Here's an example of something you don't hear about: AI Assisted Battlefield Tactics. While I've never heard of it (certainly not in the press), I simply assume that they're doing research on it. I base this assumption on the AlphaStar AI from DeepMind that would completely pawn Grand Masters in the game of StarCraft 2.
While AlphaStar is obviously designed for a game with very set rules and weights, I don't think it's unfeasible to develop a similar military AI that could also work in the shifting tactics of the modern battlefields.
The result would be comical, as larger armies without such an AI would always lose to someone with that AI, even if their army is much smaller or seemingly technologically disadvantaged. And it would seem that there's at least one such country in such a position today, which is also heavily supported by the NATO.
Now, my last argument for why alphastar wasn’t some sort of brilliant tactician was that eventually people figured out that it’s susceptible to all the same problems a normal bot is: you can dart a warp prism in and out of its vision and it will send its army back and forth, you can confuse it by going mass raven/PF etc. and it’s completely unable to adapt. So in conclusion, no: AlphaStar doesn’t say anything one way or another about military AIs.
I often wonder how much autocorrect will shape the evolution of language.
Apple recently announced that it was going to stop autocorrecting a certain expletive intensifier to "ducking", and I think that one actually had the potential to catch on....
I wonder if it'll ultimately do more to preserve ridiculous quirks of English spelling (and US/UK distinctions) most people don't remember or care about than change language
Applications include:
- Underground
- Under dense rainforest canopy where GNSS signals don't reach
- In narrow and deep valleys
- Salt water deeper than 200 mm
- In space, far away from GNSS systems (GNSSes work in space)
Source: I may have wandered through Trimble Nav Ltd. once or twice.
Suddenly you've got a viable model to use on real tactical maps, that is strikingly similar to SC2, though adapted to real life conditions. That is, if you're able to track - or in the least theorize the position of - each individual "piece" on that board (so soldiers and armour, etc).
A real life soldier does perhaps have some different qualities and abilities than a space marine, but it's still a great starting point for building a more realistic model.
So say, your model looks more like Arma 3... Only top down. Now, I've been in the army, so I can tell you first hand that many aspects of Arma 3 is scarily realistic. Other aspects, not so much. But if you add in some modding, and all that is solved.
It's the same principle. You've already have a base AI to "play the game" and now you adapt each information point to reflect real life instead of game mechanics.
Sure, this sort of AI is brand new, so there would of course be things to iron out. Perhaps you need to use other statistical models to better capture the fog of war. But at the end of it, I think it can be done. Hell, perhaps it can even be used to fight crime. What do I know, perhaps it already is, but nobody wants to talk about it, kind of like how it was such a great moment when it dropped that New Scotland Yards used graph databases to solve cases before it was cool.
AI that is good at W3 manages every individual unit’s actions and it does that based on a map that magically reveals enemies when you get close. Nothing like that would ever work IRL.
There is a very specific problem - the simulation speed problem - that is in the way.
For games RL agents can be trained by running billions of adversarial simulations. Set up a battle between two agents and reward the one that wins, try variations and repeat, and repeat, and repeat. The trick is to manage the search process so as to not waste time on strategy branches that won't get anywhere, but the idea is very simple.
Unfortunately for things like real world conflict the simulations aren't that representative of what really happens, they are also really really really really complex and slow, and so finding wining strategies is a bit hard.
I was suspecting the northern lights were to blame for most of this trouble since the bad performance periods more or less track to high Kp periods, but it seems that it may be man made interference... There are recent reports from planes flying routes over that area about bad GNSS reception, and efforts from NKOM to log conditions with mobile antennas.
It's probably happening already.
They already developed a device that could do that in the 60s, but it was quite large:
https://en.wikipedia.org/wiki/Lockheed_SR-71_Blackbird#Astro...
https://timeandnavigation.si.edu/multimedia-asset/nortronics...
Do you have a source for the one you say they're working on? Is more portable or hand-held?
However, stars are (to the nearest approximation) point sources. If you use a telescope and zoom in to the star, then you can spread the atmosphere brightness over a large area while concentrating the starlight into a very small area, which means you can see stars during the day. Couple that with a reasonable level of high dynamic range sensor and integration over time, and it would be quite possible to observe the positions of a load of stars during the day.