Machine Learning Research
Misleading Metrics: Advances in metric learning may be illusions.
A growing body of literature shows that some steps in AI’s forward march may actually move sideways. A new study questions advances in metric learning.
Latest
Letters
Why We Need H1-B Visas
I was dismayed on Monday to read that the U.S. is suspending the H1-B visa program at least through the end of the year. This effort to discourage immigration can only bring distress to workers from other countries and harm to the U.S.
Letters
Introducing the Natural Language Processing Specialization
I’m thrilled to announce our new Natural Language Processing Specialization! Courses 1 and 2 are available on Coursera. We expect to release Courses 3 and 4 soon. NLP is reshaping daily life.
The Batch Newsletter
The Batch: NLP Special Issue! Powerful techniques from Amazon, Apple, Facebook, Google, Microsoft, Salesforce
I’m thrilled to announce our new Natural Language Processing Specialization! Courses 1 and 2 are available on Coursera. We expect to release Courses 3 and 4 soon.
Interviews & Essays
AI Transformed: A Conversation with Transformer co-inventor Noam Shazeer
Noam Shazeer helped spark the latest NLP revolution. He developed the multi-headed self-attention mechanism described in “Attention Is All You Need,” the 2017 paper that introduced the transformer network.
Tech & Society
Outing Hidden Hatred: How Facebook built a hate speech detector
Facebook uses automated systems to block hate speech, but hateful posts can slip through when seemingly benign words and pictures combine to create a nasty message. The social network is tackling this problem by enhancing AI’s ability to recognize context.
Machine Learning Research
What Were We Talking About?: How Amazon's Alexa keeps up with conversations
Conversational agents have a tough job following the zigs and zags of human conversation. They’re getting better at it — thanks to yesterday’s technology. Amazon recently improved the Alexa chatbot’s ability to identify the current topic of conversation.
Machine Learning Research
Choosing Words Carefully: BLUERT trains language models to be better translators.
The words “big” and “large” have similar meanings, but they aren’t always interchangeable: You wouldn’t refer to an older, male sibling as your “large brother” (unless you meant to be cheeky). Choosing among words with similar meanings is critical in language tasks like translation.
Machine Learning Research
Gender Bender: Double-Hard Debias helps lessen gender bias in NLP models.
AI learns human biases: In word vector space, “man is to computer programmer as woman is to homemaker,” as one paper put it. New research helps language models unlearn such prejudices.
Machine Learning Research
Found in Translation: Apple's method to identify a language from a few words
Language models can’t correct your misspellings or suggest the next word in a text without knowing what language you’re using. For instance, if you type “tac-,” are you aiming for “taco,” a hand-held meal in Spanish, or “taca,” a crown in Turkish?
Machine Learning Research
Bigger is Better: A research summary of Microsoft's Turing-NLG language model.
Natural language processing lately has come to resemble an arms race, as the big AI companies build models that encompass ever larger numbers of parameters. Microsoft recently held the record — but not for long.
The Batch Newsletter
The Batch: AI's Progress Problem, Recognizing Masked Faces, Mapping Underwater Ecosystems, Augmenting Features
Last week, I wrote about the diversity problem in AI and why we need to fix it. I asked you to tell us about your experiences as a Black person in AI or share the names of Black colleagues you admire.