codekansas

18 ms·

1. 211.▲
   Decoding Gibberish Using Neural Networks(ben.bolte.cc)

   2 points by codekansas 9y ago|0 comments
2. 212.▲
   by codekansas 10y ago

   It's cool how articles like this are able to take a vague feeling that probably a lot of people have and put it in more concrete terms. It is well-written. They mentioned that some post had gotten big enough that it had merited comment
3. 213.▲
   by codekansas 10y ago

   Beyond feelings about the verdict itself, it is interesting that a single lapse in journalistic integrity has the potential to put a major news organization like Rolling Stone out of business. There are massive incentives to publish sensati
4. 214.▲
   by codekansas 10y ago

   On the contrary, the concept of a "neural network" is beautifully cohesive. Many of the architectural differences are only iterative; the fundamental units are very similar. Like how there's a lot of diversity in biology, but
5. 215.▲
   by codekansas 10y ago

   From an ML perspective, recently there's been a lot more work done on language modeling (e.g. billion word corpus). Good language models can usually fix those types of perspective. So hopefully you can expect to see that change in the