Complete Recordings

Photos are visual. Recordings are auditory. Video combines audio and visuals. Recording experiences are becoming more immersive. Therefore, the next logical step is to record reality that can be played back in immersive virtual environments, or 4D.

This device will record all aspects of a moment, as it is recording for virtual reality. It could capture temperature, vibrations, smell, tastes and more to be replayed in a chamber of some sort.

Concept For Recipe Generation

I was eating at a Japanese restaurant which had some great recipes. The first was an Asian fruit salad made of boiled seaweed, apricot and Granny Smith apples. It was an unexpected blend of textures with its crunchy apple, slick, chewy seaweed and soft apricot. I also tried tomatoes stewed in plum wine, a mildly sweet mango cake and a seafood soup with stewed crab, chicken, shiitake mushroom and clams.

Generally there is an anticipation of what a dish will taste like, but these dishes were unexpected in flavor and texture. That is what the experience of all food should be. Anything less and food is mundane. After eating at the restaurant, I felt the urge to concoct some recipes of my own. I broke down recipes into a template from which new recipes can be generated.

Many foods use the same template. The resulting range of flavors and textures is limited. The flour is used as the neutral base other flavors build on, but there are many other neutral food bases that can be used in desserts as well.

Foods

  • Neutral – Cucumber, seaweed, spinach, cabbage, lettuce, carrot, peanuts, almonds, etc.
  • Sweet – Strawberry, blueberry, orange, etc.
  • Sour – Lemon, lime, etc.
  • Umami – Meat, etc.
  • Salty – Sardines, mackeral, etc.
  • Bitter – Bitter melon, etc.

Flavors

  • Sugar, salt, spices, stimulant (pepper), fragrant (cinnamon, cloves, etc.), oils

Presentation

  • Textures – Smooth, crumbly, chewy, crunchy, stringy, etc.
  • Temperature – Hot, everything in between, cold
  • State – Solid, liquid, gas

Website Relation Web

Create a web application to determine the degrees of separation between two websites using data from Quantcast.com. Type in two website URLs. The program will then input those into Quantcast, and using the Audience Also Likes output, input those for both websites until there is a common website.

Super chill unrelated song. Amazingly smooth voice.

Motorola DROID Commercial

Bean Breeding

Selectively breed beans for maximum size until x (?) generations later, they are tomato sized super beans so large that a couple could be a meal. Would be very cool. No idea how many generations it would take. But once I get a pad I’ll probably start testing until the end of my life. Hopefully the beans will at least have doubled in size by then.

Why beans? Beans are healthy and nutrient dense. They’re delicious. But they’re small, so they’re perfect for breeding.

Real Time Strategy Expansion Flowchart

Because the first strike can easily mean a win for either side, determining the best ways to allocate the resources is important. The top players are skilled simply because they have fine tuned it to a point.

In all RTSs, you can basically harvest resources or build attacking units. Because the rate of resource acquisition and creation of new units is essentially constant, simple flowcharts can be created to determine the various combinations of units for optimal expansion or offensive capability.

Just another idea I will pursue when I’ve got loads of cash, time, an F430, and a nice McMansion.

Music Generator Program Part 1 – Planning

A while back I wrote about a crazy scheme to generate perfect music. I thought about it for a while but never really got anywhere with it. Time to start the “research” phase, if you could call it that. I won’t make it past this step since I don’t have a significant background in music theory, so I won’t be able to analyze the more important musical aspects of these songs.

So here’s a summary of the idea. Music is just a series of different tones. When played in succession and continuously, you’ve got yourself a trippy techno beat, sappy love song or energizing march. So the idea, inspired by the perfect face algorithm, is that universally (95%-99%) pleasing music must have some sort of similarity that makes them pleasing to such a majority of the population.

For now the experiment will be limited to just one culture – American. Obviously we can’t throw in some chart topping Bollywood beats or something. So the description universally appealing will indicate a song that is a chart topper on the Billboard Hot 100. Here’s some more on that. The chart topping songs are selected by sales and airtime. Initially I thought this would be a problem, as only a particular type of person would call up a radio or buy a CD, but it’s probably not a significant demographic group that it would interfere with the results.

Here are some selected some songs that have reached the #1 spot on the Billboard Hot 100 to compare.

  • Flo Rida – Right Round
  • Crank That (Soulja Boy) – Soulja Boy Tell ‘Em
  • Whatever You Like – T.I.
  • Viva La Vida – Coldplay
  • Just Dance – Lady GaGa Ft. Colby O’Donis
  • Low – Flo Rida

There’s a lot of hip-hop on the Hot 100, but I drew extra songs from other genres. Here’s the game plan, or the aspects of the songs to be compared.

  • Song Name
  • Number of weeks on chart
  • Genre
  • Theme (Ex. What is the song mostly about?)
  • Synopsis (Ex. Full blown summary of the lyrics)
  • Tempo
  • My opinion of the song
  • Syncopation
  • Chorus (Ex. Yes or no?)
  • Time Signature
  • Structure (Ex. ABCDABAB)
  • Artist (Expand as needed) – Gender, vocal range, etc.
  • Instrument – Augmented, etc.

I had more features to analyze before. Can’t think of any more at the moment.

Music Generation

A few weeks ago I read an article in the New York Times about a computer program that can “optimize” faces for beauty. It measures and alters symmetry, shape and average distance between different facial features. The program is really remarkable because the improved faces were unmistakably similar and arguably more attractive.

Interestingly, it mentions that there is no perfect face, but I assume this is only because individual faces can only be modified to a certain point before they lose semblance to the original. The generation of a perfect face should be possible because this program proves there are universally accepted characteristics of beauty.

Following the concept of this program, I’m almost certain that “perfect” (universally appealing) songs can be generated. After all, music is nothing but patterns,  there are probably some similarities in the top songs, all of which can be input into a program of some sort. After inputting the characteristics of more songs, the program reaches a point where it can randomly generate music that is “perfect”, or universally appealing to the majority of people, say 99%.

Some current variables I can think of right now are just the basics such as genre, tempo, instruments, time signature, syncopation, vocals, vocal gender. Pandora, Zune Mixview and Apple Genius all suggest music, but none of them generat music.

When I have the time I will definitely pursue this idea in the future. At the moment, there’s too much physics to study.