One of my favorite death concepts is the Death Alternative[1] mod for Skyrim. It weaves "death" into the narrative. Instead of dying, you're robbed and left for dead by bandits and then can go on a quest to get your items back, or you're captured and enslaved by vampires and must escape (or, IIRC, join them). I love that it makes defeats part of the story. They become part of your character's history, helping define who your character is. It makes death meaningful, more so than checkpoints or saves, but not as frustrating as permadeath, while being a powerful mechanism for procedural storytelling. I would really love to see it in more games, by I believe Death Alternative is the only place I've seen it done.
GP for NNs has, but this isn't GP; "self-reproduction" (as in the original title) here means that the neural network is learning to output a copy of itself. In other words, the NN is learning to be a quine (as indicated by the current title). This is a very different than just applying genetic programming to NNs. In GP, you're updating the NN (or whatever) by copying it with mutations/recombinations. Here, the NN itself is learning to create a copy of itself.
The fact that they manage to also train to the network to simultaneously perform somewhat complicated tasks is super crazy.
> One of the strengths that's getting overlooked here is that crowd-sourced news seems to be more reliable than news from any one source. Everyone is biased, but if enough people are talking about something the bias tends to cancel out.
The problem with this is that people only have time to check a limited number of sources. Furthermore, many orders of magnitude more sources means that there are many orders of sources that are dangerously wrong as well. Thus, if someone sees a number articles/tweets/posts/whatever from a variety of people espousing that the Texas church shooter was an antifa commie starting the revolution, they are much more likely to believe it.
On top this, with so many sources, people need methods of filtering, and, of course, one of our primary methods of filtering is to find communities/people we tend to agree with. Thus, the now cliche echo chambers are born. These communities are furthermore highly susceptible to manipulation (see the russian facebook ads).
Furthermore, this makes the system fairly easy to take advantage of. If a number of people that seem unrelated online engage in a coordinated effort to spread a particular message, they can do it with ease, since when you see the same message from multiple, seemingly unrelated sources, you're much more likely to believe it.
So while you're right that we used to rely on gossip and hearsay, simply amplifying the number of sources in no way implies that we're getting a less biased message.
>So while you're right that we used to rely on gossip and hearsay, simply amplifying the number of sources in no way implies that we're getting a less biased message.
That's sort of what I was getting at. At heart, these new technologies aren't necessarily more reliable than what we had before. But on the other hand, I think that at the very least they're not any less reliable either. Simply by having more people reaching a consensus on something, you're probably going to have some great diversity of opinion.
In his book The Wisdom of Crowds, James Surowiecki posits that there are four factors that determine whether or not a crowd will be able to make intelligent decisions: diversity of opinion, independence, decentralization, and mechanisms for aggregation of collective judgement. Not to be self-congratulatory, but I think that's part of the reason communities like HN produce more intelligent and well-reasoned content than, say, an NRA fan club on Facebook.
I don't follow. This would only work if the distribution of numbers was predetermined and influenced the distribution of mines. I was under the impression that the mines were uniformly distributed though. So in a "T" scenario, it really is 50-50. The fact that 4s are more rare doesn't matter at that point. Sort of like in a series of coin flips, of you've flipped 5 heads in a row, tails isn't more likely to come since 6 heads are rare: it's still just 50-60.
The mines are uniformly distributed, yes, but the numbers are not. In a relatively sparse minefield, how likely is to find a 4? Of course depending on the "shape" of a cluster, chances can be 50%. The mines influence the distribution of numbers, not the other way around.
Try to apply the tactic I mentioned to solve the minefield in the article.
The numbers induce a probability distribution in the adjacent tiles. But you also should take into account that the remaining mines are uniformily distributed.
In other words, consider the prior.
I couldn't write math neither in favor nor against this claim.
1. Maybe for uniformly distributed mines the numbers have all the information you need.
or
2. Maybe using the fact the the mines are uniformily distributed, in addition to the numbers, has impact on the probabilities distributions
EDIT:
you play a 10x10 game with 20 mines.
your initial move in a non-border tile reveals a `1`.
you now know that around that `1` there is a 1/8=0.125 chance of hitting a mine.
ITOH there is a 19/91 = 0.20879 chance to find a mine in a tile not adjacent to the `1`
k-nearest neighbors (the k is just the number of nearby data points you consider when classifying a point), a clustering algorithm, and artificial neutral network
What about fingerprints? You don't need to buy anything, phones and such are already coming out with fingerprint readers and the technology is improving all the time. Finally, you can't lose your finger print (except in the case of extreme accidents, which exist for any type of security).
