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Industrial and Commercial Uses of Artificial Intelligence

Michael BrostDepartment of Computer Science

University of Wisconsin – Plattevillebrostm@uwplatt.edu

Abstract

There are few areas of society that has grown and increased at the rate computers have. The machines we make are becoming faster and more efficient than what most even thought possible. The concept of artificial intelligence still pushes the imagination of the human spirit and is trying to be implemented in our everyday lives with newer inventions and smarter programming. Traces of AI can seen everywhere in our lives from the phones we talk on to the cars we drive. It seems every day there is a new product that mimics what a human could do and begs the question … will we truly ever reach a sentient being in regards to technology?

Introduction

Throughout the 1900's computers have been evolving at a rapid pace. One of the original questions and concerns of computing dealt with the question “if computing could advance to the level where a computer could actually think?” In the 1940's, works done by the likes of Vannevar Bush and Alan Turing (who later for the Turing Award was named after and is equivalent to the “Nobel Prize of Technology”) published papers discussing computer systems on the potential for computers to enhance human thinking and help the mind push the limits of what it could do.

Turing would later write about computers being able to simulate and mimic human thought. His paper explained his idea of what he called simply “The Turing Test”. In this test, the test subject would interact in a “conversation” with both a human and a machine. The machine was programmed with limited responses, yet at the same time would answer quite close to its human counterpart. All interactions are done via keyboard and screen to keep the identity of both the other human and computer from the test subject. The goal of the test subject is to see if he can differentiate between his fellow man and distant machine [1]. This idea would spark a wave of interest in the potential of artificial intelligence.

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Figure 1&2: Two of the pioneers of Artificial Intelligence. (Left) John McCarthy [I] and (Right) Alan Turing [II]

The surge of excitement continued post World War II. The term “Artificial Intelligence” was first used by a computer scientist and MIT graduate named John McCarthy back in 1956. McCarthy had organized the very first conference to discuss this concept of computer thinking with other professionals of the like. This concept caught the attention of computer scientists, mathematicians, and many other professionals. The idea of Artificial Intelligence had sparked the imagination of people everywhere. People where now questioning what the capacity of computing would hold.

The Power of Machine or The Power of the Mind

It is evident that computers can process information. Computers continue to grow and advance at an astounding rate. Despite its impressive advancement the question remains; can a supercomputer ever process information as well as a human? The top super computer in the world right now is the Cray Titan supercomputer. This machine currently takes up 4,352 square feet of space and contains 18,688 nodes. This machine has recently crushed the former title holder, the IBM's Sequoia, for world's fastest supercomputer by doubling its performance [2].

Figure 3: the top supercomputer in the world. Averaging 17.6 Petaflops (reaching up to 20), Cray's Titan supercomputer is the fastest [III]

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This was quite an impressive feat. Sadly, the Titan supercomputer is still no match for the human brain. At a massive 88.5 cubic inches, the current comparison of computations isn’t even close. About fifty times faster, the current human brain processes information at roughly 1 exaflop (1,000 Petaflops) compared to the Titan maxing out around 20 Petaflops [3]. Using this logic, we are still quite a few years away from harnessing the true potential power of the mind and simulating it with a computer.

That being said, Moore's law states the chip performance doubles about once every 18 months. If this trend were to continue with supercomputers author and expert in the AI field ,Ray Kurzweil, states that we can see supercomputers performing at the same rate as the human brain as soon as 2023 and the entire human race by 2049[4].

Figure 4: a table illustrating the advancement and cost of computing showing when it is estimated computing will reach the calculations per second a human mind can do [IV]

The Chinese Room Argument

Hypothetically, what if a computer could output the same amount of calculations a human brain could. The mind can process information, but then again so can a basic calculator. The next question to ask is “Would the computer actually know what it was doing?” This idea leads to the theory known as the Chinese Room argument. The Chinese Room argument was thought of by an American philosopher named John Searle. His theory discussed the awareness of such a machine and if reaching a level of true thinking ever exists. Searle described his argument as such:

“Imagine a native English speaker who knows no Chinese locked in a room full of boxes of

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Chinese symbols (a data base) together with a book of instructions for manipulating the symbols (the program). Imagine that people outside the room send in other Chinese symbols which, unknown to the person in the room, are questions in Chinese (the input). And imagine that by following the instructions in the program the man in the room is able to pass out Chinese symbols which are correct answers to the questions (the output). The program enables the person in the room to pass the Turing Test for understanding Chinese but he does not understand a word of Chinese.”[5]

Many rebuttals and arguments have been formulated supporting or rejecting Searle's theory and the subject has been up for debate ever since. Currently there is no way to prove if computers truly ever will fulfill the complete definition of “Artificial Intelligence” and precisely mimic the human brain.

Search Algorithms and Artificial Intelligence

Algorithms have been developing hand in hand with the growth of artificial intelligence. Algorithms started with the older simplistic search algorithms used to search records and have developed into the more complex evolutionary algorithms that are integrated in current AI technology today. To this day one of the most identifiable algorithms we know of is Google's PageRank.

