Entry 8 - Tesla

Tesla:

Elon Musk is the CEO and CTO of SpaceX, co-founder, CEO, and product architect of Tesla. Recently his ingenuity in design, technology, and reinvention with common products has made him one of Forbes’ “Most Influential People”. Particularly Tesla specializes in the production of cars and auto-parts. The difference between Tesla and other car companies is that Tesla is on the way to revolutionizing the common car. Tesla wants to make cars completely electronic in order to rid pollution. Musk states, “Our goal when we created Tesla a decade ago was the same as it is today: to accelerate the advent of sustainable transport by bringing compelling mass market electric cars to market as soon as possible.” Tesla claims that their cars are safer, their products are efficient, and that their model is moving the world towards a greener state.

Relationship to Computer Science:

Being that Tesla necessitates a basis in electrical components, Tesla is extremely related to computer science. Just like your computer, Tesla’s car uses a Lithium Ion battery that requires charge. Since the car is electric it makes certain aspects of the car more efficient. They mention an Autopilot aspect to their new cars which is what it seems, a fully self-driven car that is much safer than the human driven alternative. The car is equipped with cameras covering all 360 degrees with “Twelve updated ultrasonic sensors….allowing for detection of both hard and soft objects at nearly twice the distance of the prior system”. There is also a central CPU that processes this data. It uses radar and sonar detection to allow vision in every single direction. The car, being self-driven, needs to be able to navigate around the map of the world as well. A program created by Tesla uses these sensors to park, drive, and maneuver the car around objects, roads, and parking spaces, all which fundamentally necessitate computer science to do so.

References:

https://en.wikipedia.org/wiki/Elon_Musk

https://www.tesla.com/blog/mission-tesla

http://mashable.com/2013/01/17/tesla-electric-car/#BVIjdwe1_Zqp

https://www.tesla.com/autopilot
https://cdn.arstechnica.net/wp-content/uploads/2015/05/Tesla-Autopilot.jpg

Entry 7 - Computer Generated Imagery

CGI:

The definition of art can range very widely. In my perspective art is about capturing the abstractness of the human mind. Merriam Webster defines art as, “The conscious use of skill and creative imagination especially in the production of aesthetic objects”. Broadly put, art is the production of some type of work that contains some sort of aesthetic. The means of how these images are created can vary widely but as of now the types of objects or images I am talking about are computer generated images (CGI). These are objects that are modeled in order to be animated commonly used in movies but are not specific to just motion pictures.

Relevance to Computer Science:

Computer Generated Images are inherently related to computer science. The means of making a model become a realistic or abstract image is all a result of a CGI program. This programs allows one to have almost unlimited in designing an object or image. CGI is not only used for movies. Like movies, video games require images that constantly generate to provide the graphical interface for the user. There are common medical applications like pulmonary tests where the patient is subject to x-rays and a computer generates an image of the internals of the subject. Another common use of CGI could be for educational purposes. Perhaps modeling a geometrical object or a microscopic section of an animal for a textbook. The relationship of CGI to computer science is obvious but the use of such programs to generate images is far more frequent and useful than we may have thought.

References:

https://www.merriam-webster.com/dictionary/art

http://static4.businessinsider.com/image/537d0e01eab8ea3631d00e9a-/dawn-of-the-planet-of-the-apes-motion-capture%20.gif

https://en.wikipedia.org/wiki/Computer-generated_imagery

Entry 6 - Business

Business:

Everyone understand the concept of business because it is essential in our society. Merriam Webster defines it as, “A usually commercial or mercantile activity engaged in as a means of livelihood”. Whether it be on a small or a large scale each business processes goods or a provides a service in turn for money in order to supply people. Business in general is efficient in the fact that we’ve optimized production in society so that searching for raw materials individually is unnecessary. Trade or exchanges in production can vary in many subcategories as well. For instance, modeling economic trends, producing goods, insurance, or even to companies like private schools. These subcategories are where computer science is relevant to business as a whole.

