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metamind.io

Company blog · metamind.io/researchaidata

metamind.io is the company blog at metamind.io, writing about ai and data. Since 2014, 10 different Hacker News readers have linked it 13 times, most often “MetaMind – AI for Enterprise”. No feed was found, so read it on the site itself.

13mentions?
10HN people?
2014–2017first – last linked?
Links on Hacker News per year · peak 5 in 2017

Too few sampled comments (6) to say how often HN recommends it.?

Why HN links it

HN comments link MetaMind, a machine learning company later acquired by Salesforce, for its research pages, a sentiment analysis tool, and a 2016 hiring post. The linked pages are about ML research and products.

Summarised by Claude from a sample of 6 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.

Most-linked posts?

  1. MetaMind – AI for Enterprise
    3 people · 3 mentions · first linked 2014-12-05
  2. Your tl;dr by an ai: a deep reinforced model for abstractive summarization
    2 people · 2 mentions · first linked 2017-05-11
  3. Deep learning with text: Learning when to skim and when to read
    2 people · 2 mentions · first linked 2017-03-15

What Hacker News says?

  1. MetaMind, a Salesforce company | Palo Alto | Full-time | H1B OK MetaMind are a machine learning company. We're interested in machine learning engineers and machine learning researchers who want to push the state of the art in machine learning, both in research and deployment! Our production stack is primarily in Java and Lua/Torch whilst our researchers are highly, flexible using the framework best suited to the tas…

    Comment linking /careers.html

    on “Ask HN: Who is hiring? (July 2016)”
  2. Submitted Deep learning with text: Learning when to skim and when to read as a story · 181 points

    HN discussion
  3. Disclosure: I'm one of the co-authors of the QRNN paper (James Bradbury, Stephen Merity, Caiming Xiong, Richard Socher) produced by Salesforce Research. There are many interesting advances that Deep Voice paper and implementation make but the part I'm excited by (and which might be transferable to other tasks that use RNNs) is showing that QRNNs are indeed generalizable to speech too - in this case in place of WaveN…

    Comment linking /research/new-neural-network-building-block-allows-faster-and-more-accurate-text-understanding

    on “Deep Voice: Real-Time Neural Text-To-Speech”
  4. Submitted Your tl;dr by an ai: a deep reinforced model for abstractive summarization as a story · 120 points

    HN discussion
  5. The space for AI-powered venture-backed companies is really booming. Full list of companies mentioned in the article: Enigma - http://enigma.io/ Sift Science - https://siftscience.com/ Ravelin - https://ravelin.com/ H2O.ai - http://h2o.ai/ Seldon - http://www.seldon.io/ SigOpt - https://sigopt.com/ Gluru - https://gluru.co/ x.ai - https://x.ai/ SwiftKey - https://swiftkey.com/en Matternet - https://mttr.net/ SkyCatc…

    Comment linking /

    on “Investing in Artificial Intelligence”
  6. Submitted MetaMind acquired by Salesforce as a story · 60 points

    HN discussion
  7. Metamind's sentiment analysis tool[1] is probably about the best you can get, especially for short text. Try the "Tweet" version (a tab on that page or available separately[2]). Sentiment on short text is pretty hard. Metamind claims 81.73%[3], although that appears to be for general text (not just Tweets). Anything above ~70% accuracy would be competitive with the state of the art on Twitter data[4]. [1] https://ww…

    Comment linking /classifiers/155/stats

    on “Visualizing Tone in Chat with IBM Watson and a Blink(1)”
  8. Submitted Your tl;dr by an ai: a deep reinforced model for abstractive summarization as a story · 16 points

    HN discussion
  9. Things like topic recognition, entity and reference linking/disambiguation, synonym/paraphase are well researched tasks with purpose-made datasets for competitions like TREC. The most common approaches will be to choose a word embedding (one of the word2vec or Glove are good starts) and run that into a CNN or RNN variant: https://arxiv.org/abs/1702.01923 https://arxiv.org/abs/1611.09100 https://metamind.io/research/…

    Comment linking /research/learning-when-to-skim-and-when-to-read

    on “Ask HN: How to start with NLP”
  10. Submitted MetaMind – AI for Enterprise as a story · 6 points

    HN discussion
  11. The non-Alphabet AI company I am most excited about is MetaMind: https://www.metamind.io/

    Comment linking /

    on “Ask HN: Who/what companies are working on artificial general intelligence?”

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