Hugging Face Raises USD 40m for Natural Language Processing Platform
Hugging Face raises USD 40m series B to grow its natural language processing platform, which...
#TensorFlow
Array
(
[post_type] => post
[posts_per_page] => 12
[paged] => 1
[post_status] => publish
[tax_query] => Array
(
[relation] => AND
[0] => Array
(
[taxonomy] => post_tag
[field] => term_id
[terms] => 1463
[operator] => IN
)
)
)
Is TensorFlow ‘for Boomers’? PyTorch May Gain More Ground in Machine Translation
Developers praise PyTorch, Facebook’s open source framework, for its flexibility, speed, and usability. But the...
Photo Gallery — SlatorCon San Francisco 2019
SlatorCon SF 2019 photo gallery including photos taken at the Welcome Reception hosted by CyraCom...
Key Takeaways from SlatorCon San Francisco 2019
Industry leaders met at a sold out SlatorCon San Francisco to discuss market opportunities, technology,...
SlatorCon San Francisco 2019: Full Agenda Announced
Over 120 language industry leaders will meet at the language industry’s premier executive forum in...
Slator 2019 Language Industry Market Report
Slator’s inaugural comprehensive language industry market report. It examines total market size, the 10 main...
Is Google’s New Lingvo Framework a Big Deal for Machine Translation?
Neural machine translation experts weigh in on Google’s open sourcing of Lingvo, a sequence modeling...
How Language Featured at the 2019 Applied Machine Learning Days
Language industry startups Unbabel and Lilt took to the stage at one of Europe’s largest...
Amazon Pits Neural Machine Translation Framework Against Google, Facebook, Others
Though Amazon announced its open-source, sequence-to-sequence machine learning framework Sockeye would be available to all...
Google Pitches Tensorflow to Neural Machine Translation Developers
Google publishes a tutorial on how to build a neural machine translation model from scratch...
We Went to Google I/O to See What’s New With Google Translate
Google Translate hides in plain site at annual developer conference. The talk was mostly about...