The Conjunction Of Artificial Intelligence With Machine Vision

Name Tutor Course Date Machine Vision Machine vision and artificial intelligence (AI) are the today leading innovations. Computer scientists are exploring new edges to machine vision systems engineering and the different fields where the innovations can be applied. The most apparent application has been in different forms of entertainment and the reconstruction of anarchic multimedia, fossils, and technology. This essay examines how the conjunction of artificial intelligence with machine vision will impact perception, the views of researchers and curators on machine vision and the artistic inspiration of machine vision in the future. Bruce Sterling's short story “Maneki Neko” is a humorous science fiction story, which explores the life of Tsuyoshi Shimizu, who recreates archaic multimedia pieces to modern captivating formats. Tsuyoshi who is a self-employed multimedia artist uses image stabilizers, and interlacing algorithms on his fractal detail generator desktop to create better composed, sharper and cleaner products compared to the original copies. Traditional recording mediums lead to productions of videos that had a lot of flaking and polarity loss (Sterling). Recreation of such videos has garnered him a lot of attention online, which has contributed to the creation of a dominant network among him, his fans and other producers who use the internet as a medium to distribute their works. Sterling explores the impact of artificial intelligence on futuristic economies on the internet, legal concerns for information copyrights, and the impact of AI on the social lives through the life of Tsuyoshi. A Maneki Neko is a popular Japanese figurine, which has one paw raised to illustrate an invitation of good fortune. Tsuyoshi uses a Pokkecon, designed as a Maneki Neko, with functions similar to a PDA (personal digital assistant) to organize his life. The Pokkecon organizes the life of the holder in a gift economy, where they may be directed to purchase a product that they end up gifting strangers (Sterling). The good gestures are held in the memory of the Pokkecon and rewarded in the future. The good gestures are viewed like credits that are repaid through gifts from anonymous sources. Similarly, the Pokkecon learns of wrong or impolite actions by an individual and punishes them consciously or unconsciously. However, the gift economy is limited to Tsuyoshi’s dominant network. People who are not members are perceived as foreigners and are attacked by the intelligent systems. For example, Louise, a US legislator, upon arrival in Japan, her PDA got a denial of service attack barring her from communicating with anyone from her home country. In her confrontation with Tsuyoshi, she reveals that she had taken down a part of the dominant network, which would explain the series of unfortunate experiences, including denial of access to her emails, public embarrassments, and the delivery of frustrating presents (Sterling). Louise’s and Tsuyoshi confrontation brings to light the legal concerns of the online economies and the impact they have on people who are members as well as non-members of the online communities. Bruce also gives interesting insights on the conflict that is likely to ensue from the regulation of the online economies by entities who are not members of this community. Additionally, he illustrates the differences between the justice systems in the real world as opposed to the virtual justice systems, which are predetermined by algorithms online. Bruce demonstrates how the dominant networks rely on big databases, indexes, catalogs and sophisticated search engines have unique identification abilities (Sterling). Such abilities are displayed on Tsuyoshi’s walk from the coffee shop when he is directed by the Pokkecon to offer a disturbed stranger the “take away” coffee which it had initially implored him to purchase. Besides the identification of the people associated with the network, the network which functions through the Pokkecon as an interface has the ability to identify one's needs, emotional orientation, and their credit in good deeds or misdeeds. The stranger who got a free cup of coffee must have had good memories in the network datasets, thus the good gesture. In an interview with DIS magazine, Benjamin Bratton confers the limitations and the abilities of machine vision in relation to aesthetics and humanlike traits. Benjamin establishes that artificial intelligence machines do not pose inference, emotion, and allegory, which are inherent traits in human beings (Bratton). However, these qualities are only actualized when a man is interacting with man and not with the machines. Further, he establishes that man is yet to intrinsically comprehend these human traits to an extent where they can render them algorithmically in artificial intelligence. As such, he deduces the inability of AI to exhibit this trait essentially due to the fact that they are yet to be factored in their data sets. Besides the impediments of lacking human-like perception, machine vision still has the capacity to identify individuals. While these inabilities have been a huge impediment to the application of machine vision in the identification of art pieces in terms of genre or their creators, machine vision in the future promises to implement these functions. Bratton establishes that pre-internet art could have been a challenge for machine vision to categorize into genres due to the emotional disconnect (Bratton). However, image vision has developed other traits which have enabled machine visions to identify the different art pieces to form a unique perspective, hence gaining the ability to identify genres. Further, Bratton establishes that seeing ourselves from the machines which cannot acknowledge aesthetic is disenfranchisement. The quality of sapience does not hold any value in the distributed systems cognition. Benjamin deduces that while machine vision fails to acknowledge the value of human life, it is a reflection of the inhuman perceptions of the machine by man. The contrast narrows down to the inability of man to comprehend the factors that make them human and factor them into the AI data sets. However, while in pursuit of the ...