jk4930

Downstream would be typical satellite applications (usually communication, navigation, imaging / Earth observation), though I don't know their names out of my head. Sometimes one sees a crowdfunding campaign aiming for some novel application. The lunar applications are mostly different, more on the space science and space mining side.

And of course many things not directly doing rocket science. Just some ideas: space suit sensor networks, big data and analytics for spaceflight medicine R&D, AI for autonomous vehicles or on-site assessments a.s.o. Could be done via established smaller suppliers (e.g. co-funded via Horizon 2020 grants) or own project / startup attempts. Even quite a few of the established players moderately embrace the digitalization and automation wave, so they're open for novel techniques and approaches.

One could get involved with one of the many Mars Society chapters and see whether one could spin off something there.

Our challenge is to create a European private space ecosystem. Luckily we have tech and talent, but compared to the US we're small, underfunded, not well connected. Part of my work is to change that, but I'm still preparing.

There's an older post of mine re the GLXP: https://news.ycombinator.com/item?id=9916217

Since you're into Lisp, you perhaps like this one: http://www.flownet.com/gat/jpl-lisp.html

So what should be our next steps?

https://www.washingtonpost.com/news/worldviews/wp/2014/07/24...

1. Islam is the only true religion: 72% YES 2. There should be a Muslim majority in Germany: 46% YES 3. Want only Muslims as neighbours: 62% YES

> http://www.welt.de/politik/deutschland/article108659406/Tuer...

Just in case, a good implementation (e.g. GNU APL, Dyalog) to recommend (performance-wise)? I also tried J years ago, but not on larger data sets or computationally expensive things. My experience and overview is pretty dusty.

It's mostly literature from the 1970s and 1980s, usually in German. APL explained (basics, data structures, algos), APL applied to AI, math, statistics, etc. Nothing that beats Iverson's written works.

Then the community is kind of dying out, at least over here (Germany).

This is really bitter for me. APL is fun with the intellectual satisfaction that comes from arranging the symbols, the beautiful theoretical background and the clear approach to doing things.

1. Tech development: It requires changes in thinking, tools, procedures etc. Perhaps harder than tech itself is to acquire the required mindset.

2. Legal: Space law is fun but complex once it goes into the details. US laws like ITAR (now a bit milder than before) haunt us. Plus plenty of other laws.

3. Funding: It's hard to make business cases for a (literal) moonshot. Sponsorship and payload are the main revenue sources, but most teams don't succeed. Their story (or presentation) is not exciting or convincing, their team is not adequate (skills, mentality, manpower), so they don't get sponsors, investors, or customers. Or they're just in a country where risk is not rewarded or capital is absent.

4. Launch: Finding the right rocket is important; it influences spacecraft design. Then negotiating a contract and sticking to it. Many hurdles. And it's expensive before the launch. Launch is the biggest cost center.

5. Politics: XPRIZE Foundation is a US org, so US law and politics determine much of what you (not) do, e.g. avoid tech or people from blacklisted countries. Or when geopolitics kicks in and the rocket in another country suddenly or potentially becomes unavailable.

And much more. So we're making progress. But it's not something we talk about much.

I just realize that I wrote the five points above in a kind of negative tone. They're not. E.g. once you have the required mindset, you're filled with nearly unshakable certainty about what you do and why. Laws are solved problems--or when they work on them, they make open problems pretty clear. The pressure to find business cases makes you think hard about what is possible and economical at what time, you start to see a roadmap of doable things until you reach your goal; after all to kickstart private space is one of the GLXP's intentions. The launch sector is a funny business, you meet interesting people and it gives you insights into one of the greatest filters that still stops humanity from going into space at large scales. Politics is not always a burden, it can also be a source of support and goodwill; e.g. if you align interests and avoid stepping on the wrong toes, it can be very helpful.

So, yeah, space is hard. But we're getting there.

Ada is not made for explorative hacking or intellectual workouts but for reliable implementation. And it's not that those who criticize its verbosity program in APL themselves. ;)

http://www.terrybisson.com/page6/page6.html

1. If you use it commercially, you can pay for it.

2. In most cases where it's needed, 64 bit doesn't matter.

(Though I might be wrong on the second one.)

As [1] says: "Rust for C programmers != Rust for functional programmers."

[1] http://science.raphael.poss.name/rust-for-functional-program...

science: from all we know, we assume that cutting off his leg is bad, so we don't do it. => data and models

Make it so.

;)

http://en.wikipedia.org/wiki/Compartmental_models_in_epidemi...