Project Oxygen: A Retrospective

1. Project Oxygen: A Retrospective • Larry Rudolph

2. What was it

3. Lessons • Human-centric input: inherently ambiguous • goal is to disambiguate • chop into pieces with meaning • Stepford Wives • input --> recog pieces --> reassembly --> output

4. Lessons • information must flow across abstraction barriers • app --> what is expected • n-best approximation --> app

5. Lessons • State of the world is “stochastic” • most of the time, stuff isn’t working correctly • Multi-modes compensate for errors

6. Lessons • Lots of similarities in diverse fields • Bayesian inference widely used • speech, vision, gestures, handwriting, location, congestion control • Lots of app-specific optimizations • real engineering work, not easily generalized • “Its all the same, but different”

7. Lessons • Location (indoor) is key • Hard to beat commodity items • two heads better than one

8. Things done right (usually by accident) • No one overall architecture • No major standardization effort • Lots of pairwise interactions • Fewer constraints with state-of-the-art systems • Professional videos • very little cheating; real deadlines • Publications in subfield areas -- measurable progress

9. Version 2.0? • “Eat our own sausage” • lots of support staff for internal technology transfer • speech recognition on every desk • free-hand sketching --> powerpoint • comprehension-lite versions • a’la speech builder

10. Brittleness • up and running all the time (not just during demos) • too many publish & subscribe mechanisms • must be able to measure

11. Scenario’s • too much emphasis • for every “wouldn’t it be cool” scenario, there exists a “nightmare” scenario • there is no “cool-meter” or cool-metric

12. Metric for Success of Oxygen? • did it change the world? No • did it help the world change? Yes