
AI drives down cost and drudgery of routine patent work - hhs
https://www.ft.com/content/80ae35aa-7711-11e9-b0ec-7dff87b9a4a2
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asdfman123
A fun sensationalized headline for this would be "AI now capable of doing the
work of Albert Einstein."

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aswanson
Lol. They should have ran with that.

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MegaButts
I mean we don't really understand creativity. Maybe that AI will evolve to
invent new physics - after all it spends all its time analyzing inventions for
new ideas. /s

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Ididntdothis
Somehow I have the feeling that like in medical the new technology will not
drive down the cost for the customers of the patent lawyers.

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rayiner
Any cost savings likely will not be very noticeable, in part because the
technology doesn't do very much. It is directed at finding prior art,
classifying inventions, etc. That work already is often outsourced overseas.
The stuff that makes patent legal services expensive ( _e.g._ having an
engineer explain how the invention works so a patent can be drafted) remains
quite outside the reach of existing computer technology.

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cgy1
There are some tools out there that can help with the drafting of patent
applications too. I've seen tools that can predict the art unit the patent
might end up, catch errors in patent applications being drafted, and even
tools that can draft a simple preliminary written description for a set of
patent claims.

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wetherbeei
If you're interested in using patent data for AI, check out
[https://www.kaggle.com/bigquery/patents](https://www.kaggle.com/bigquery/patents)
and [https://www.kaggle.com/ostegm/plotting-similar-
patents](https://www.kaggle.com/ostegm/plotting-similar-patents)

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ivan_ah
Thx for posting this. Very interesting dataset:
[https://bigquery.cloud.google.com/table/patents-public-
data:...](https://bigquery.cloud.google.com/table/patents-public-
data:google_patents_research.publications_201710?pli=1&tab=preview)

Do you know by any chance how the `embedding_v1` vectors were generated? The
data field description says "Machine-learned vector embedding based on
document contents and metadata, where two documents that have similar
technical content have a high dot product score of their embedding vectors."

Could this be word2vec, GloVe, or something else like that? Maybe produced
from the tf-idf-transformed sum of the word tokens in the title+abstract of
each patent?

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wetherbeei
We (I run Google Patents), generated them using Wsabie
([https://research.google.com/pubs/archive/37180.pdf](https://research.google.com/pubs/archive/37180.pdf))
trained on the set of words of the full text -> Cooperative Patent
Classification codes. So summed word embeddings trained for a classification
task, which works well on similarity too.

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nnone
What will happen to the patent system when people start claiming AI generated
patents? Like those generated with GPT-2 on this site:
[https://aipatent.wordpress.com/](https://aipatent.wordpress.com/)

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neonate
[http://archive.is/P2du6](http://archive.is/P2du6)

