lsb

26 ms·

271.
by lsb 14y ago
Désolée = sorry, in French.
272.
by lsb 14y ago
SQLite only makes B-Tree indices, not hash or bitmap, and there are no clustered indices, for instance. But there are indices spanning multiple columns, there are ephemeral indices (when doing an n^2 query would be prohibitive), there are s
273.
by lsb 14y ago
You know what'd be cool? To take arbitrary code in a language, pattern match on the implementation in that language of each std lib function, and actively recommend substitutes for duplicated code.
274.
by lsb 14y ago
The "right" way is to take endless numbers of videotapes of what's happening outside the video, and feed them into the biggest and fastest computer, gigabytes of data, and do complex statistical analysis -- you know, Bayesian this and that
275.
by lsb 14y ago
It's beautiful. And it's further a demonstration of how magical Bob Ross was; without his narration, it's just an insipid landscape, if the clouds are not happy and little, and the left cloud does not have the right cloud as a friend.
276.
by lsb 14y ago
I can take credit for winning my city's marathon, but only investigations will reveal the facts.
277.
by lsb 14y ago
This is a really unfortunate treatment of a serious topic. There are valuable insights, but the signal to noise ratio is too low. To be clear, I'm not launching the "I didn't like your TONE"; I'm launching the "I didn't like how you trivial
278.
How to use an untrustworthy social network(slightlynew.blogspot.com)
3 points by lsb 14y ago|0 comments
279.
by lsb 14y ago
What sort of code are you writing? What languages are you using?
280.
by lsb 14y ago
Clicking on the word gives you more info. Blue = not found in GBooks 1grams. Green = high-entropy word. Red = very low-entropy word (<10 bits in a 1gram model). Orange = low-entropy word (<8 bits in a 2gram or 3gram model).
281.
by lsb 14y ago
Yup, check out https://github.com/lsb/passphrase-safety-ui
282.
by lsb 14y ago
1) If you break each word apart, it looks like a false positive for "fuck" being low-entropy, based on "loving" "shit". Click each word to see. 2) It just said it's not in the dictionary. I'm admittedly not doing segmentation, so that's a d
283.
by lsb 14y ago
Yeah, the word list is from Google Books, which isn't exactly as colloquial as people are with passphrases / passwords. Ideally v2 gets trained on blog posts / tweets / other colloquial text sources.
284.
by lsb 14y ago
That looks pretty cool. It seems that it's only single words, not phrases, so you wouldn't catch that adding "man" at the end of "One small step for" doesn't help the entropy of your passphrase.
285.
by lsb 14y ago
Yeah, "arglebargle babelfish supercalifragilisticexpialidocious" is better than "i love you". However, the goal is to memorize it, or otherwise record it, in the end, so you don't want to get stuck typing in nonsense words, because then it'
286.
by lsb 14y ago
I was thinking about creating an Android app with 0 network permissions to do exactly this, but didn't get around to it. Once you've loaded all the 3-grams (~50MB of data), you can run entirely offline, close the page, and then go back onli
287.
by lsb 14y ago
There's no third party! It's all in your browser. You download basically a few bloom filters for low-entropy 1-grams, 2-grams, and 3-grams, and there's some highly optimized Javascript to do probabilistic matches.
288.
by lsb 14y ago
To implement this space-efficiently, I wrote a compressed bloom filter: http://github.com/lsb/gcs It's more space efficient than a standard bloom filter, runs in constant memory on the server, and has pretty fast performance in Javascript
289.
Re XKCD 936: test the safety of your passphrase entirely in your browser(leebutterman.com)
29 points by lsb 14y ago|48 comments
290.
by lsb 14y ago
Ah, but it's all local, with something like a compressed bloom filter doing lookups. So nothing goes across the wire!
291.
by lsb 14y ago
Hm. I've got "It's". Will investigate.
292.
by lsb 14y ago
Yup: the assumption is that it won't even semantically parse. The only way that "correct horse battery staple" even makes sense is with an image and a story! Much as passwords work on the lexical level, and adding random punctuation ensur
293.
by lsb 14y ago
Passphrases are getting a lot more popular, and we can tell how good passwords are, so I wanted to build something similar for passphrases. Let me know what you think!
294.
Show HN: How secure is your passphrase?(leebutterman.com)
9 points by lsb 14y ago|9 comments
295.
by lsb 14y ago
DreamHost is known more for its low prices than its reliability. Look at the blurb on Inktank that starts "Inktank is the company delivering Ceph—the massively scalable, open source, distributed storage system" . Follow the link at the en
296.
by lsb 14y ago
Interestingly, the data storage seems similar to Rich Hickey's Datomic: "data is versioned, and each version is automatically timestamped with its commit time; old versions of data are subject to conﬁgurable garbage-collection policies; and
297.
by lsb 14y ago
Author here. I wanted to explore the GBooks ngram dataset, and see what parts of sentences were less predictable by models, so I made a little visualization.
298.
Show HN: interactive visualization of text entropy(leebutterman.com)
3 points by lsb 14y ago|1 comments
299.
by lsb 14y ago
You'll fold when someone reinvents investment funds?
300.
by lsb 14y ago
Interestingly, this is a great time to see which of your favorite websites are rock-solid and which are kind of shaky. I've been thinking about building a site with a Parse backend, and they're up, which is good to discover.

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