What is a (hard) problem? Can we know which problems do not have solutions? Is scheduling flights a hard problem? Is assembling cars an easy problem? Theoretically, are there more problems (uncountable) than solutions (countably many)? Are algorithms well defined? Are they a finite description for infinitely many possible inputs & processes? What is not an algorithm? Can processes be algorithmic and not computational? Does it matter how algorithms are embodied? Is every algorithm a Turing Machine? Is there a difference between equations and algorithms? Can algorithms be approximate? Where do heuristics come from? Are comparisons the easiest measurement? Do physical symbols always underlie any computation? Are the best algorithms exponential? Is there infinite richness of algorithms, & are computers infinitely reconfigurable machines? How is the real world abstracted (& discretized)? Do problems need analog computing, since (real life) variables are usually (?) continuous and not discrete? Is a recipe, then, an algorithm? Is the brain a computer? Is the world analog or digital? Do algorithms have an ontology? Are algorithms abstractions? Are they here to stay? SynTalk thinks about these & more questions using concepts from logic & theoretical computer science (Prof. Anuj Dawar, Cambridge University, Cambridge), & operations research & industrial engineering (Prof. Ashok K. Mittal, ex-IIT Kanpur, New Delhi). Listen in....

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