Given the situation of job loss, lack of US visa and lack of skill in Artificial Intelligence, what would be Strategic and Operational strategy for an IT service organization With the world moving towards automation in every sector to simplify the process and eliminate the redundancy and dependencies, Artificial Intelligence is further fueling it by targeting to increase the efficiency and scale up the productivity. We now see $160 billion Indian IT Industry is the no exception to it, and are implementing Artificial Intelligence at a much faster pace. Biggies like TCS, Infosys, Wipro and IBM have launched their AI platforms Ignio, Mano, Holmes and Watson respectively. Although the primary reason for implementing the Artificial Intelligence
“The robot is going to lose. Not by much. But when the final score is tallied, flesh and blood is going to beat the damn monster” – Smith. Some scientists believe that robots will surpass humans in intelligence and replace them in jobs by the late 2020’s, making humans either part-robot or extinct. This is unrealistic, however, as robots will not overtake humans in terms of jobs and intelligence.
Both movies share a lot of similarities, probably due to the fact that the books they are based on are both written by Philip K. Dick. In Blade Runner we see a society in which corporations have overtaken the world and technology is so advanced that the corporations have even started creating humanoid robots, replicants, which are disposable servants to their interests. In the course of the movie, however, we start to doubt this practice and how right it is to engineer an artificial intelligence for capitalistic purposes. Blade Runner aims to show the implications of trying to “play God” with technology, ultimately showing that it is not right to do so. Similarly, Minority Report also shows a world heavily dependent on machines and that technology, as helpful as it can be, can also be manipulated, misused and misunderstood when open to interpretation.
Artificial Intelligence can and does benefit us all; however people have constantly warned that making computers too intelligent can be to our disadvantage. Bill Gates and Elon Musk were discussing how we should put a lot more of our effort in Artificial Intelligent safety instead of advancing with it. If not a lot of money is spent more on safety and informing ourselves on the dangerous, we could have very many consequences. Also, in this video, Gates was talking about how if we put everything we know into learning how to improve this machine and all our knowledge, it will become almost as superhuman. There are too many possible negative effects that Artificial Intelligence could have, and we don 't know enough about it yet to continue advancing it.
As more developers understand the potential of software patents, more patents are being issued. Of course, a patent can only be issued when an invention is new, useful, and non obvious. In addition, obtaining a patent on computer software can be an expensive process. The choice of whether to pursue patent protection for a software invention should be made by comparing the value of the program (the potential revenue from its distribution) to the cost of the patent application process and the likelihood of obtaining significant patent
When the wheel was invented people were able to carry heavy objects without exhausting themselves, they were able to trade and build bigger structures. But the reason why science in Brave New World is disliked by the readers is because the way it created a society that is totally controlled by the world state, a society where a ‘race’ of humans is superior to others and a society where family and religion were replaced with science. Science also controlled the emotions of all the individuals. The humans in Brave New World were not considered humans anymore, they were all cloned in laboratories and then conditioned to fit their roles in society. When science is abused to create humans that are so unnatural it then should be considered evil.
Garrod was initially apprehensive in Audi’s self-driving car. Daniel Suarez, a former systems consultant to Fortune 1000 companies, is no exception and disagrees with the TED talk because he is against the evolution and creation of robots with the power to kill. The new technological inventions are taking power and responsibility away from humans and placing it into the hands of the machines. Due to the threat of hacking drones with electromagnetic jamming to change their objectives, we should design drones to know their objective beforehand and react to unforeseen circumstances without any outside guidance (Suarez, 2013). This may increase society’s fears because pre-programming the missions' objectives increase the robots' responsibilities.
Artificial Intelligence and Machine Learning Artificial Intelligence & Machine Learning here we get started!! Now the terms ‘Artificial intelligence & Machine learning’ are closely related and it’s not wrong to say that the abstraction level between these two words is fairly thin line and they can be interchangeably huge. But, when we say AI or ML what most people think is the same old terminator movie : / you think that there’s gonna be some TX9000 machine that’s gonna come up from the future and destroy entire humanity. You start panicking and you going to think that there’s no need of programmers in the future and a lot of queries. Hold on, this is not a fictional movie If this could have been true, so, we should stop
Most of Xerox’s innovation was developed in their Palo Alto Research Center, which was aimed at capturing value from the new market of the computer industry. Xerox created their PARC in 1970, with scientist George Pake recruiting some of the best computing researchers available at the time. The PARC would turn out to be a research success, however, it could not capture value from its technologies. Chesbrough (2003) concluded that Xerox’s problems with the PARC developed from their closed innovation paradigm. Most of the technological achievements that emerged from the PARC could not thrive in a closed paradigm but only in an open context.
Anecdotal evidence suggests the failure to apply software engineering in research development is commonplace and results in expected problems. Prior to our 2002 research  no formal work appears to have been done to examining the level of use of Software Engineering use in academia or its appropriateness. While Software Engineering is seen as a vital industry skill to teach our students, within our departments we have been slow to adopt it. Once adopted it still needs adaptation to better suit the needs of research. 3.