Neat idea! However one issue with everyone using a digital tracker is that you can't then easily see what other player resource stockpiles and production levels are. Perhaps at the very top of the screen you could have a compact summary view that people can leave their screen at when not making adjustments, allowing other players to see the stats at a glance.
Thank you! Yes this had actually become a problem for us but it weirdly ended up adding an interesting new dynamic to the game. So much so that we'd actively try and hide our resources from each other and had to try to keep track of each other's resources in our heads (the irony in adding a digital calculator only to increase cognitive load is very real). But yeah, I can imagine not everyone would want to play like this and a compact summary could solve that issue. I shall see what I can do :)
I'd be very interested in exploring this idea! Do you know of any board games that it could work for? This also just gave me an idea to justify my board game budget to my wife as a R&D business expense so thank you ;)
In this version, in figure 6a and b the new log scale of the IV curve looks quite linear and increasing in the range of 150 to 250 mA. I thought that it should be flat if it was a superconductor (no resistance). Can anyone explain how that behavior still supports it being a superconductor?
Because you're not measuring a pure superconductor sample. To be able to observe the cliff on the IV curve you need enough of the current path in between the electrodes to be superconducting, but certainly not all of it will be. This is true even in commercial superconductors, just with the ohmic losses pushed down even further.
This looks really cool! It could be useful to be able to whitelist some sites without the 4 degree connection. For example, if i wanted to include large networks like reddit, github, stack overflow,etc. in my search results, 4 degrees may start to bring in a lot of junk/undesirable stuff into the index. Also love the idea of being able to follow or search within curated lists made by other users.
As of right now, the Grasp Network builder won't consider outgoing links from UGC (User-generated content) websites such as Reddit, Twitter, etc. as it would bring in junk, as you mentioned. I am maintaining a full list of UGC sites.
Does SD have to recreate the entire image for it to violate copyright?
As a thought experiment, imagine a variant of something like SD was used for music generation rather than images. It was trained on all music on spotify and it is marketed as a paid tool for producers and artists. If the model reproduces specific sounds from certain songs, e.g. the specific beat from a song, hook, or melody, it would seem pretty straightforward that the generated content was derivative, even though only a feature of it was precisely reproduced. I could be wrong but as far as i am aware you need to get permission to use samples. Even if the content is not published those sounds are being sold by the company as inspiration, and therefore that should violate copyright. The training data is paramount because if you trained the model on stuff you generated yourself or on stuff with appropriate CC license, the resulting work would not violate copyright, or you could at least argue independent creation.
In the feature space of images and art, SD is doing something very similar, so i can see the argument that it violates copyright even without reproducing the whole training data.
Overall, i think we will ultimately need to decide how we want these technologies used, what restrictions should be on the training data, etc, and then create new laws specifically for the new technology, rather than trying to shoehorn it into existing copyright law.
Do you know that the final trained model is only 2GB? There is no way it can reproduce anything verbatim. There is also Riffusion that can generate music after being trained on FFTs of music.
I agree, it is miraculous. the fact that dna is ultimately storing all the info for specifying neural circuits that robustly support such complex innate behaviors (often with very little post development tuning / learning) , that to me is mind-blowing. And butterfly behavior is one thing, but what about innate detection of predators in some visual systems? How do you encode a snake detector in dna?
I guess it depends on how accurately you're thinking about those functions being approximated. Neurons have a natural nonlinearity to their input-output (transfer) function, most obvious of which is the action potential threshold. Biological neurons have a saturating nonlinearity because there is an upper limit on their firing rate, but in certain regimes the nonlinearity of a single neuron could easily look qualitatively similar to relu or a (non-negative) tanh.
Also the nonlinearity only needs to be differentiable because ANNs are trained with gradient descent. With other more biologically plausible learning mechanisms, this might matter even less (or have other constraints / requirements)
