Ajit Jaokar: How many cats does it need to identify a Cat?

Artificial Intelligence , Deep Learning

In his article on Data Science Central of January 5, 2017, TFA Member and Futurist Ajit Jaokar asks the question: “How many cats does it need to identify a Cat?” “This question is in reference to Andrew Ng’s famous paper on Deep Learning,” write Ajit Jaokar, “where he was correctly able to identify images of Cats from YouTube videos. On one level, the answer is very clear: because Andrew Ng lists that number in his paper. That number is 10 million images .. But the answer is incomplete because the question itself is limiting since there are a lot more details in the implementation.” » read more.

In his essay “Twelve types of Artificial Intelligence (AI) problem”, Ajit Jaokar looks at:

  1. Domain expert: Problems which involve Reasoning based on a complex body of knowledge
  2. Domain extension: Problems which involve extending a complex body of Knowledge
  3. Complex Planner: Tasks which involve Planning
  4. Better communicator: Tasks which involve improving existing communication
  5. New Perception: Tasks which involve Perception
  6. Enterprise AI: AI meets Re-engineering the corporation!
  7. Enterprise AI adding unstructured data and Cognitive capabilities to ERP and Datawarehousing
  8. Problems which impact domains due to second order consequences of AI
  9. Problems in the near future that could benefit from improved algorithms
  10. Evolution of Expert systems
  11. Super Long sequence pattern recognition
  12. Extending Sentiment Analysis using AI

Read all about it on Data Science Central or download Ajit Jaokar’s complete essay as PDF.

Gabriele Ruttloff

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