I wish the press release had a bit more detail about what this model actually does and whether it's actually useful for the suggested use cases.
However, make no mistake: this is for the scientific community and will not help geospatial data to be commercialized. No one cares about your geospatial crop model or that you can identify energy infrastructure or that there's some activity around that copper mine. Well, at least no one cares that will actually pay you.
(FWIW, I cofounded a geospatial analytics company)
Satellite data is extremely idiosyncratic. It's coarse (~10m at best), infrequent (every few days at best), and oh you have to deal with the fact that the planet is covered in 50% clouds at any moment. Satellite data works best on things that don't move, that are fairly large, and change infrequently. If you find a use case that satisfies those conditions and want to make money, then you need to find a problem that terrestrial sensors haven't solved. And if you find that problem, the cost of building, training, and running your model (plus the cost of the data!) has to be less than the marginal value of your model. Good luck finding those use cases.
The US Government is special. We don't know what's going on in North Korea or Ukraine or the South China Sea so we buy high resolution imagery over those areas (30cm) at great cost. Large ag companies and oil companies know what's going on within their own facilities; and price gives them information about the rest of the supply chain.
In other words, this might be an interesting announcement for scientists, but it won't change the geospatial market at all.
Hey, I'm the founding CEO who wrote the article. I hold some of the blame here too for trying to read the market and be something that we weren't. When you hear lots of people raising at 20-30x their ARR, it pushes you as a founder to try to paint a picture of your company through that lens. However, I currently don't see the possibility of anyone in geospatial being widely-used software.
Has anyone tried to write an algorithm that translates any piece of text into "basic English." That seems like a tractable problem, since it's just mapping all the words in English and grammatical structures into Ogden's 850 words and rules.
A scientist at Los Alamos National Laboratory trained a GAN to test automated change detection algorithms in satellite imagery, with a link to the associated SPIE paper.
We've had 10 years of frothiness in venture markets. Many employees under 30 don't even know what a downturn looks like. They're used to high pay, constant calls from recruiters, and venture capital flowing into their companies. Even the companies who flop, no big deal, just go down the street to the next company. I worry that that generation is going to have the most difficulty with these changes. They'll wonder why things are contracting, why difficult decisions need to be made, can't we just wait this one out...?
I've never seen anything like COVID-19. I lived through the dot-com bubble, watching friends who want from an IPO party to crying and packing up their car back to Iowa within 6-months. Tech contracted and survived. Then there was the 2008 financial crisis. In that case, the damage was spread out beyond tech centers. Capital markets dried up and life seemed very uncertain for awhile.
With COVID-19, we went from extreme prosperity to an unprecedented shutdown of global economies with massive uncertainty as to how long this will last. Every business will be affected, the vast majority of them negatively.
I really wonder whether everyone is prepared for what it means to live in scarcity instead of abundance.
I left the Bay Area almost 5 years ago now to start a company that I spun out of Los Alamos National Laboratory. Everyone - investors, my friends & family, our founders, even me - thought we would move to San Francisco within a year.
Four years later, Descartes Laba is almost 100 people strong, $38M investes, and thriving in the Land of Enchantment.
The reality is that if you have a strong mission, a viable company, and a great place to live, you can build a company. Sure, we can't hire anyone from Silicon Valley, but that's ok. Our recruiting team looks in all of the places FANG isn't looking - and we've found some incredible talent.
I hope that it's not just major cities that see this Renaissance of tech, but cities across America and the world. This is how we transform society with technology - by bringing a wider audience into the conversation.
I'm the CEO of Descartes Labs. It's indeed true that we've built a data refinery that ingests lots and lots of satellite data. The data refinery can be seen as a two-sided marketplace. On one side, we form partnerships with satellite and other geospatial data companies (in addition to open source data from NASA, ESA,and others) and pull in all of that data. On the other side, scientists can run computations over huge amounts of data from multiple datasets. For now, most of our business has been done on the scientist side. In principle, we could provide our infrastructure to satellite companies so they don't have to build out the software on their own. Most hardware companies suck at being software companies.
Amazon's offering is geared more towards ground stations, but they might move up the stack and start providing data refinery-type services on top of the ground station work.
Oh, our entire stack is built on Google Cloud Platform.
What a fantastic read. As a CEO who has grown my company from 6 to almost 100, this is one of the hardest discussions to have with someone. It's not that they did anything wrong, they're just no "right" for the position in its current state.
He suggests that it's impossible to retain employees through such changes. I haven't found this to be the case. One technique I've used is to keep the company title-light, so that changes in title aren't as stark. I've also had a few people who have gone from IC->manager->IC, which shows the company that I value people no matter what their role is. Retaining people after hiring above them requires a lot of careful, honest conversations not just with the affected employee, but with messaging to the broader team.
Descartes Labs is building models of complex systems on the planet. Though our first product is focused on agriculture, our aim is to tackle tough, meaningful, global problems with science. To do this, we've amassed over 3PB of geospatial data, growing at over 10TB per day, and can spin up tens of thousand of cores to perform calculations. We're looking for engineers who want to evolve our platform and for scientists who want to build solutions on top of that platform. Check us out!
(I'm the CEO - feel free to contact me directly at mark@[company name].com or apply through our site)
However, make no mistake: this is for the scientific community and will not help geospatial data to be commercialized. No one cares about your geospatial crop model or that you can identify energy infrastructure or that there's some activity around that copper mine. Well, at least no one cares that will actually pay you.
(FWIW, I cofounded a geospatial analytics company)
Satellite data is extremely idiosyncratic. It's coarse (~10m at best), infrequent (every few days at best), and oh you have to deal with the fact that the planet is covered in 50% clouds at any moment. Satellite data works best on things that don't move, that are fairly large, and change infrequently. If you find a use case that satisfies those conditions and want to make money, then you need to find a problem that terrestrial sensors haven't solved. And if you find that problem, the cost of building, training, and running your model (plus the cost of the data!) has to be less than the marginal value of your model. Good luck finding those use cases.
The US Government is special. We don't know what's going on in North Korea or Ukraine or the South China Sea so we buy high resolution imagery over those areas (30cm) at great cost. Large ag companies and oil companies know what's going on within their own facilities; and price gives them information about the rest of the supply chain.
In other words, this might be an interesting announcement for scientists, but it won't change the geospatial market at all.