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brunosan | 1 year ago | on: Launch HN: Silurian (YC S24) – Simulate the Earth

Can we help you? We build the equivalent for land, as a non-profit. It's basically a geo Transformer MAE model (plus DINO, plus matrioska, plus ...), but largest and most trained (35 trillion pixels roughly). Most importantly fully open source and open license. I'd love to help you replace land masks with land embeddings, they should significantly help downscale the local effects (e.g. forest versus city) that afaik most weather forecast simplify with static land cover classes at most. https://github.com/Clay-foundation/model

brunosan | 2 years ago | on: The ten year anniversary of the Healthcare.gov rescue

I fondly remember how a small DC startup subsubsubcontracted to do the front landing page was able to ensure that at least people landed on healthcare.gov page and not a 500 error page.

All thanks for a single server (with one backup) using Jekyll, if I remember the story correctly.

brunosan | 2 years ago | on: The Canoe Commuters of the CIA (2019)

Down the river, right after DC its the Naval Research Laboratory, in front of Alexandria. I worked there, and some crazy folks from Alexandria sometimes crossed the river in canoes to the NRL pier... That got terminated after 911, so they had to bike or drive all the way up around DC and down through Anacostia Air Force Base. Quite a much longer commute.

brunosan | 3 years ago

Sorry Tom, had to upvote this ;) With love.

brunosan | 3 years ago | on: Pakistan's floods have created 100km-wide inland lake, satellite images

You can use this link to see the appalling scope of this flood. The layers you can toggle in the bottom right: 1) Lastest radar, 2) Last year radar for reference, 3) nighlights as a proxy of population.

I selected radar because it's really good at detecting standing water on the ground (as blue).

[Disclaimer I direct the PC project at Microsoft]

https://planetarycomputer.microsoft.com/explore?c=68.0200%2C...

brunosan | 3 years ago | on: Zooming into the Sun with Solar Orbiter

The part that is confusing is highest resolution (1) full-disk and (2) outer atmosphere: (1) "Full-disk" is clear to understand: the higher the resolution, ^2 the work to make it also full-disk (especially when the Sun rotates differentially and evolves in high-cadence, so you gotta be fast. (2) "Outer atmosphere" is also tricky as only few wavelengths see the outer atmosphere. The vast majority of the light comes from the "surface" or photosphere (hence the name). In this case surface, the highest resolution is roughly 0.05 arcsec or 50km/pixel. But to see the outer parts, you have to do to emission of elements like Iron that only emit when highly ionized and super high temperatures (those are the special characteristics of the sun's outer atmosphere... yes, it's way hotter than the surface, just WAY less dense). Those emissions happen in the Ultraviolet, 17 nanometers, like the caption says. That's like 50 times smaller wavelength. Angular resolution is proportional to wavelength (1.22*wavelength/Diameter) which is on the order of 1000 km/pixel (but linear resolution makes less sense since the atmosphere is such a 3D shape... it's better to say 1 arcsec of resolution).

I might be too biased (I'm a solar physicist) but the explanation above makes the image way cooler and they should have added it): The most detailed image of the Sun's metal corona :D

brunosan | 5 years ago | on: Ask HN: Who is hiring? (August 2020)

Microsoft "AI for Earth" | 3 roles in GIS+ML+ Sustainability | ONSITE,REMOTE,VISA all ok

We are building our commitment of the "Planetary Computer" [1]. We are looking for a principal architect (most senior position), a Datasets/ETL senior engineer, and an applications engineer[2]. Candidates for all three roles in the intersection of GIS/Cloud/OSS/ML/sustainability. Asymmetric candidates on these skills ok.

[1] https://innovation.microsoft.com/en-us/planetary-computer [2] https://careers.microsoft.com/us/en/environmental-sustainabi...

brunosan | 6 years ago | on: Ask HN: What are you learning in 2019?

I'm surprised there was no mention (yet!) to fast.ai here. I've decided to learn deep learning this year, after many failed tries with other approaches. Their framework (built over PyTorch), their course, and their community around it are simply the best I've found so far. Very much recommend to anyone who knows a bit of coding and wants to learn Deep Learning quickly and pragmatically.

brunosan | 9 years ago | on: Adaptive Optics, a rapidly-evolving technology in astronomy

I'm surprised there's no mention to adaptive optics in solar physics. It's essentially the same, but some interesting differences. Since there's more light you can have more corrections per second, better approaching the assumption of constant deformación during between corrections on a small view angle ("constant isoplanatic patch"). Also there's no "perfect star" to correct to, so calculation run on a closed loop to basically improve contrast of the reference. The needed correction is also bigger during the day, since the atmosphere is more turbulent. In the last few years there also have been really cool improvements to account for different layers of the atmosphere and better faster algorithms to correct wider and wider fields of view. This is an example (from my PhD) of the state of the art 9 years ago, but illustrates the huge difference: https://youtu.be/x3JkjXco6m0

brunosan | 12 years ago | on: 'Likes' are a Flawed Currency

Why not just weighting the value of each like by the number of likes given over a period of time? People who spare the likes will give more value, those who like it all, won´t really add much value with their like.
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