
Ever wondered how computers understand words?
Image: Vadim Zhuravlev, Public domain, via Wikimedia Commons
Ever wondered how computers understand words?
Imagine you're trying to teach your smart speaker to recognize different ways to say "I will go to the store."
The speaker uses a special method to link words that mean the same thing based on how they're used together.
Example
If you say "I will go to the store," the speaker learns to connect it with "I will shop."
Remember this
Word2vec helps computers grasp language nuances by finding patterns in word usage.
Text adapted from Wikipedia, licensed under CC BY-SA 4.0.
word error rate (WER) measures: edit distance between predicted and reference transcriptions
Ever wondered how machines understand speech as we do?
ring attention does: distributes long sequences across multiple devices
How can a machine understand and generate human language?
384-dim all-MiniLM-L6-v2 optimizes: fast sentence similarity with 6 layers
All-MiniLM-L6-v2 optimizes fast sentence similarity with 6 layers
weight tying does in language models: shares embedding and output projection matrices
Ever wonder how machines understand the sequence of words in a sentence?
BPE tokenization does: iteratively merges the most frequent adjacent byte pairs
How do we make computers understand language better?
[CLS] pooling does: uses the first token's embedding as the sentence representation
CLS pooling: uses the first token's embedding as the sentence representation
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