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New
The latest blog posts to take off on Hacker News. 326 posts.
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Prodigy: A new tool for radically efficient machine teaching
Machine learning systems are built from both code and data. It's easy to reuse the code but hard to reuse the data, so building AI mostly means doing annotation. This is good, because the examples are how you program the behaviour – the learner itself is really just a compiler. What's not good is the current…
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Transitioning entirely to neural machine translation
Visit the post for more.
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A Comparison of Distributed Machine Learning Platforms
This paper surveys the design approaches used in distributed machine learning (ML) platforms and proposes future research directions. This ...
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Visualizing the Math Behind Logistic Regression and Newton's Method
The Laziest Programmer - Because someone else has already solved your problem.
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Lessons Learned from Benchmarking Fast Machine Learning Algorithms
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A Guide to Synthesizing Adversarial Examples
Synthesizing adversarial examples for neural networks is surprisingly easy.
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The Road to Superintelligence (2015)
Part 1 of 2: "The Road to Superintelligence". Artificial Intelligence — the topic everyone in the world should be talking about.
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Agents that imagine and plan
Imagining the consequences of your actions before you take them is a powerful tool of human cognition. When placing a glass on the edge of a table, for example, we will likely pause to consider how stable it is and whether it might fall. On the basis of that imagined consequence we might readjust the glass to prevent…
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Second version of HoloLens HPU will incorporate AI coprocessor
By Marc Pollefeys, Director of Science, HoloLens It is not an exaggeration to say that deep learning has taken the world of computer vision, and many other recognition tasks, by storm. Many of the most difficult recognition problems have seen gains over the past few years that are astonishing. Opens in a new tab…
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Teaching Robots to Understand Semantic Concepts
Posted by Sergey Levine, Faculty Advisor and Pierre Sermanet, Research Scientist, Google Brain TeamMachine learning can allow robots to acquire com...
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Interpreting neurons in an LSTM network
A few months ago, we showed how effectively an LSTM network can perform text transliteration .
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The future of deep learning
This post is adapted from Section 3 of Chapter 9 of my book, Deep Learning with Python (Manning Publications).
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Robust Adversarial Examples
Stay up to speed on the rapid advancement of AI technology and the benefits it offers to humanity.
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Facets: An Open Source Visualization Tool for Machine Learning Training Data
Posted by James Wexler, Senior Software Engineer, Google Big Picture Team(Cross-posted on the Google Open Source Blog)Getting the best results out ...
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The Limitations of Deep Learning
This post is adapted from Section 2 of Chapter 9 of my book, Deep Learning with Python (Manning Publications).
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Machine Learning Crash Course: The Bias-Variance Dilemma
Machine Learning at Berkeley is a student organization at UC Berkeley. Click to read ML@B Blog, by Machine Learning at Berkeley, a Substack publication with thousands of subscribers.