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Bots Panel

on YouTube 37m
Talkat AI By the Bay 2017 · 2017-03-06..03-08· [ai-assisted-development, machine-learning]

speakers

name:Andrew Burgert
links:none on file
name:David Hall
links:none on file
name:Dennis Yang
links:none on file
name:Pete Skomoroch
links:none on file
name:Sonal Gupta
links:none on file
name:Yishay Carmiel
links:none on file

resources

video:https://youtu.be/SRRIwIHQUFg
slides:none on file

summary

Panelists argue bots already process massive live data and show early wins — 1.2 billion messages processed — but true, flexible conversation that handles common‑sense and complex referring expressions arrives slowly, with useful multi‑turn capabilities in 1–2 years and human‑level understanding more like 5–10 years. Commercial NLU platforms named include Google, Amazon, IBM Watson and Microsoft LUIS; recurring problems are speech recognition noise, limited language coverage and handoff consistency between vertical and general bots, while simple weather and commerce bots drive current engagement.

AI-written summary · about

chapters (9)

  1. 0:00Introduction to Bots Panel
  2. 1:07Panelists Introductions
  3. 3:15Multi-turn Dialogue in Bots
  4. 10:25Vertical vs Generic Bots
  5. 16:41Bots Coordination Challenges
  6. 23:44Will Bots Go Bust?
  7. 28:49Enterprise Bots Potential
  8. 30:14Voice in Automobiles
  9. 33:01Closing Thoughts on Bots

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