The Future of Artificial Intelligence In Manufacturing

Artificial Intelligence

Several movies have been used to depict AI: the Matrix series, Transcendence (Johnny Depp), iRobot, and Her. These movies show what AI can do. 

The case of the Matrix movies explores the possibility that the world that humans experience their lives in is a simulation. In Transcendence, Johnny Depp’s consciousness becomes a global force to be reckoned with. Finally, the movie Her shows how AI can act as a collective consciousness.

The truth is, we’re far from this level of artificial intelligence. Moreover, we will probably not see the day when AI becomes self-aware unless massive developments in quantum computing exist. 

At this point, we’re still relying on ones and zeroes on software running on hardware that’s smaller than a fingernail. But, thanks to Big Data and the IoT, the patterns identified are used in many different ways. 

What’s surprising is that AI is heavily used to further capitalism, which in itself is not inherently wrong or a disadvantage. Supply chains are shorter thanks to artificial intelligence, and the problem of inconsistency in mass-producing quantities of anything is far fewer thanks to robots and their software implements.

What’s the State of AI now?

There are two categories of AI: weak AI and strong AI. Weak or narrow, AI only performs a single task at a time. For example, chatbots are considered narrow AI since they can respond to sentences containing specific keywords. On the other hand, strong AI, or General AI (AGI), involves machine learning – that is, AGI analyzes and comprehends the problem instead of being reactive or narrow.

When it comes to ASI or artificial superintelligence, it’s still too early to decide whether this would be a feat we can accomplish. Moore’s law allows for the development of smaller and more packed integrated circuits, but there will come a time that new technologies would have to be developed for things to be still physical and practical. ASI will require these new technologies so they can develop. Else, we’re stuck with AGI.

There are jobs dedicated to improving machine learning, and this is what will make AI possible. The first application of AGI will enhance the cost efficiency of materials used to develop the hardware necessary to run the AI. From that point on, it will be easier to create ASI.

The current technology exploiting AGI is Google. Unfortunately, Google’s search engine is one of the most common and unnoticed AGI and machine learning software. This is because the keywords input into the search engine are part of a data set that becomes part of a study done by data scientists, although Google has announced the search engine has a deep learning algorithm.

Right now, AI is not as anthropomorphized, but we’re striving to develop AI that can benefit the whole of society, not just capitalism.

What’s the most advanced AI known by the public?

In the second quarter of this year, NVIDIA announced it had made the most powerful AI supercomputer to help further studies in science. It’s being housed in the US National Energy Research Center. 

It’s though that the capabilities of the Perlmutter can make it possible to render a detailed map of the whole observable universe. Perlmutter uses Python-based language, a programming language finding its way to business services like that of Oracle’s Java from JD Edwards Managed Services.

IBM and Microsoft currently use the largest supercomputers that can run AI. Hanson Robotic’s Sophia was featured on several Youtube videos on how AI can imitate various human expressions. However, Sophia is an example of how tedious it is to make an AGI, requiring several individuals’ input to process the necessary outcome. 

Why is AI necessary?

AI is necessary for the same reason why there are supply chains – efficiency. Incorporating artificial intelligence in everything – medicine, entertainment, manufacturing, and others makes our lives more convenient to a degree. It also speeds up studies, making simulations and iterations of drug testing rather than manually observing mice and recording results. 

Right now, we’re still waiting for Google and other Big Data-driven software to make use of data sets that predict consumer behavior. But, if successful, we might see a future where AI manages the whole agricultural industry to help maximize food production based on available resources.


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