yabun

6 ms·

1.
by yabun 11y ago
The core difference with AI is that it is adaptable. Sure, flailing around and happening to do something useful isn't clever, but if we can reinforce useful behaviours something more closely resembling intelligence can emerge.
2.
by yabun 11y ago
Only if people don't know about the dummies, things tend toward zero sum with awareness of the situation.
3.
by yabun 11y ago
http://www.progonos.com/furuti/MapProj/Normal/ProjPoly/projP... These maps aren't too bad.
4.
by yabun 11y ago
The helium reduces resistance which results in lower vibration of the read/write heads, which in turn allows for reduced space between the platters and the heads, which allows for a reduced space between the platters and more platters
5.
by yabun 11y ago
Deep learning has really only recently become successful with new learning algorithms such as constrastive divergence and convolutional neural networks. Previous efforts were focused around backpropagation, but due to the signal loss across
6.
by yabun 11y ago
Another issue is that when a big drop falls, the small drops that it leaves behind are equally sized and equally spaced.
7.
by yabun 11y ago
OK, but that's a very large data set that to track - does AV software actually do that?
8.
by yabun 11y ago
A lot of new malware is self-modifying. In situations where this is the case checksums lose most if not all of their value. Heuristics in such situations are really the only viable option.
9.
by yabun 11y ago
There really needs to be a change to patent law around independent derivation of a concept. At very least we need to look into generalised thicket busting laws. The current situation is fundamentally unscalable.
10.
by yabun 11y ago
Concatenation of the hashes seems like an unjustified risk, that in certain circumstances will allow weaknesses from either algorithm to flow throw to the final hash. If you really want to combine the hashes, XOR seems like a safer bet to m