Mike Tamir Interview
summary
Argues that recent progress ties specific deep learning methods to capabilities: convolutional neural nets drive image recognition, 1D convolutions push speech‑to‑text (Baidu work), and Q‑learning plus neural embeddings enable dialog and long‑term customer interaction. Describes using neural recommenders and user‑understanding models in enterprise backends and frames the remaining gap as the lack of a single integrated system that simultaneously senses, understands, and interacts. No demos or numbers given.
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