Language as labeling

AI

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  • 1. Asynchronous Message-Passing Systems
    in a.m.p we have message chains, but something make me confues.. processe 1 send message u to process2 in round 1 processe 2 receive msg u from process1 in round 2 processe 2 send msg u' to processe 1 in round 3 why we then can say that in round 3 process1 also receive msg u' from process2 instead of that process1 receive msg u from process2 in round 4.. why there is no round 4
  • 2. potential of AI
    hi, im wondering what kind of commercial/acedamic potential will AI related disciplines have compared with other areas such as nano technology. Im asking this because im planning to seriously learn AI related areas hoping that it will give a good return on investment. im mostly is interested in : Natural Language Processing Speech Recognition / speech synthesis Machine Learning and Neural Networks Knowledge-Based Applications Systems Im currently following "Speech and Language processing" book and "Artificial Intelligence a modern approach" book. i believe combined knowledge of these areas will allow me to build systems that can replace humans (for example automated call centers, automated flight reservation, load planing of power systems, medical expert systems, etc). I know these areas are extremely hard to learn and use, but i've already started learning some of them. one reason for me to ask this questions is that, i downloaded lot of AI related papers from ieee, but most of them are published in 1980 - 1990 period. i could not find any recent papers on them. this made me think the potential of AI has dropped and there are other areas with better potential in computer science? are there any such areas? If you think AI is a good choice, what kind of tools should i learn in order to build real world applications. is prolog a good choice?

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