UCSB Freshman Seminar “What is computing?”, Fall 2016

Some questions posted by the class after Lecture 5, October 25, 2016

• If memory in a computer was not finite (i.e not a fixed number) would any of these problems remain unsolvable?
• In the traveling salesman example, could that problem actually not be solved, or is it just an example?
• I was left wondering if our knowledge of the limitations of computing could be altered by new discoveries in physics.
• Does the fact that Turing machine is unable to solve first type of questions imply that human's thinking process is more complicated and more capable than a Turing machine? (Because human can prove math theorem)
• Is the Traveling Salesman Problem a physical/technological limitation, given that it deals with speed, time, and efficiency? If not, why?
• Is there a limit to processing speed in computers--if any?
• What do you mean by unsolvable problems in computing and do you think these problems could eventually be solved with the future advancements in technology?  
• To what extent in the medical field is it possible for computers to replace doctors? Some people say that computers can replace doctors completely, for diagnosis, prognosis and for surgical reasons. What would happen if computers replaced doctors?
• What are some other common examples of problems computers can not be programmed to do?
• Are there more limits to computers and computing? Is there a way to speed up the amount of time it takes for a computer to run through problems?
• How can software and hardware limit the efficiency of a computer?
• How can the computers today be improved to be more efficient and run faster?
• Are these limitations because of computers or computing as a concept?
• As our processors speed up, and things can be computed faster, will the scaling problem become less and less - if still always slightly - relevant?
• I am curious about the theoretical implications of being able to build a computer with planck length signal transfer distances. In what most fundamental ways do the computational limits of a quantum computer differ from that of a 'classical' computer?
• What are some other decision problems which computer programs can't solve?

UCSB Freshman Seminar “What is computing?”, Fall 2016

Some questions posted by the class after Lecture 4, October 18, 2016

• How can you know if your algorithm is efficient?
• The question is that I've heard that merge sort needs the use of recursion in programming, is it always trying to compare two already sorted lists and write it as a recursion?
• Could a computer write its own algorithms in its own language? Why does it need a natural language from humans to know what to do? Or, conversely, could it be taught the computer language and use it to create programs for itself (learn it just how, say, Watson could learn things)
• What is Big-O notation?
•  How do you prove that merging requires the fewest steps?
• How do computers sort through different programs?
• How does a programmer decide how to design and implement his or her algorithm (e.g., divide and conquer, brute force, etc.)?
• Are people still programming new algorithms even though they have been designed and used for hundreds of years?
• How exactly are the efficiencies of algorithms measured or calculated?
• Hypothetically speaking, can algorithms be applied to all situations? In the sense, like solving problems in  the medical field, diagnosis? What are the real world applications of algorithms?
• How do programers tell the computers to do the algorithms?
• Is it possible to design computer that generate their own algorithms, speeding up the process exponentially.
• Are there any computers that don't use binary, or is binary universally used?
• What other sorting methods are there and what sorting methods are optimal for different specific tasks?
• What are the trade-offs are "more desirable" programs?

UCSB Freshman Seminar “What is computing?”, Fall 2016

Some questions posted by the class after Lecture 3, October 11, 2016

• The example on the board gave a series of numbers that translated to “Hello!”. 72 meant H, 101 meant e, etc. How does the computer know where the code for one number ends and the other begins? How does it know that the code is 72, not 721, when 101 directly procedes it
• How many and what types of encoding are there?
• How many k/bits are necessary to have in an audio in order to have the best quality humans can detect?
• Who created the "ASCLL" code?
• How can a computer encode a picture or a song into a series of number? 
• Since an audio format, like a song, can be downloaded/converted into a computer by the data that was input, how does a computer convert/translate audio that is simply spoken, without physically reading data. For example, when a person asks "Siri" a question on their iPhone, how does the computer convert what it heard into text on the computer screen?
• It is an interesting computational and philosophical question to ponder which, if any, types of information could not be expressed in code. This is equivalent to asking if there exists purely qualitative information that cannot be quantified. 
• How does a computer convert sensory details into numbers?
• What is the most universal coding system that most computers use? In other words, has it changed over the years or evolved to become shorter or more concise?
• What separates uniquely human attributes from those that a computer can understand?
• How are computers able to process lots of large binary numbers so quickly?
• Is every shade of the 17million colors translated as a specific number to create visuals on TVs, computers, phones?
• Different types of information can be stored as long lines of numbers. What are the limitations of such information? Is this format less or more accessible (in the distant future) than books?
• Can a program be modeled by something other than human quantifications?
• How far are we from developing an AI that can feel? Can such a development ever be achieved?
• If Red, Blue, and Yellow are the "primary colors", why did people choose to use Red Green and Blue light when dealing with monitors? Wouldn't using the Primary colors yield the same effect?