Our Year in Review · Explosion

The year 2021 is coming to an end, and like the previous year, it was shaped by
unique challenges that impacted our work together. For Explosion, it was a very
productive year. We found an investor that fits our strategy, we released spaCy
v3, the work on Prodigy Teams is in full swing, and the team has grown
a lot. So here’s our look back at our highlights of the year 2021.

• 💫 Feb 1: We kicked off February with the big release of
  spaCy v3.0, which features new
  transformer-based pipelines that get spaCy’s accuracy right up to the current
  state-of-the-art, and a new workflow system to help you take projects from
  prototype to production. If you’re interested in what spaCy v3 is all about,
  check out our video, where Ines
  and Matt guide you through some of the most exciting new features!
• 🪐 Feb 1: As an add-on to our spaCy v3 release, we published
  spaCy projects, which allow managing
  end-to-end spaCy workflows for different use cases and domains.
• 📺 Feb 1: Along with spaCy v3, Ines published the
  behind the scene spaCy v3 design concepts
  video.
• 📺 Feb 1: Sofie celebrated the release of spaCy v3 with her tutorial on
  implementing a
  trainable entity relation extraction component in spaCy v3.
• 📺 Feb 3: At the
  Contributing.Today meetup
  with Guido van Rossum, Sofie presented the new
  spaCy v3 features.

• 💫 Mar 4: We released 1.0 of our
  spaCy and Stanza package, which
  allows you to use the latest Stanza (StanfordNLP) research models directly in
  spaCy.
• 📺 Mar 17: March saw
  a new episode of Vincent
  Warmerdam’s “Intro to NLP with spaCy” series. In this episode, Vincent
  showcased the project system of spaCy v3.
• 📺 Mar 29: Ines joined the at the German Python Podcast to talk about
  Natural Language Processing with spaCy.
• 🥳 Mar 30: At the end of March, we celebrated that spaCy reached
  20k+ stars on GitHub.

• 📺 Apr 22: Ines was invited as a guest on Microsoft’s
  A bit of AI show to talk about
  her journey into AI.
• 📺 Apr 30: Later that month, Ines joined the
  Snorkel Science Talks.
  She discussed her path into machine learning, fundamental design decisions
  behind spaCy, and the importance of bringing together different stakeholders
  in the machine learning development process.

• 💫 Jul 7: We released spaCy v3.1,
  which allows using predicted annotations during training. In addition, the
  release includes a SpanCategorizer component for predicting arbitrary and
  overlapping spans. You can create training data for it using Prodigy’s new
  annotation UI for overlapping spans.
• 🤗 Jul 13:
  Hugging Face welcomed spaCy to their Hub.
  You can now upload any spaCy pipeline using the
  spacy-huggingface-hub
  CLI, with auto-generated pretty READMEs and a interactive visualizers to try
  your pipeline in the browser.
• 🥳 Jul 14: Sofie became
  team lead for
  spaCy.

• ⚙ Aug 12: We’ve partnered with Weights & Biases and the tracking of
  reproducible spaCy NLP pipelines
  became even easier.
• ✨ Aug 12: We released
  Prodigy v1.11, which includes a
  bunch of new features, including a new installation process via pip and new
  wheels for Python 3.9 and ARM architectures, a new recipe and UI for
  annotating overlapping and nested spans,
  new recipes for improving a sentence recognizer model, further training and
  data export recipes that seamlessly integrate with spaCy’s config system.
• 📺 Aug 17: Ines was live on the radio and joined the
  Byte Into IT show on Melbourne’s Triple R radio
  station.

• 💥 Sep 2: A big moment for us – we sold
  5% of Explosion.
  Since founding Explosion in 2016, we’ve run the company as a profitable
  business. Our next step is Prodigy Teams, and doing this project well is much
  more important to us than doing it cheaply, so we decided to consider an
  external investment. With SignalFire, we found an
  investor that fits our strategy.

• 💫 Nov 5: We released spaCy v3.2,
  which improved performance for spaCy on Apple M1 and Nvidia GPU, added Doc
  input for pipelines, and provided registered scoring functions.
• 🍏 Nov 5: Along with the new spaCy 3.2, we published our
  thinc-apple-ops package to
  accelerate spaCy on macOS by calling into Apple’s native “Accelerate” library.
• 🌸 Nov 5: We also presented Adriane’s recent work on our new
  floret library, which uses fastText
  and Bloom embeddings for compact, full-coverage vectors with spaCy.
• 🌳 Nov 17: In mid-November, Daniël presented our new experimental machine
  learning-based lemmatizer
  that posts accuracies above 95% for many languages.
• ✍️ Nov 17: Our machine learning engineer Lj Miranda published a
  detailed technical overview
  on using spaCy’s project config system, traversing our stack in increasing
  levels of abstraction.
• 🛡️ Nov 17: The Guardian
  wrote about
  how their data science team used spaCy and Prodigy to
  train a machine learning model that helps extract quotes from news articles
  and match them to the correct source.
• 📺 Nov 30 Weights & Bias hosted an
  AMA with Ines, where she talked
  about software development, Python, startups and product building.

• ✍️ Dec 8: For
  KDNuggets,
  Ines shared her perspective on AI and Machine Learning developments in 2021
  and key trends for 2022.
• 🏫 Dec 9: We’ve updated our interactive
  NLP course for spaCy v3! The updated course is
  available in English, Spanish, German, and Japanese. More languages will
  follow.
• ✍️ Dec 14: To demonstrate the performance of spaCy v3.2, Adriane compiled
  a series of UD benchmarks
  comparable to the Stanza and Trankit evaluations on Universal Dependencies
  v2.5.
• 🦑 Dec 15: Our machine learning engineer
  Edward published his
  blog post on Healthsea, an end-to-end
  spaCy pipeline to
  analyze user reviews to supplementary products and
  extract their potential effects on health.
• 📺 Dec 17: Ines was invited as a guest on the TalkPython podcast to
  discuss
  machine learning ethics and EU laws.

With the community and the team continuing to grow, we look forward to making 2022 even better. Thanks for all your support!