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Mon Jan 2 08:37:19 EST 2017
Slept from ten to six-thirty. Woke briefly around three.
High of thirty-eight today. Increasing chance of rain.
Back to work!
Work:
- Remember to turn off out-of-office
Done.
- Debrief with Scott (PR, website, etc.)
Done.
- Update CFO
Done.
- Price out new hypervisor
Done.
- Review invoices
Done.
- Set up backups for doorentry vm
Done.
Huh. The dual-socket Supermicro server boards aren't really any more expensive than the single-socket boards.
Priced out our new commodity hypervisor build at $3200, which isn't bad for 64 GB ECC, 8 cores/16 threads, and 3 TB storage (6 x 1TB SSD RAID 10).
Those boxes would also have significant overhead for hardware upgrades (second processors, much more ram, etc.).
Twenty minute walk at lunch. Pretty nice out.
https://forums.tigsource.com/index.php?topic=40618.0
https://news.ycombinator.com/item?id=10498245
https://www.gamedev.net/blog/2030/entry-2260847-gastropoda-a-snail-simulation/
http://liza.io/snaillife/
> The simulation is based on real life and I’d like to make it as realistic as possible. It’s not meant to be fun or a game (I imagine to most people this is going to be pretty boring and tedious, actually). However, I’m no snail expert or biologist, so I spend time hunting down online articles and research papers about snail life and nutritional requirements. Where I can’t find the necessary information I base a feature on the requirements of humans until something better is found. For example, I found sources about recommended intake of some vitamins specific to snails, but not others. Those I didn’t find any snail-specific information for I based on human vitamin requirements. Of course this is hugely wrong, but it lets me implement the features I need and then go back and tweak the values when I have more accurate information. If a planned feature can’t realistically take place in the real world, it may need to be tweaked.
> So far the brain is in the very beginning stages [...] I check each snail's sensors (olfactory, optical, tactile, gustatory) for any inputs - ie any detected object, whether another snail or item. I then assign input weights to each input based on various criteria like distance, receptor strength/quality, etc. Then I send the input with the highest weight to the attention neuron and then to the recognition neuron, where we check if the snail has any memory of the object it detected (so far no, as I'm not yet storing memories). Then, we decide at random whether the snail is "curious" about the object or not (temporarily random - eventually this will be based on other factors). All of that information goes to the decision neuron, where the snail decides what it wants to do (right now if it curious it simply tries to approach the object). It then fires relevant motor neurons for approach (ie left, right, up, down, based on where the snail is in relation to the object it's trying to approach).
In the evening, I watched a couple of episodes of Dicte, combed through a few Album of the Year lists, and read about data structures.
Breakfast: carrots, yogurt with berries, coffee
Lunch: mixed raw nuts
Dinner: steak sandwich
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