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baidu-research
warp-ctc
Cuda2016–2016
baidu-research / warp-ctc

warp-ctc

Fast parallel CTC.

6Distinct people
8Mentions
0Explicit recommenders
4.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Fast parallel CTC.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by week8 dated mentions

Observed mentions: 2016-01-14 18:34:53 UTC to 2016-03-24 15:52:39 UTC. Weeks start Monday, UTC.

01232016-01-11 00:00:00 UTC to 2016-01-18 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 commentsJan 112016-01-18 00:00:00 UTC to 2016-01-25 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-01-25 00:00:00 UTC to 2016-02-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2016-02-01 00:00:00 UTC to 2016-02-08 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-02-08 00:00:00 UTC to 2016-02-15 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2016-02-15 00:00:00 UTC to 2016-02-22 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsFeb 152016-02-22 00:00:00 UTC to 2016-02-29 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2016-02-29 00:00:00 UTC to 2016-03-07 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-03-07 00:00:00 UTC to 2016-03-14 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2016-03-14 00:00:00 UTC to 2016-03-21 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-03-21 00:00:00 UTC to 2016-03-28 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsMar 21

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jan 112016-01-11 00:00:00 UTC2016-01-18 00:00:00 UTC312
Jan 182016-01-18 00:00:00 UTC2016-01-25 00:00:00 UTC000
Jan 252016-01-25 00:00:00 UTC2016-02-01 00:00:00 UTC101
Feb 12016-02-01 00:00:00 UTC2016-02-08 00:00:00 UTC000
Feb 82016-02-08 00:00:00 UTC2016-02-15 00:00:00 UTC101
Feb 152016-02-15 00:00:00 UTC2016-02-22 00:00:00 UTC000
Feb 222016-02-22 00:00:00 UTC2016-02-29 00:00:00 UTC101
Feb 292016-02-29 00:00:00 UTC2016-03-07 00:00:00 UTC000
Mar 72016-03-07 00:00:00 UTC2016-03-14 00:00:00 UTC101
Mar 142016-03-14 00:00:00 UTC2016-03-21 00:00:00 UTC000
Mar 212016-03-21 00:00:00 UTC2016-03-28 00:00:00 UTC101

What Hacker News says

8 sources
I agree with the general motivation that having too much AI research in the hands of software companies who keep it proprietary harms transparency and progress. But there is already a lot of neural-network free software, so why another package? Not only is there a lot out there, a lot of it was released by companies like IBM[1], Google[2], Yahoo[3], Baidu[4], Microsoft[5], etc. So while I'm generally sympathetic to the FSF's position, this case almost seems like a bit of a reversal of things: there doesn't seem to be a problem with for-profit companies taking the fruits of the labors of volunteers and building on top of it... instead, we have a surplus of riches, released as Open Source by a bunch of big companies. It just happens that most of it is under a permissive license like the ALv2. Of course, one could suggest that that state o
Read the rest
f affairs isn't natural and/or sustainable, and that this doesn't negate the issues the FSF is dedicated to. So I support this effort, even if it seems redundant on some level at the moment. [1]: http://systemml.incubator.apache.org [2]: http://tensorflow.org [3]: http://yahoohadoop.tumblr.com/post/139916563586/caffeonspark... [4]: https://github.com/baidu-research/warp-ctc [5]: https://github.com/Microsoft/CNTK
In GNU Gneural Network
I was thinking the same thing, it almost looks a little too good to be true -- although it does kinda make sense given the focus on GPU-based clusters. I wonder how this compares to Baidu's warp-ctc [1]. They don't really seem to be the same thing, and maybe I'm missing something since I'm just starting to get into ML, but it seems to be conspicuously absent from this writeup. [1] https://github.com/baidu-research/warp-ctc
In Microsoft releases CNTK, its open source deep learning toolkit, on GitHub

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