Artificial General Intelligence (AGI) is the Holy Grail of AI research. Futurists keep speculating about singularity, movies and science fictions are inundated with stories around super-intelligent machines and companies like DeepMind have set an aspirational goal to \u201csolve intelligence\u201d. In this grand quest of creating machines that can \u201cperform the full range of human cognitive abilities\u201d, there are two risks.\n\nFirst, collectively we may be setting ourselves up to an expectation that is based more on belief than on actual state of research. Nobel laureate economist and Turing award winner, Herbert A. Simon, once declared in 1965 \u2013 \u201cmachines will be capable, within twenty years, of doing any work a man can do\u201d. With no unified definition of intelligence or agreement on the types of intelligence so far, we may once again be heading towards a hype around singularity.\n\nSecond and perhaps more importantly, in our eagerness to get a handle around \u201cstrong AI\u201d, which is the other name for AGI, we may be underestimating the power of \u201cweak AI\u201d. Wikipedia says \u2013 \u201cWeak artificial intelligence (weak AI), also known as narrow AI, is non-sentient artificial intelligence that is focused on one narrow task.\u201d The nomenclature of \u201cweak AI\u201d or \u201cnarrow AI\u201d can be misleading and for all practical purposes, the \u201cnon-sentient\u201d nature of \u201cweak AI\u201d need not be viewed as limiting.\n\nApplied AI is not \u201cweak\u201d \n\nThe power of \u201capplied AI\u201d becomes apparent if we look closely at the disruptions faced by the auto industry. Several automakers and technology companies all over the world are attempting to test their self-driving cars. People are no longer talking about the feasibility of autonomous vehicles but instead trying to understand \u201cwho is winning the race to build self-driving cars\u201d. The autonomous vehicle technology is going to disrupt the auto, truck, railways and even airline industries. Boeing has already announced their plan to test pilotless jetliners starting from next year.\n\nThe core technology or AI algorithms required for autonomous vehicles falls under the category of \u201capplied AI\u201d. This technology would not only change the future of transportation industry but also the way people experience travel. With so much of potential to disrupt established industries and markets, there can be little doubt about the immense power hidden in so called \u201cweak AI\u201d.\n\nApplied AI is not \u201cnarrow\u201d \n\nNot only the auto industry, but AI is disrupting various industries including manufacturing, retail, consumer goods, banking, healthcare, telecom and many more. It is changing the lives of people through advancements in computer vision, speech recognition, language translation, sentiment analysis and a host of technologies that take advantage of big data, seamless access through cloud and high processing powers of hand-held devices.\n\nAll such interesting applications that we are aware of are examples of \u201capplied AI\u201d. In addition, the more we use machine-learning algorithms, the smarter these algorithms become. Machines can now learn and beat humans even in tasks that are more intuitive than logical. A widely cited example in this context is the instance when AlphaGo \u2013 an AI based program developed by Google\u2019s DeepMind, defeated a professional world champion in one of the most complex board games \u2013 Go.\n\nApplied AI has unlimited scope \n\nAlmost every job that humans perform can be broken down to specialized tasks that can potentially be performed by applied AI. Venture capitalist and Sun microsystems co-founder Vinod Khosla, in a recent panel discussion hosted by MIT said \u2013 \u201cI can\u2019t imagine why a human oncologist would add value, given the amount of data on oncology\u201d. One HBR article has highlighted how machine learning is improving companies\u2019 work processes. While AI is replacing humans in many jobs, it is also creating new job opportunities, as indicated by Alex Knapp in his recent Forbes article. Even in the fields of writing, music and art, AI has started redefining creativity.\n\nThe scope for \u201capplied AI\u201d is only limited by imagination. With the proliferation of IoT devices, it would be even easier in the future to get the required data for any activity or job and use the same for machine learning purposes.\n\nConclusion\n\nThe nomenclature of \u201cnarrow AI\u201d or \u201cweak AI\u201d does not convey how powerful and broad \u201capplied AI\u201d can be. In fact, all breakthroughs we have seen so far in AI fall under the bracket of \u201capplied AI\u201d. Instead of differentiating the two classes of AI as \u201cweak\u201d vs \u201cstrong\u201d, we can perhaps call these two branches as \u201cArtificial Special Purpose Intelligence\u201d (ASPI) and \u201cArtificial General Purpose Intelligence\u201d (AGPI) respectively.