When will we have a Rosie of our own?
summary
Overview of where language tech actually is: covers Word2Vec analogy (king − man + woman = queen) and recent neural MT advances, demos like Google Duplex and Facebook DeepText, and hardware work such as IBM TrueNorth: 1M neurons / 256 synapses. Cites behavioral data — people follow robots into danger 70% follow faulty robot — and names practical toolchains to try (TensorFlow, OpenNLP/Microsoft Cognitive, NLTK). Good if you want concrete claims, numbers and usable starting tools.
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chapters (17)
- 0:00Start
- 1:19Who Am I
- 8:38Main Areas of Nlp
- 8:49Optical Character Recognition
- 13:41Accents
- 17:18Pragmatics
- 18:21Ambiguity
- 19:41Where Are We at Now
- 20:52Deep Learning
- 21:22Machine Translation
- 24:17Word Vectors
- 26:19Neuromorphic Computing
- 27:37The Turing Test
- 29:56Google Brain
- 33:48Google Duplex
- 34:20Social Robots
- 36:26Emergency Robot
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