> Students taught to solve easy problems by themselves will be at a big disadvantage in the workforce compared to students taught to solve hard problems using AI.
What hard problems could students solve with AI that requires the students to be especially trained? It seems you are thinking of GPT-3 style "prompt engineering". That's a thing of the past. Students can just copy the assignment into the LLM. They don't need to be taught to do that.
An interesting thing about the a lockstep solution which only considers inputs is that any RNG required in the game must be generated from the input history somehow. This could lead to players being able to manipulate their luck with extremely precise inputs.
The other interesting trick is you need a separate RNG for visual only affects such as particles than the one you use for the physics simulation. Depending on the game during replays, you could position the camera differently and then particle effects would render differently depend, depending on what’s on screen. Obviously that shouldn’t affect the way objects decide to break during the physics simulation.
Typical deterministic game engines will do this, send it to every machine as part of the initial game state, and also check the seed across machines on every simulation frame (or periodically) to detect desyncs.
That could lead to other subtle problems elsewhere though, because it requires synchronizing the seed. If you can't do that, it could lead to problems. E.g. when comparing offline speedruns where everyone would have a different seed. Then some players could have more luck than others even with the same inputs, which would be unfair. (Though I can't think of anything else at the moment.)
This does the standard thing of treating preorders as the default generalization of partial orders. But an (arguably) more natural, and more useful, generalization of partial orders is acyclicity.
Unfortunately acyclicity isn't called an "order" so people assume it's something unrelated. But "orders" are just second-order properties that binary relations can fulfill, and acyclicity is also such a property.
Acyclicity is a generalization of strict (irreflexive) partial orders, just like strict partial orders are a generalization of strict total (linear) orders. Every strict partial order relation is acyclic, but not every acyclic relation is a strict partial order.
A strict partial order is a binary relation that is both acyclic and transitive, i.e. a strict partial order is the transitive closure of an acyclic relation.
Binary relations of any kind can be represented as sets of pairs, or as directed graphs. If the binary relation in the directed graph is acyclic, that graph is called a "directed acyclic graph", or DAG. In a DAG the transitive closure (strict partial order) is called the reachability relation.
Examples of common acyclic relations that are not strict partial orders: x∈y (set membership), x causes y, x is a parent of y.
Nice. But note that the average is still significantly below 50%. It's also a bit concerning that the growth rate seems to be levelling off. It currently looks like a sigmoid curve with a maximum far below 100%.
I wouldn't be so worried about it. It's really hard for something as big as this to really hit 100%. If we hit 80% or thereabouts, we can at least plausibly argue to backwards ISPs that IPv6 is the default and the standard that everyone should reasonably be offering.
Generally: I'm really surprised that Norway is just at 27%. I think I've been with 3 different residential ISPs the last 15 years, and all of them have done IPv6 perfectly well (two nits: I think one required a trivial opt-in, and my current ISP is just giving me /60 which isn't perfect).
Edit: Oops, sorry to my current ISP for shaming them. Some googling told me that one can get a /56 using DHCPv6-PD. I'll try that!
I was always puzzled by Guernica. It looks so ugly (I think most people who saw it for the first time and didn't know it was a famous painting by Picasso would agree), so how did it get so famous in the first place? Perhaps the point was that war is ugly, so the painting also had to be ugly? But it looks literally like a bad children's drawing. Maybe it got famous because a famous painter making an ugly painting on a serious subject was a novel and unconventional idea.
What hard problems could students solve with AI that requires the students to be especially trained? It seems you are thinking of GPT-3 style "prompt engineering". That's a thing of the past. Students can just copy the assignment into the LLM. They don't need to be taught to do that.
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