Relation to CS:

Computer science is essential to business in a myriad of ways. When a business has so many customers is becomes difficult to track or model their customers, their products, or actually run the business at the core (like a website). Most if not all companies need to keep track of what they’ve sold or how much of their product they have in stock. Computer science programming is related to things like databases or websites which control the whole image or the success of a company. This is why most businesses, if big enough, will have an IT sector to their company. These people will handle marketing (social media), security of the business’s information, business growth, and customer satisfaction. Other related CS fields in business include innovations that make customer satisfaction and ease of access increase. These include things like paying by phone, online service, or something like Amazon’s Dash button where you can simply press a button and receive the product of your choosing. Computer science in business has progressed business to where it is now and will continue to do so.

References:

https://www.merriam-webster.com/dictionary/business

https://www.linkedin.com/pulse/role-information-technology-business-success-abid-afzal-butt

https://www.slideshare.net/hunks/grup-1

Entry 5 - Biology

Biology

Biology simply is the study of life. As Dictionary.com defines it, “the science of life or living matter in all its forms and phenomena,especially with reference to origin, growth, reproduction, structure,and behavior”. Common studies or experiments done in biology today include immune systems and cancer development, mechanical, electrical, and molecular interactions in an organism, and DNA analysis, etc. This area of study, as you probably already know, is extremely important to our modern and future healthcare and has produced advancements to allow us to experience our way of life as we do today. However, experiments in these various areas of biology often necessitate highly precise tools that measure the extremely small.

Relation to Computer Science:

Often when studying life, the fundamental driving forces are microscopic, and sometimes molecular. It is hard to directly study extremely small objects with macroscopic objects (like our hands or handheld tools). Computer science has allowed biologists to study the extremely small for many years. A direct use of computer science is for molecular modeling. This would involve programs that simulate a molecule and its interactions based off of the knowledge we already understand about certain molecules. Another, and huge, more seemingly indirect use of computer science in biology is with DNA structures. The DNA structures are not modeled (although they can be) but rather the DNA structures are given to the user through an electronic instrument that runs and analyzes the specific makeup of the DNA strand. Another use of CS is through a database that compares these DNA makeups to others which can be used in law enforcement or continuing studies on DNA in general. Computer science is implemented in an incredible amounts of ways in order for the advancement of biology to continue.

http://www.dictionary.com/browse/biology

https://www.forbes.com/sites/quora/2015/04/22/13-of-2015s-hottest-topics-in-computer-science-research/#7b27ebab1e88

http://www.forensicdnacenter.com/dna-str.html
https://chemicalengineering.byu.edu/images/Department/twophase.gif

Entry 4 - Music Production

Description of Topic:

Music Production, as most of us know, is simply the means of making music. However, this seemingly simple topic is actually incredibly complicated in various ways. Wiki states, Music production (more specifically here, Audio post production) “is the general term for all stages of production happening between the actual recording in a studio and the completion of a master recording. It involves, sound design, sound editing, audio mixing, and the addition of effects”. These sub-topics, especially now, include things like actually creating the sounds that we hear electronically as well as the editing done to the audio in order for it to sound the desired way or for it to be able to be played in a certain setting and in a certain format.

Relation to Computer Science:

Music production relates to computer science (especially in electronically produced music) because the music depends inherently on music software (for instance Logic Pro, Ableton, FL Studio, Garageband, etc.) which is created through programming. Actually, all music today at some point goes through some sort of computer in order to be played electronically (unless you hear the music live and the instrument is not plugged into anything). The process goes beyond just music software but also towards self-made instruments that provide input to computers (Like “a pendulum hanging from an upside-down cup-shaped sensor” that plays organized music when swinging. A “UCSC professor David Cope drew attention and criticism on computer-driven human composers in the ‘90s when he debuted software called EMI Experiments in Musical Intelligence”. This program was able to mimic certain composers style so that it be unrecognizable (which inevitably brought about the question of creativity in music in the future). There are many more computer science related sub-topics in music such an Artificial Intelligence that can create music itself, including vocals, without human interaction. In the modern day most music is extremely closely related with computer science in most, if not all aspects.

