Difference between revisions of "Blog - 20 Must Knows About AI"
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Revision as of 10:53, 18 July 2021
Return to AI Research
1. What is AI? Certain vs. Uncertain
2. How does AI get its intelligence? Expert System (algorithms) vs. Machine Learning
3. Is AI going to be smarter than humans? Artificial General Intelligence vs Billions of Narrow AI
4. What can AI do? Cognitive Assistance vs. Autonomy
5. Where is AI Working? - Selling us stuff
6. How does machine learning learn? ML, DL & RL
8. What can AI do like Humans?
Use example of chatbots
Conversational UX, Machine Learning, NLP, Sentiment Analysis, Multilingual, Analytics & Administration, RPA, voice bots, cognitive abstraction
Vision, Sound Processing, Sound transmission, NLP, Robotic Physical Automation, RPA, Geospatial, Predicting, Pattern Recognition, Decision Making, Associations, Explainability
8. What can AI do better than humans? Machine Learning Superpowers
Regression
Association
Correlation
Self-play
9. What does AI do worse than humans? AI doesn't know context, takes a long time to learn, needs lots of data
10. Why are Autonomous Vehicles taking so long?
AI Powered Systems - autonomous vehicles, GANs (GPT-3, BERT), facial recognition, language translation, recommender systems, navigation systems, chatbots/virtual assistants,
11. What are the limitations of data? Passive vs. Active Data sets
Passive is collection of data (such as Facebook, Google, Amazon, Netflix) and active would be to ask questions to improve the data sets. An example is long covid sufferers who have 51 possible symptoms. An active data collection would ask the person which symptoms they have to improve the ML model.
12. When will AI become mainstream like the internet?
The progress of AI is beginning to shift from the concentrated AI talent working for tech giants and doing research to almost every sector of the economy. To understand how you and your company can ride this wave and avoid the undertow, the following are the "AI must knows" to leverage the collaboration of AI and humans.
13. What is Intelligent Automation - Robotics (Physical) vs. Process (Digital)
14. Will AI drive Workforce Disruption and Reduction - Citizen Developers
15. What AI is a Must in Managing Complexity - 50 complex challenges
16. Why AI Gives Us a change to Keep Up With Complexity - complexity is growing
17. Why AI Requires Quailty Data Sets - Large for Deep Learning
See blog, some public data sets (ImageNet) have 3% errors.
18. Why AI is biased
19. AI is based on incomplete data
20. AI doesn't understand
21. AI or Humans Can't Accurately Predict an Uncertain Future
