• Skip to main content
  • Skip to header right navigation
  • Skip to site footer
Subscribe for exclusive resources and insights
Becket U

Becket U

The Best Resources for Learning STEM

  • Our Story
  • Subjects
    • Math
    • Physics
    • Computers
    • Microeconomics
    • Game Theory
    • Persuasion
  • Newsletter Archives
  • Requests & Feedback
  • Library
  • Math
  • Physics
  • Computers
  • Microeconomics
  • Game Theory
  • Persuasion

You are here: Home / Computers / Distill – Machine Learning Research Explained

Distill – Machine Learning Research Explained

“Machine Learning Research Should Be Clear, Dynamic, and Vivid. Distill is Here to Help.” If you agree with the previous statement, you should visit Distill.

Learn More

About:

Some benefits of Distill:

  1. A modern medium for presenting research – The web is a powerful medium to share new ways of thinking. Over the last few years we’ve seen many imaginative examples of such work. But traditional academic publishing remains focused on the PDF, which prevents this sort of communication. Example: Reactive diagrams allow for a type of communication not possible in static mediums. Hover over this diagram to see how a neural turing machine shifts its attention over its old memory values to create new values.
  2. New ways of thinking enable new discoveries – New notations, visualizations, and mental models can deepen our understanding. By nurturing the development of such new ways of thinking, Distill will enable new discoveries. Example: An interactive playground for t-SNE dimensionality reduction helps readers develop an intuition for technique and where it is best applied.
  3. Machine learning needs more transparency – Machine learning will fundamentally change how humans and computers interact. It’s important to make those techniques transparent, so we can understand and safely control how they work. Distill will provide a platform for vividly illustrating these ideas. Example: An inspectable RNN handwriting model allows readers to feed in examples and see activations in real time.
  4. Legitimacy for non-traditional research artifacts – Many researchers want to do work that is not easily contained within a PDF, but can’t get the support they need to pursue it. We, as the research community, are failing them by not treating these wonderful, non-traditional research artifacts as “real” academic contributions. Example: Non-traditional contributions often don’t get credit unless authors wrap them with proxy papers. Unfortunately, this multiplies effort and divides attention.
  5. Clear writing benefits everyone – When we rush papers out the door to meet conference deadlines, something suffers — often it is the readability and clarity of our communication. This can add severe drag to the entire community as our readers struggle to understand our ideas. We think this ”research debt″ can be avoided.
TweetEmailLinkedInFacebook

Subject: ComputersType: AI Research, Computer Resources, Computers, Deep Learning, Distill, Machine Learning, Open Source, Research

© 2025 Becket U LLC.
All Rights Reserved. Powered by BizBudding

  • About
  • Sponsorship
  • Terms of Service
  • Privacy Policy

Becket U participates in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising commissions by linking to Amazon.