FYI – I have started my holiday project already!
…I am working on a series of lectures for next generation cognitive curriculum, understanding cognitive systems…
Lecture One: Two Worlds Today: Learning vs Building Cognitive Systems
video: https://youtu.be/S1KD_cliGeU
slides: http://www.slideshare.net/spohrer/understanding-20161128-v8
Lecture Two: One World Coming: Learning By Interacting
video Pieter Abbeel: https://www.youtube.com/watch?v=7NDEzdg-Qsg
slides: http://www.slideshare.net/spohrer/understanding-two-20161212-v2
Next up – what is deep learning and how does it work?
Each two hour lecture will be organized:
First hour:
20 minute lecture with pre-readings assigned + challenge questions and 40 minutes small group discussion
Second hour:
20 minute demonstration + challenge questions and 40 minutes of small group/individual building digital cognitive systems
Feel free to share – I am eager to get feedback, since I am developing fourteen lectures total for an adjunct course I will teach at universities.
The above document discusses 10 of the 14 lectures:
The study of Cognitive Computing requires a BCS (person), DCS (machine), and Tasks (e.g., question-answering, etc.). Every module should discuss <BCS, DCS, Task>to be complete. Two lectures before these ten, and two lectures after these ten – create the 14 lecture/lab series.
Cognitive Computing = AI + IA
AI = Artificial Intelligence – Building DCS to augment BCS on Tasks
1. Learning – auto-complete and spelling correction task
2. Perception – speech and image recognition task
3. Reasoning – question-answering task
4. Interaction – conversation task
5. Knowledge – ingesting textbooks task
IA = Intelligence Augmentation – History of augmenting BCS on Tasks
6. Science – history of the brain and societal evolution [Deacon, Friedman]
(macro-augmentation theory and smarter service systems)
7. Design – history of socio-technical system design loop [Klein]
(micro-augmentation theory and smarter service systems)
8. Business – history of AI & IA in business and applications
9. Ethics – history of AI & IA in law and public policy, and public debate
10. Interdisciplinary – T-shape skills, and history of all disciplines contributing to AI & IA body of knowledge
Classes M-W-F lectures three times a week:
Week 1: M-W-F (1st quiz) – on about this course
Week 2: M-W-F
Week 3: M-W-F (2nd quiz) – on AI section
Week 4: M-W-F
Week 5: M-W-F (3rd quiz) – on IA section
Week 6: M-W-F (final test) – on review this course
Total of six weeks to earn credits.