I like it. One might say I am predisposed to like it, based on a semi-Asperger-ish clinging to rigid definitions by my mind. Or one might say that it is easy to like, considering the clarity and confidence found in its obtainment.
Perhaps not everyone cares about an explicit or conscientious path toward discernment, but presumably most or all do care about it one way or another.
Does learning have an end? Is there a point at which a person knows all there is to know, or all they need to know, about something? On the one hand, everything is eventually connected to everything else, and the connections between everything can probably be generalized into finite, discrete views or categorizations of relevance. And so knowledge might be complete once all the relevant views upon a topic are understood. On the other hand, who knows? To know something, it turns out, is both a mental and an emotional state. Emotional states are usually fickle. Is reminding or remembering a part of learning? Only inasmuch as something is experienced by the individual that they have never experienced before.
But I think it's safe to say that in this short and limited life learning can always be continued, even for one simple thing like eating or addition. And discernment is necessary at a given level for learning to take place. We might even say that discernment is the eventual result of learning. (Discernment seems to imply an awareness of a perception, not just the perception itself. Perhaps all discernment is cognitive discernment.)
As mentioned, discernment occurs at different levels. Discernment at a given level can only be as useful as all the discernment obtained at levels below it.
Usually I perceive learning taking place (off the top of my head) as a combination of a process guided by another party, an exercise in intuition, and a subscription to a defined belief or heuristic. Learning can be planned strategically but complications arise when there are unknown unknowns (you don't know what you don't know).
It seems like a teacher is enabled via sensitivity to their students states and predispositions toward learning a given topic. Even self-teachers. Not all students are ready to have another person's entire discernment impressed directly upon them.
But there are teaching methods which either obstruct discernment from taking place or aid it's realization. Involving additional senses engages the individual more, while introducing distinction among the delivery in accord with the relevant inherent distinctions of the subject matter gives a built-in, reference-able truth that is non-distracting. It's part of the scenery. I've noticed this while white-boarding: the proper use of varying colors can speed understanding and protect clarity.
---
Came across this quote: "A young teacher teaches even what she does not know, a middle-aged teacher teaches only what she knows, and an old teacher teaches only what is necessary." Source: http://carmelnet.org/larkin/larkin093.pdf. I did not read this paper much; it feels very specific. Some young teachers teach what they know but don't yet know specifically why what they teach is true. Life has been designed such that this is possible, in the interest of those who have limited access to information and experience (which let's face it includes all of us).
Spiritual discernment is the most valuable knowledge. It is discernment at the highest level with all levels of worth below it.
Bit of a long lunch break but a refreshing one. :)
Wednesday, December 3, 2014
Saturday, March 17, 2012
Slippery Truth
It seems like the most valuable truth can be "slippery" or hard to hold on to. I just left a comment on someone else's Facebook post in response to their solicitation of emotional help and support. It is kind of surprising to me because I'm not exactly having a flowery, paradisaical time myself of late, but I've been trying to learn and rise above it. Adversity exists: it always has, and always will. In fact, it is built into the very fabric of existence, if you will, because every force has an equal and opposite force (e.g., see Newton's Third Law of Motion). So we don't expect to be free of opposition, we can only expect that it exists. The nice thing is that we have access to the following so that we can find solutions:
Using these tools, we may (if we so choose) do just about any meaningful thing, despite opposing forces. The trick for me often is knowing and feeling what it is that I want to do, because I have so much going for me and so much in my control that I want to do it all. I cannot do it all in a limited time-frame--I can only do a certain subset. So I better pick the subset most valuable to me.
This is so easy to forget, but so important! May we all learn and internalize this perpetually. Here's that post:
- Agency (Will and Caring)
- Animation of personal faculties
- Stewardship of resources
- Relationships to other agents
Using these tools, we may (if we so choose) do just about any meaningful thing, despite opposing forces. The trick for me often is knowing and feeling what it is that I want to do, because I have so much going for me and so much in my control that I want to do it all. I cannot do it all in a limited time-frame--I can only do a certain subset. So I better pick the subset most valuable to me.
This is so easy to forget, but so important! May we all learn and internalize this perpetually. Here's that post:
Hey [name omitted], you should know that all my interactions with you have been positive and you are an good individual! Challenges exist in life but they don't define who we are. Ultimately we decide who we are and what our perspective is, and that decision is reflected in our response to challenges and blessings alike. And if things seem completely out of our control, then we can recognize that and choose to focus on what is in our control. I'm rootin' for you! Praying, too. :)
Monday, February 20, 2012
More CS Counsel
Continuing along the same vein, here are some words from Manuel Blum of Carnegie Mellon University:
...Finite Automata can add but not multiply.
Turing Machines can compute any computable function.
Turing machines are incredibly more powerful than Finite Automata.
Yet the only difference between a FA and a TM is that
the TM, unlike the FA, has paper and pencil.
Think about it.
It tells you something about the power of writing.
Without writing, you are reduced to a finite automaton.
With writing you have the extraordinary power of a Turing machine.
And here, have some more:
Brains are muscles.
They grow strong with exercise.
And even if they're strong, they grow weak without it.
Yum, this is tasty stuff...
Whatever you do, you got to like doing it....
You got to like it so much that you're willing to think about it, work on it, long after everyone else has moved on.
.
Well now I am just bordering on copyright infringement:
When working on proving some statement S true,
you should spend at least some time trying to prove it false.
