Document Analysis NLP IA
WORDS
WORDS
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sentiment
Sentiment0.20418086641491
redaction
Subjectivity0.46481148874766
Affirmation0.38524590163934
Highlights
FREQ, RAKE or TFIDF
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OTHER
- GPU100
- TensorFlow75
- AppleTechnologyEquipmentCompany75
- performanceProcess100
- trainingProcess100
- CPUPart100
- deviceInstrument66
- machine learning53
- bake53
Summary (IA Generated)
A new Mac-optimized fork of machine learning environment TensorFlow posts some major performance increases.
Although a big part of that is that until now the GPU wasn’t used for training tasks (!), M1-based devices see even further gains, suggesting a spate of popular workflow optimizations like this one are incoming.
Announced on both TensorFlow and Apple’s blogs, the improved Mac version shows in the best case more than a 10x improvement in speed for common training tasks.
The change from CPU-only to CPU+GPU could account for a great deal of the improvement, as the benchmarks on an Intel-based Mac Pro show huge gains on the same hardware.
That’s not to say the M1 isn’t capable, but the new M1 Macs also have new GPUs, meaning the jump from nearly 10 seconds for a task on a 2019 MacBook Pro to less than 2 on a new M1 machine can only be partly attributed to Apple’s fancy first-party silicon.
Read the Full Article at TechCrunch