WORLD_ENDS_SOON

Deep learning combines linear functions together, but the way in which they are combined is always nonlinear. If the way in which they were combined were linear, the resulting function would also be linear (a linear combination of linear functions is linear), and you'd have linear regression. Specifically the final layer of a deep neural network is often linear but the nodes in middle layers are often Rectified Linear Units which have a nonlinear "max" function applied to a linear function. Without these "max" functions you'd be able to flatten all the layers into one. Other common nonlinear functions you'll find in a deep neural net are sigmoid functions like tanh. These functions are sometimes called "activation functions".

Have you tried out the ChucK language? I haven't tried Extempore yet, but it looks like the way they handle timing could be similar. ChucK has a very elegant system for synchronizing synthesizers and sequencers where you can write code in a simple imperative style (within a sequencer you can "wait" until the next note needs to be played). The language runtime keeps all of the coroutines running in sync with a global clock. I don't know of other languages that use this style of timing, so I'd be very curious to hear how they compare.

I think it is because many labs in CS departments do very little research involving human subjects (e.g. a machine learning lab or a theory lab), so within those labs there isn't really an expectation that everything goes through IRB. Many CS graduate students likely never have to interact with IRB at all, so they probably don't even know when it is necessary to involve IRB. The rules for what requires IRB involvement are also somewhat open to interpretation. For example, surveys are often exempt depending on what the survey is asking about.

It's very sad Rosenblatt did not live to see the resurgence of neural networks and his perceptron algorithm. The perceptron algorithm isn't exactly what we use to train neural networks today, but it's similar enough in theory and practice that it still feels very fundamental to understanding machine learning.

This sort of research is maybe less flashy than say using machine learning to automatically generate game assets from photos, but I think this sort of computer-aided game design is possibly the biggest way machine learning will transform video games. As games are becoming bigger and more complicated, the problem of tuning various gameplay parameters explodes exponentially. And, this sort of tuning can have a huge effect on player retention and overall game quality.

In this research the machine learning is being used to balance the game across different asymmetric strategies (different decks in the card game), but you could imagine using similar techniques for balancing and tuning content for single player games as well. Once you have a reasonable model of the player's behavior, you can do all sorts of automatic tuning like balancing the difficulty of jumps in a platformer, tuning enemy positions in an FPS, etc.

I'm guessing information isn't put in the email because of federal privacy laws around education (FERPA). Email isn't considered a secure communication protocol since it isn't encrypted in transit, so schools can't email grades or other information related to education records. I'm guessing sending all messages through a secure web portal is just an easy way to avoid FERPA liability from the schools perspective.

Dip pens are used quite a bit for artwork still. Until very recently (last 10 years or so), dip pens were very much the standard for inking certain types of art, manga especially. The main advantages of a dip pen are the amount of control you have over the line by varying pressure and angle (like a flexible nib fountain pen) as well as the ability use pigment based inks that will clog most fountain pens. Of course digital tablets have pressure and tilt sensors, but without the tactile feedback of the nib flexing and pushing back against your hand, it can be much harder to control. I'm guessing that drawing tablets will eventually have haptic feedback for this reason. The ability to swap out nibs or use a paint brush with the same ink is also very useful.

Not sure about tattoo artists, but Disney has been known to pursue cake decorators / bakeries that uses their IP without a license.

I've found Resolve to be more productive than other video editing programs I've used, primarily because the core operations of navigating through video and cutting clips just feel much more responsive to me. With other editing programs I often feel like the UI is waiting for editing operations to complete in the background, but with Resolve it feels like the UI updates instantly so I can continue working. It sounds like a small change, but it can make a huge difference for productivity since you are no longer waiting for UI confirmation after every action.

Something I see frequently missing from the discussion on roguelikes is the long history of Japanese console roguelikes like the Mystery Dungeon series dating back to 1993. These games have not been very successful outside of Japan but represent some of the earliest successful commercial games inspired by Rogue. They tend to be much closer to traditional "Berlin interpretation" roguelikes (turn-based, grid-based, etc.) than the recent "roguelite" indie games.

To add another item to the list of legal, legitimate uses of YouTube-dl: lots of public domain content is uploaded to YouTube, including a lot of media produced by the US government. For example, The White House has a YouTube channel, and my understanding of US law is that the vast majority of the content uploaded to that channel is public domain (produced by federal employees in the course of their job). Journalists or anyone else wanting to monitor the government would likely find YouTube-dl useful for archiving this public domain content from government channels.

Very cool app--wanted to leave you some feedback after my first test render finished.

Loved the visuals. I can tell that your analysis separates out harmony and percussion as advertised as the video reacts very well to transients in music. This is a common criticism I have of music visualizers--often they don't react to transients quickly enough to communicate the percussion patterns and that's not an issue here.

The whole process creating the video was very easy. Some more control over the images used would be cool, but I'm not sure how that'd work. I do also like that the images are generated and unique for each project. Perhaps if it's possible there could be an advanced feature to upload a pool of images to seed the generation of images. For example, if I wanted to create a video using landscape images of a particular type (mountains, forests, etc), this kind of feature would be very useful.

I'm not sure I'll be a paying customer for this product, as I don't have a commercial use for music visualization at the moment, but I'll be playing around with it some more for sure. I have a big collection of synthesized versions of classical music I created for a project that never materialized, so I can see using this tool to revisit that music and perhaps create videos to share. Thanks for sharing this very cool project!

It could be because of my browser settings / extensions, but I couldn't find any information about the games you can play on the site. It looks like you have to have a paid account to see the list of available games. From a guest account the "Play a Game" page is blank. I would suggest making the games themselves more front and center, as right now the site almost feels like a business-to-business site telling me more about the company itself than the products.