Machine Learning & Facebook
Introduction
It could be argued that machine learning is influencing the way we perceive information and think. From customer service software to Google search algorithms, machine learning is already becoming a daily phenomenon that is aiding us towards making better and faster decisions. Machine learning is best defined as an artificial intelligence (AI) approach in which machines are allowed to learn and make further decisions about certain outcomes without programming it to. In this paper, I will further define what machine learning is and by using Facebook’s Messenger Platform as an example, I will showcase how machine learning can be implemented in our everyday life.
What Is Machine Learning? From a technical
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This tool gives companies the power to have better customer service and an easier way to foster a relationship between brand and consumer. In addition, Facebook has also opened the chatbot to developers. Researchers at Facebook Artificial Intelligence Research (FAIR) have open-sourced code and published research that provides developers new dialog agents (Lewis 2017). The availability of the code will give developers the resources needed to build more complex bots that can decipher meanings and continually learn to get better over time (Lewis 2017). This can also help companies give their customers a more unique experience and provide an overall better branding practice for the …show more content…
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This world of artificial intelligence has the power to produce many questions and theories because we don’t understand something that isn’t possible. “How smart’s an AI, Case? Depends. Some aren’t much smarter than dogs. Pets. Cost a fortune anyway. The real smart ones are as smart as the Turing heat is willing to let ‘em get.” (Page 95) This shows that an artificial intelligence can be programmed to only do certain ...
Lewicki, R. J., Barry, B., & Saunders, D. M. (2007). Essentials of Negotiation. New York: McGraw-Hill/ Irwin.
First, advertising accounted for the majority of the revenue. It took up 99 percent of Facebook’s revenues in 2009, 95 percent in 2010 and 85 percent in 2011. The social connections and demographic information of users allowed the advertisers to have opportunities to segment and target these users. The requirement for users to reveal their authentic identities gave companies good opportunities to grasp their information and make money. Facebook created database according to the interests and hobbies of users by mapping the connections between users and their friends and recording the services and products they liked. Based on users’ interests and connections, advertisers could target customized products and
“Is Facebook creating I-disorders” methodically tested if using certain technologies would predict scientific symptoms of six personality disorders and three mood disorders. Examining 1335 adults between the ages of 18-65 in southern California, clinical symptoms of psychological disorders, daily technology and media use, technology related attitudes and technology related anxiety were measured. 4 hypotheses were created and supported by previous studies and questionnaires. 1) Adults who use more social media will show increased clinical symptoms of psychiatric disorders 2) Adults who show more negative attitudes toward technology will show increased clinical symptoms of psychiatric disorders 3) Adults who show more anxiety about checking technologies
Shopping bots are personal agents in embryo, and are currently an exciting development made possible by web-based e-commerce. The functionality of shopping bots is changing rapidly in what is becoming an enormous market opportunity. The war for portals has subsided, and the next battle will be between the search services, including shopping bots, and the actual vendors. Both are competing for the loyalty of the web-savvy consumer. As shopping bots improve, and begin to function more like personal agents and less like search services, they will become an indispensable tool of modern life in the age of e-commerce. One need only look at the revenues of “yellow pages” companies to understand the enormous potential inherent in shopping bots.
The today’s society is living in the digital era, where many companies have transformed itself to serve their customer better. This is an on-going phenomenon that scholars around the world are looking into in the past decades. Berners-Lee (1997) predicted that with the Internet, the most rapid growth would be in public information. He dreamt that someday we would be able to map out the relationships and dependencies that define how the project is going. However, in this essay, we will not be discussing about how the Internet is changing the companies, but rather to talk about the digital native company called Facebook.
In order to see how artificial intelligence plays a role on today’s society, I believe it is important to dispel any misconceptions about what artificial intelligence is. Artificial intelligence has been defined many different ways, but the commonality between all of them is that artificial intelligence theory and development of computer systems that are able to perform tasks that would normally require a human intelligence such as decision making, visual recognition, or speech recognition. However, human intelligence is a very ambiguous term. I believe there are three main attributes an artificial intelligence system has that makes it representative of human intelligence (Source 1). The first is problem solving, the ability to look ahead several steps in the decision making process and being able to choose the best solution (Source 1). The second is the representation of knowledge (Source 1). While knowledge is usually gained through experience or education, intelligent agents could very well possibly have a different form of knowledge. Access to the internet, the la...
With the book of human discoveries flipping its chapters into the twenty-first century, computer science has shown immense growth over the recent years. New versions of artificial intelligence (AI) are constantly being applied toward practical uses. It is becoming a technological
Today, there are approximately two billion active users on Facebook monthly, and 90% of them use emojis when messaging or posting (Oleszkiewicz et al. 2015). More than 60 billion emojis are sent through Facebook every day. In 2015, the Oxford Dictionary first announced the “Crying-Laughing” emoji as the “Word of the Year” instead of the typical string-of-letters word. Undeniably, emojis have become an indispensable part of online social networking. As a new type of “universal language,” emojis simplify our communication and combat language barriers, connecting people all around the world. Due to to emojis, we can now simply send a “smiley face” to express happiness, allowing us to forgo typing a whole sentence or learning another
It is clear that technology becomes an important part of daily life. Especially, the Internet, which is compatible with the style and pace of modern life. More particularly, the Internet development has established new communities in the world, which are social networks. It is websites or applications, which allow people to connect with each other, sharing photos, videos and messages. For example, Facebook, twitter are channels of keeping in touch with friends around the world as well as making new connections with other people based on similar interests.
Humans can expand their knowledge to adapt the changing environment. To do that they must “learn”. Learning can be simply defined as the acquisition of knowledge or skills through study, experience, or being taught. Although learning is an easy task for most of the people, to acquire new knowledge or skills from data is too hard and complicated for machines. Moreover, the intelligence level of a machine is directly relevant to its learning capability. The study of machine learning tries to deal with this complicated task. In other words, machine learning is the branch of artificial intelligence that tries to find an answer to this question: how to make computer learn?
Some machine learning works in a way similar to the way people do it. Google Translate, for example, uses a large database of text in a given language to translate to another language, a statistical process that doesn 't involve looking for the "meaning" of words. Humans, do something similar, in that we learn languages by seeing lots of examples. Google Translate doesn 't always get it right, precisely because it doesn 't seek meaning and can sometimes be fooled by synonyms or differing connotations. (Schapire, 2008) Current and future examples of machine learning include; optical character recognition, face detection, spam filtering, fraud detection, weather prediction and medical
Artificial intelligence (AI) is on the rise as it is integrated into every aspect of our daily lives; from computers, video games, and even kitchen appliances. As humans, we have allowed AI to infiltrate our daily lives as they complete the simplest of task for us, however they are not completed to the best of their abilities. As humans, we are able to complete a task to the prime of our capacity through the combination of our experiences, emotions, and logic. On the other hand, artificial intelligence formulates a conclusion through a series of mathematical equations, numerous numbers of code, and a series of zeros and ones in order to mimic our human capabilities of decision making. Previous experiences and lessons learned from them formulate
Best example on our day today basis is amazon's recommendation for a user while shopping. Machine is learning about a user's web activity and interprets and manipulate it thus by giving best recommendation based on your interests and choice of shopping. To provide this recommendation, the
"Smart work is better than a Hard work." This statement has always helped me in accomplishing my milestones in a better way. The output which I get through smart work is better than the one through hard work. This same statement is now leading me towards the idea what if machines start working smartly which can be certainly achieved by Machine Learning. There can be a huge revolution in the field of technology.