References:

http://outfog.com/2013/05/23/algorithm-blues-how-computer-science-and-music-work-in-harmony/

https://qz.com/790523/daddys-car-the-first-song-ever-written-by-artificial-intelligence-is-actually-pretty-good/
https://en.wikipedia.org/wiki/Audio_post_production
https://www.cheersounds.com/wp-content/uploads/2014/04/Booth-bannersize.jpg

Entry 3 - Particle Physics

Description of Topic:

Particle physics is a specific subcategory in physics dealing with subatomic particles and their interactions. Experiments done in this field often require a particle accelerator. An accelerator (as it sounds) accelerates extremely small particles to high speeds and collides them (either with another beam or a still object) in order to study the particles made to give context to the fundamental laws of the universe. The most famous particle accelerator is the circular accelerator called CERN in Geneva, Switzerland. "The name CERN is derived from the acronym for the French Conseil Européen pour la Recherche Nucléaire, a provisional body founded in 1952 with the mandate of establishing a world-class fundamental physics research organization in Europe" -Angles and Demons. The most recent fantastic discovery made with CERN is the discovery of the Higgs Boson, a particle that gives reality to the field (Higgs Field) that gives some particles their mass.

Relation to Computer Science:

Computer science becomes very important to this subject of physics when it comes to particle accelerators (especially big ones). It is essential in producing machines that require high energies needed to obtain certain interactions between particles. Computer science is needed in order to program the electronics (like detectors) and also is used to store information (in server farms) that the millions of interactions and collisions the particle accelerators can produce. The computers used in the facility also require a certain software necessary to analyze the collisions.

References:
https://home.cern/sites/home.web.cern.ch/files/styles/320/public/image/topic-stub/image/higgs_event_display.jpg?itok=H-IZs8wA
http://angelsanddemons.web.cern.ch/faq/what-does-cern-mean

Entry 2 - IT Security

Description of Topic:

Computer Security or IT Security, intuitively, is the general concept of protecting computers against any non-intended use. As Morrie Gasser defines it, “The protection of computer systems from the theft or damage to the hardware, software or the information on them, as well as from disruption or misdirection of the services they provide”. This term is so general that it includes such a myriad of different types of security to protect and involve the following…

Cloud security, which involves data held in server rooms not under your personal management.

Malware protection, which eliminates software or any other type of malicious programs that try to attack a computer.

Phishing, which is primarily a malicious email sent in order to retrieve information illegally.

Encryption, which encodes messages or information that is sent in order for that information to be only readable by the intended user.

And etc.

Relation to Computer Science:

IT security’s relationship to computer science should be apparent in that it directly deals with protecting computers, hardware, and software, all which operate using CS. The difficulty with security is that it is preventing computer science programs with computer science programs, which both usually have either errors or entry ways to access. This promises that both malware and security are not always efficient or 100% protective. However, security is absolutely essential for privacy relevant to any information or program that contains high importance.

References:
https://en.wikipedia.org/wiki/Computer_security
http://www.forbes.com/sites/sungardas/2015/01/15/what-9-cyber-security-buzzwords-and-jargon-terms-really-mean/#449cde685e57
http://security.freshmango.com/wp-content/uploads/2014/09/IT-Security-Icon-Brainstorm-Chart-lr.jpg

Entry 1 - Artificial Intelligence

Description of Topic:

Artificial Intelligence (AI), as Merriam Webster defines it, is  "1: A branch of computer science dealing with the simulation of intelligent behavior in computers. 2: The capability of a machine to imitate intelligent human behavior". The denotation of the words AI literally encapsulate how computers are able to be used to solve problems. The connotation however has inevitably evolved into how humanlike a computer can be or if a computer can obtain consciousness. Some people argue that AI will never have the intelligence like humans do regardless of how well it can mimic human movements and some others argue the complete opposite, that AI could possibly take over the world. As of now, AI, is used everywhere in our daily life (through "Siri-like" and "Alexa-like" software, cars, phones, or, essentially any computer that can make decisions).

Relation to Computer Science:

This topic is actually all about computer science as shown by the Webster definition. These computers are programmed by humans and therefore it is a direct relation to CS. In order for a computer to mimic human behavior it has to follow various algorithms. However, a question I inevitably have then is, how much different does computer science have to be from what we believe it to be now in order to be able code and program consciousness (if this is at all remotely possible)? As it is now, AI is a subcategory of computer science because it deals with computers that come from computer science but does not encapsulate computer science as a whole.

Sources:
1. https://www.merriam-webster.com/ 
2. https://www.technologyreview.com/s/534871/our-fear-of-artificial-intelligence/ 
3. http://cdn.ttgtmedia.com/rms/computerweekly/photogalleries/237178/1411_20_the-honda-asimo-robot.jpg
4. https://en.wikipedia.org/wiki/Artificial_intelligence