While the first search engine to hit the internet came in 1993, the “W3Catalog” search engine was highly inefficient. In 1996 Larry Page and Sergey Brin collaborated in creating their own search engine “BackRub” which would soon change its name to “Google”. After only two years Google would be named in the list of “Top 100 Web Sites and Search Engines for 1998” [6].

Growing at a rapid pace, Google would make the choice to go public in 2004 and become one of the biggest talks of the tech world. Following their core principles such as “It's best to do one thing really, really well” and “Focus on the user and all else will follow”, Google has continued to improve and advance its market share over the web world handling roughly two thirds of the U.S.'s internet searches.

Figure 5: Co-Founder's Sergey Brin (Left) and Larry Page (Right) outside the Googleplex (Google HQ) in Mountain View, California [V]

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What truly set Google's search engine apart from the competition is the trademarked PageRank algorithm developed by both Page and Brin. Using a series of formulas the algorithm deciphers and ranks websites based on location of the website, length of time the page has existed, and the number of pages linked to the searched website entered. Utilizing PageRank, Google was able to acquire much faster results while also obtaining some of the most preferred results from its users.

Figure 6: This illustration demonstrates the popularity of a web page using the trademarked “PageRank” algorithm that acquires a higher score with the more pages linked to it [VI]

Since then Google has updated and adapted its PageRank system. Due to the popularity of internet queries and trends, Google will reference your current text and offer a suggestion of the search you are looking to enter. If you have an account with Google and are logged in, Google's algorithm will take the process a step further and compare the entered text to previous searches as well and offer similar suggestions.

Current AI in Business

Currently, Artificial Intelligence is defined as “The theory and development of computer systems able to perform tasks that normally require human intelligence”. This definition included everything from a basic calculator to robots that mimic human movement and interaction.

In 2010, the idea to bring artificial intelligence to Wall Street had officially come to life. An upstart company by the name of “Rebellion Research” has been leaving its investments on the stock market up to a machine. The company is made up of a bunch of computer gurus and math standouts. By adjusting their algorithms accordingly, the program will buy and sell stocks for their hedge fund which is currently worth in the upwards of $7 million. Spencer Greenberg,

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current CEO and Chief Software Architect explain the vision and idea behind their business plan. "It's pretty clear that human beings aren't improving, but computers and algorithms are only getting faster and more robust." [7]. Rebellion Research is still trading on the market to this day setting a trend that many more traders have begun to follow.

Moving Forward

It has been theorized and even joked about over and over again how machines will eventually replace human labor in the workforce. Even back in the 1960's, the popular cartoon show “The Jetsons” portrayed people having all their tasks and duties are being done for them. But what about today in the work force? Will self-automated machines eventually replace human labor? And what about the jobs that require human thought and judgment?

Many feel the next step after the artificial intelligence we have today is taking AI and combining it with what is known as ambient intelligence. Ambient intelligence is defined as electronic environments that are sensitive and responsive to the presence of people. Forms of ambient intelligence already exist such as voice recognition software located within your phone or in gaming consoles such as the Xbox Kinect. By combining technologies such as sensors, cameras, and ubiquitous computing techniques among many others, many unforeseen inventions and possibilities may be closer than once thought.

Figure 7: a group of friend's play the popular Xbox Kinect utilizing the Kinects motion detection capabilities and it's infrared sensors to detect depth [VII]

The Blind Driver

On June 29th, 2011, Nevada's DMV did something that has never been done. The DMV had issued the first license ever … to a car. Google made headlines with its project to create the first ever driverless car. This vehicle utilizes a laser used to create a 3D mapping of the environment around it using a plethora of data points and infrared reflectivity. With this information the car can spot obstacles to avoid. Combine this mapping with four radars to help the vehicle merge into traffic and direct it when to start and stop. The car also utilizes a GPS to track its location to

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help monitor its current speed. Finally the vehicle tracks the steering wheel's current position using a wheel encoder.

Figure 8: A driverless Google Vehicle labeled with its additional features [9]

Sebastian Thrun, head of Google's driverless car project, explains that the laser on gathering environment information tracts certain aspects of the environment around it. Its data points tracks the elevation around it, the lane shapes and features, and static points located over time that could be confused as a pedestrian or a pole. Over time the data is accumulated and stored for future reference[8].

Figure 9: The figure demonstrates inputted data from the Google driverless car distinguishing between other vehicles, stationary objects and smaller moving objects such as pedestrians [9]

The vehicle has algorithms programmed to handle all sorts of situations. It is programmed to handle all sorts of intersections, handle the “late pedestrian” sprinting across a “no cross” cross walk, and even recognizes and adapts to poor driving habits of other drivers. Thrun continues to to state the driverless car can reduce traffic accidents by 90%, reduce wasted commute time and energy by 90% and reduce the number of cars by 90%[9].

Based on statistics gathered by the auto insurance company AAA, their 2009 report “Crashes vs Congestion: What's the Cost to Society” states about $450 billion is the total amount of costs associated with crashes in the United States[10]. This means that if Google's claims are true, $400 billion in revenue could be saved each year. On top of that, 27,000 lives would be saved

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each year and 1.8 million injuries would be avoided. The potential the automated car has for the good of society is beyond measure.

