Jul. 21st, 2017 12:14 pm
tensegrity: (Default)
[personal profile] tensegrity
I'm in the final stages of getting an iOS app ready to submit to the Appstore. It's another silly, simple game. The basics are in place, I just need about 4-5 additional pieces of art and to fine tune the play matrix. But I haven't added any sound effects yet. I seriously dislike noisy apps to the point where I normally keep all sound effects turned off on all my mobile devices. And the only thing worse than a noisy app is one with badly done noises. Still games–even simple ones–should be immersive, even for brief episodic use, and adding sound helps that. 

I am not feeling enthusiastic about delaying this app in order to do sound design and source effects for it. I can add them in an update, but you only get one first impression, right? Except this is a free app. It's designed to be simple. The graphics are hand-drawn. The words are minimal. Ugh. Ok, I was planning submitting in early August. That gives me another week or so to finish things up. If I get inspired to design some sounds, then it will happen. If not, it's going ahead without them. Either way, there will be an update to the app before the end of the year–probably shortly after iOS 11 is released.

The next decision is whether or not I want to go ahead and write an Android version of the same app. I should. I just can't muster much in the way of enthusiasm for it. We'll see.

Secret Sauce

Jul. 13th, 2017 08:47 am
tensegrity: (Default)
[personal profile] tensegrity
One of the cool things at WWDC this year was machine learning. Is it a hot dog? Is it a rose? I saw a number of demonstrations and sat through several presentations about how iOS will be able to import a variety of models. Very cool and exciting. But you need to have a trained model to import and creating one is in an entirely different scope. And honestly, every time I've dipped into the programming literature, the math quickly went beyond my comfort level in terms of being able to understand what the heck was going on.

But then I found a pointer to the TensorFlow project, and decided to give it another try. Reading through their tutorials, I started to have a suspicion that I might actually understand what was going on. And then I tracked down this article,, and suddenly it all started making sense. Machine learning is applied statistics, and in its simplest form, it's not even very complex statistics. Which also explained why the trained models they were adding to iOS projects were so very small; the models are just equations. Now, they can be fairly complex equations, but they're just equations.

When they call it machine learning, it's easy enough to assume that the model continues learning as you use it, giving it more data. No, by the time you begin using the model, all the learning is done, at least with the systems I've looked at. The learning part happens when you let the code tweak the equation to better fit what you want to see as a result, and that's where the dangerous part is. There are a number of decisions the model binder has to make and they all influence the outcome of the model, and that's not even touching the quality of the data set or whether the assumed correlation is real enough to be useful. And even if you don't make a wrong step in making and training and tuning the model, it's still dependent upon past data. If the nature of the correlation changes, it will invalidate the model.

All of which is a fancy way of saying that if someone comes to you with a fancy machine learning model, don't treat it like a magical black box, because it isn't. Also, brush up on your statistics if r-squared is still greek to you. Really, it's not that bad, and it can come in handy when reviewing scientific studies or listening to economists.
altamira16: Tall ship at dusk (Default)
[personal profile] altamira16
I saw Grinspoon at The Conference of World Affairs earlier this year. He rambled a lot, mostly about things I like. I bought his book to see if his written thoughts were more organized than his speaking style. There were so many things to like about this book, but I got really bogged down and would have preferred two or three smaller books to this long one. I was hoping that this would be a good place to begin reading about climate change, but it didn't really go too deeply into that.

Grinspoon is an astrobiologist. The field seems like it might be a form of theoretical science or just really deep background on science fiction. In the early chapters, he wrote lovingly about his encounters with Carl Sagan. Sagan was a family friend who inspired Grinspoon in his academic career.

Grinspoon wrote about how we confirm climate models by applying the models to planets other than our own and checking to see if the predictions are correct. He discussed the Gaia hypothesis, and I found the notion of Earth being in a symbiotic relationship with the life that exists on it to be a little odd.

Later, he wrote about SETI and whether or not we should consider METI. If there are aliens out there, should we shout at them and make our presence known? I thought that his discussion about how the probability of finding intelligent life was calculated was interesting. Basically, intelligent life would have to exist for long enough for us to find it and overlap in time with our own civilization. We would not be able to find intelligent life that takes a very long time to develop or life that developed and died before we had a chance to discover it. One way for us to increase our chance of finding other life is to increase our own longevity by maintaining Earth in a way that will sustain humanity.

Throughout the book, he wrote about the Anthropocene, the period of human history affected by human activity. The critique of this is "Have humans been around long enough to be considered on the geologic time scale?" When we talk about the history of the planet, we are talking about millions and billions of years. Humans have just not been around that long. In addition to the Anthropocene epoch (tens of millions of years), he proposed a possible Sapiozoic era (hundreds of millions of years) where the planet is guided by a really smart life form.

One thing that he mentioned toward the end of the book was that the doomsday warnings about climate are going to get some people to disengage and give up and that we must stay optimistic.


itzwicks2023: Baby Bryan (Default)

July 2017


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