironstone), and the surrounding soil is iconic of what's known as Australia's "Red Centre."
In 2001 we used Erdas Imagine to do this type of work. It required humans to train the software using heads-up digitizing. Dare I say machine learning on Pentium workstations?
edit, looks like they have ai too now. could be neat to play with after how long has it been. jeesh.
Once Zillow and Redfin start doing this, that will be game-changing
Guess which corporation just announced they're profiting off of the government shutdown of vital environmental and climate agencies? I wonder why they failed to mention any of that in this press release.
Mhh, don't we already have conventional ways of telling where a flodding might happen?