The driverless car has since driven over 300,000 miles and three other states have passed laws allowing this concept of the driverless car.

Conclusion

Although we may be decades away from the theatrical vision of “The Terminator”, the idea of artificial intelligence is still nothing to disregard. Technology is getting closer and closer to mimicking human decision making and simulating thought. Inventions such as the driverless car are just the beginning as humans continue on our quest for an easier life. There are some that feel the idea is just a myth and a hopeless dream. There are others who feel the sky is not only the limit, but within arms reach. Only the future will tell if true AI will ever exist. One thing is for sure though, we are in for an exciting future.

References

[1] Smith, Cris. (2006, December). The History of Artificial Intelligence. History of Computing – University of Washington. Retrieved from http://www.cs.washington.edu/education/courses/csep590/06au/projects/history-ai.pdf

[2] Feldman, Michael. (November 12, 2012). Titan Knocks Off Sequoia as Top Supercomputer. HPC Wire. Retrieved from http://www.hpcwire.com/hpcwire/2012-11-12/titan_knocks_off_sequoia_as_top_supercomputer.html

[3] (2013). Introducing Titan: Advancing the Era of Accelerated Computing. Retrieved from http://www.olcf.ornl.gov/titan/

[4] (2007, September 9). Can Computers Beat Human Programmers?. Software Creation. Retrieved from http://softwarecreation.org/2007/can-computers-beat-human-programmers-part1-gaining-processing-power/

[5] Cole, David. (2013, Spring). The Chinese Room Argument. The Stanford Encyclopedia of Philosophy, Edward N. Zalta (ed.), Retrieved from http://plato.stanford.edu/archives/spr2013/entries/chinese-roCrafting and Executing

[6] Strategy: The Quest for Competitive Advantage Concetps and Cases 18e (2012), (Thompson, Peteraf, Gamble, Strickland) 174-193.

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[7] Patterson, Scott (2010, July 13). Letting the Machine Decide. The Wall Street Journal. Retrieved from http://online.wsj.com/article/SB10001424052748703834604575365310813948080.html?mod=WSJ_hpp_LEFTTopStories

[8] Urmson, Chris and Thrun, Sebastian. How Google's Self-Driving Car Works[Video]. Retrieved from http://www.youtube.com/watch?feature=player_embedded&v=YXylqtEQ0tk#!

[9] Mui, Chunka. (2013, January 22) Fasten Your Seatbelts: Google's Driverless Car is Worth Trillions. Forbes. Retrieved from http://www.forbes.com/sites/chunkamui/2013/01/22/fasten-your-seatbelts-googles-driverless-car-is-worth-trillions/

[10] Cambridge Systematics, Inc. (2011, November). Crashes vs. Congestion: What's the Cost to Society? Retrieved from http://newsroom.aaa.com/wp-content/uploads/2011/11/2011_AAA_CrashvCongUpd.pdf

[11] Kanellos, Michael. (2003, February 3) Moore's Law to Roll on for Another Decade. Cnet. Retrieved from http://news.cnet.com/2100-1001-984051.html

Images and Figures

[I] New York Times. (2011, October 25). [A picture of one of the figure heads of AI, John McCarthy]. John McCarthy, 84, Dies; Computer Design Pioneer. Retrieved from http://graphics8.nytimes.com/images/2011/10/26/business/MCCARTHY-obit/MCCARTHY-obit-articleInline.jpg

[II] Huffington Post. (2012, April 4). [Alan Turing as a young man]. Alan Turing's Death Shows 'Cost Of Intolerance Is A Loss To The Nation' Says GCHQ Boss Iain Lobban. Retrieved from http://i.huffpost.com/gen/801189/thumbs/a-ALAN-TURING-640x468.jpg?6

[III] Knox News (2012, November 14). [The Cray Titan supercomputer as a whole]. Cray Titan headed ranking the most powerful super computer (Translated). Retrieved from http://eizvestia.com/wp-content/uploads/2012/11/1352799595_1.jpg

[IV] Software Creation. (2007, September 9). [A chart illustrating previous trends of computing using the “Calculations per Second per $1,000” as the Y axis and year as the X axis. Retrieved from http://softwarecreation.org/images/2007/ComputingGrowth.jpg

[V] Guardian Media. (2008, July 13). [Sergery Brin left of other Google Co-Founder Larry Page]. The Media 100 2008. Retrieved from http://static.guim.co.uk/sys-images/Media/Pix/pictures/2008/06/30/BrinPage460.jpg

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[VI] Rafferty Pendery: Internet Marketing Consultant. (n.d.) [Figure represents the connections and references between website pages]. How Page Rank Works. Retrieved from http://www.raffertypendery.com/images/page-content/page-rank-graphic.jpg

[VII] Digital Trends. (2013, February 21). [A group of friends playing and demostrating the camera interactive Xbox Kinect video game]. Rumored specs for Kinect 2 describe a far more precise motion controller for Xbox 720. Retrieved from http://graphics8.nytimes.com/images/2011/10/26/business/MCCARTHY-obit/MCCARTHY-obit-articleInline.jpg