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microsoft
BlingFire
C++2019–2021
microsoft / BlingFire

BlingFire

A lightning fast Finite State machine and REgular expression manipulation library.

3Distinct people
4Mentions
0Explicit recommenders
1.9KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A lightning fast Finite State machine and REgular expression manipulation library.

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, 1:49:46 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 month4 dated mentions

Observed mentions: 2019-04-18 00:07:31 UTC to 2021-04-01 17:06:24 UTC.

0122019-04-01 00:00:00 UTC to 2019-05-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 commentsApr 20192019-05-01 00:00:00 UTC to 2019-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-06-01 00:00:00 UTC to 2019-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-07-01 00:00:00 UTC to 2019-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-08-01 00:00:00 UTC to 2019-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-09-01 00:00:00 UTC to 2019-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-10-01 00:00:00 UTC to 2019-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-11-01 00:00:00 UTC to 2019-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-12-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2020-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-02-01 00:00:00 UTC to 2020-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-03-01 00:00:00 UTC to 2020-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-04-01 00:00:00 UTC to 2020-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsApr 20202020-05-01 00:00:00 UTC to 2020-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-06-01 00:00:00 UTC to 2020-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-07-01 00:00:00 UTC to 2020-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-08-01 00:00:00 UTC to 2020-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-09-01 00:00:00 UTC to 2020-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-10-01 00:00:00 UTC to 2020-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-11-01 00:00:00 UTC to 2020-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-12-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2021-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-02-01 00:00:00 UTC to 2021-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-03-01 00:00:00 UTC to 2021-04-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021-04-01 00:00:00 UTC to 2021-05-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsApr 2021

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
Apr 20192019-04-01 00:00:00 UTC2019-05-01 00:00:00 UTC211
May 20192019-05-01 00:00:00 UTC2019-06-01 00:00:00 UTC000
Jun 20192019-06-01 00:00:00 UTC2019-07-01 00:00:00 UTC000
Jul 20192019-07-01 00:00:00 UTC2019-08-01 00:00:00 UTC000
Aug 20192019-08-01 00:00:00 UTC2019-09-01 00:00:00 UTC000
Sep 20192019-09-01 00:00:00 UTC2019-10-01 00:00:00 UTC000
Oct 20192019-10-01 00:00:00 UTC2019-11-01 00:00:00 UTC000
Nov 20192019-11-01 00:00:00 UTC2019-12-01 00:00:00 UTC000
Dec 20192019-12-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
Jan 20202020-01-01 00:00:00 UTC2020-02-01 00:00:00 UTC000
Feb 20202020-02-01 00:00:00 UTC2020-03-01 00:00:00 UTC000
Mar 20202020-03-01 00:00:00 UTC2020-04-01 00:00:00 UTC000
Apr 20202020-04-01 00:00:00 UTC2020-05-01 00:00:00 UTC000
May 20202020-05-01 00:00:00 UTC2020-06-01 00:00:00 UTC000
Jun 20202020-06-01 00:00:00 UTC2020-07-01 00:00:00 UTC000
Jul 20202020-07-01 00:00:00 UTC2020-08-01 00:00:00 UTC000
Aug 20202020-08-01 00:00:00 UTC2020-09-01 00:00:00 UTC000
Sep 20202020-09-01 00:00:00 UTC2020-10-01 00:00:00 UTC000
Oct 20202020-10-01 00:00:00 UTC2020-11-01 00:00:00 UTC000
Nov 20202020-11-01 00:00:00 UTC2020-12-01 00:00:00 UTC000
Dec 20202020-12-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
Jan 20212021-01-01 00:00:00 UTC2021-02-01 00:00:00 UTC000
Feb 20212021-02-01 00:00:00 UTC2021-03-01 00:00:00 UTC000
Mar 20212021-03-01 00:00:00 UTC2021-04-01 00:00:00 UTC101
Apr 20212021-04-01 00:00:00 UTC2021-05-01 00:00:00 UTC101

What Hacker News says

4 sources
Microsoft | Sr. Data & Applied Scientist | Bellevue, WA | Full-time At the Web Data team we're looking for a passionate Applied Scientist to help us on our mission of employing deep learning to understand all the data on the web; the largest store of information in human history. With this understanding we power end-user experiences across a variety of areas, including: • Relevance of search results on Bing.com • Question answering • Recommender systems As a team, we play a central role in document understanding and aggregation of data across documents leveraging the web graph. Work in our team is unique in that you'll be able to work with trillions of documents, which pushes the boundaries of our infrastructure and computational resources. Moreover, it provides interesting challenges that haven't been encountered before, thereby combinin
Read the rest
g research and product applications. Examples of our team's work include: • Revolutionize the field of information retrieval through bridging the gap between end to end dense retrieval and the traditional cascade approach of sparse retrieval with BERT reranking. [https://arxiv.org/pdf/2007.00808.pdf] • Develop the best technology to bring deep learning solutions to unprecedented scale, for example we built the world's fastest tokenizer. [https://github.com/microsoft/BlingFire] • Establish new benchmarks for natural language understanding tasks such as key phrase extraction. [https://github.com/microsoft/OpenKP] We are looking for a passionate Applied Scientist with demonstrable skills in information retrieval, deep learning, natural language processing and/or large-scale distributed computing. https://careers.microsoft.com/us/en/job/990004/
In Ask HN: Who is hiring? (April 2021)
Microsoft | Sr. Data & Applied Scientist | Bellevue, WA | Full-time At the Web Data team we're looking for a passionate Applied Scientist to help us on our mission of employing deep learning to understand all the data on the web; the largest store of information in human history. With this understanding we power end-user experiences across a variety of areas, including: • Relevance of search results on Bing.com • Question answering • Recommender systems As a team, we play a central role in document understanding and aggregation of data across documents leveraging the web graph. Work in our team is unique in that you'll be able to work with trillions of documents, which pushes the boundaries of our infrastructure and computational resources. Moreover, it provides interesting challenges that haven't been encountered before, thereby combinin
Read the rest
g research and product applications. Examples of our team's work include: • Revolutionize the field of information retrieval through bridging the gap between end to end dense retrieval and the traditional cascade approach of sparse retrieval with BERT reranking. [https://arxiv.org/pdf/2007.00808.pdf] • Develop the best technology to bring deep learning solutions to unprecedented scale, for example we built the world's fastest tokenizer. [https://github.com/microsoft/BlingFire] • Establish new benchmarks for natural language understanding tasks such as key phrase extraction. [https://github.com/microsoft/OpenKP] We are looking for a passionate Applied Scientist with demonstrable skills in information retrieval, deep learning, natural language processing and/or large-scale distributed computing. https://careers.microsoft.com/us/en/job/990004/Sr-Data-Appli...
In Ask HN: Who is hiring? (March 2021)

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