Even if it's true, trying to prove it false can give insight.
And in any case, too often, our intuition is dead wrong.
There is yet another sense in which, when working on a hard problem, you may find that the answer is NOT what you expected.
You may be looking for a YES or a NO; it may be something else.
Then he talks a bit about the P=NP problem, which I wish I had a better handle of in my mind but unfortunately took Theory of Computation during a semester when the force of earth's gravity spontaneously doubled. But actually, there's nothing stopping me from researching it further as soon as I finish with my undergraduate degree. When you listen to researchers talk, you can tell that to them there are no limits when you want to study something: the only thing holding you back is your own motivation or lack thereof.
Here's a poem that he wrote, called Blind Spots:
He ends with another poem (although I suppose it is a mixture of poetry and prose) of his, of which I include the final stanza:
One does not have to be brilliant, a genius, to be special.
To do something better than anyone/everyone else. To be
UNMATCHED,
One has only to choose an END
any END
that MATTERS
that INSPIRES
YOU
And then DO IT.
Overall I am impressed with this man's research and thoughts, and I greatly appreciate his willingness to share so much of it and so openly. I hope to return to his site to learn more about consciousness and complexity and anything else that's worthwhile. He seems like quite the interesting fellow, considering that he's a jewish-born Venezuelan computer scientist who now lives in America and won the 1995 Turing award.
While skimming through the Research Goals paper from Microsoft's Jim Gray I came across a mentioning of the Turing Tar Pit: "where everything is possible but nothing is easy". This seems like it has some valuable parts as well, although I would probably revisit it just to skim for the main ideas.
...Finite Automata can add but not multiply.
Turing Machines can compute any computable function.
Turing machines are incredibly more powerful than Finite Automata.
Yet the only difference between a FA and a TM is that
the TM, unlike the FA, has paper and pencil.
Think about it.
It tells you something about the power of writing.
Without writing, you are reduced to a finite automaton.
With writing you have the extraordinary power of a Turing machine.
And here, have some more:
Brains are muscles.
They grow strong with exercise.
And even if they're strong, they grow weak without it.
Yum, this is tasty stuff...
Whatever you do, you got to like doing it....
You got to like it so much that you're willing to think about it, work on it, long after everyone else has moved on.
.
There's a wonderful quote from ANATOLE FRANCE:
"A University Student"
-- and this is especially true for a PhD Student --
"should know something about everything
and everything about something."
"A University Student"
-- and this is especially true for a PhD Student --
"should know something about everything
and everything about something."
You know the jokes about PhD's...
A PhD knows more and more about less and less
until he knows everything about nothing.
A PhD knows more and more about less and less
until he knows everything about nothing.
Well now I am just bordering on copyright infringement:
When working on proving some statement S true,
you should spend at least some time trying to prove it false.
Even if it's true, trying to prove it false can give insight.
And in any case, too often, our intuition is dead wrong.
There is yet another sense in which, when working on a hard problem, you may find that the answer is NOT what you expected.
You may be looking for a YES or a NO; it may be something else.
Then he talks a bit about the P=NP problem, which I wish I had a better handle of in my mind but unfortunately took Theory of Computation during a semester when the force of earth's gravity spontaneously doubled. But actually, there's nothing stopping me from researching it further as soon as I finish with my undergraduate degree. When you listen to researchers talk, you can tell that to them there are no limits when you want to study something: the only thing holding you back is your own motivation or lack thereof.
Here's a poem that he wrote, called Blind Spots:
All men have Blind Spots in their eyes,
That manufacture visions of their vale.
And shape that void where light's unregistered,
With bold-faced unrepentant tales.
That manufacture visions of their vale.
And shape that void where light's unregistered,
With bold-faced unrepentant tales.
What other blind spots shape our minds and thoughts?
What other tales do won'dring minds unfurl
To woo us unbeguiled we would believe
To strange and nonexistent worlds?
What other tales do won'dring minds unfurl
To woo us unbeguiled we would believe
To strange and nonexistent worlds?
He ends with another poem (although I suppose it is a mixture of poetry and prose) of his, of which I include the final stanza:
One does not have to be brilliant, a genius, to be special.
To do something better than anyone/everyone else. To be
UNMATCHED,
One has only to choose an END
any END
that MATTERS
that INSPIRES
YOU
And then DO IT.
Overall I am impressed with this man's research and thoughts, and I greatly appreciate his willingness to share so much of it and so openly. I hope to return to his site to learn more about consciousness and complexity and anything else that's worthwhile. He seems like quite the interesting fellow, considering that he's a jewish-born Venezuelan computer scientist who now lives in America and won the 1995 Turing award.
While skimming through the Research Goals paper from Microsoft's Jim Gray I came across a mentioning of the Turing Tar Pit: "where everything is possible but nothing is easy". This seems like it has some valuable parts as well, although I would probably revisit it just to skim for the main ideas.
Saturday, February 18, 2012
Research
I've been trying to decide if "research" is the right field for me, and just now I was reading "Advice to the new researchers" by IBM researcher Mark Wegman (here's the link, assuming they preserve it.) Among other things, he mentioned that typically a research problem has various sub-problems a, b, and so on. Here's a quote I liked:
In any research problem you are taking a risk. This requires great courage. Don't think for a moment that it doesn't. Each of the sub-problems might stump you and you might fail at the whole task.... The right approach to a risky endeavor is to go more breadth first. Do a bit of work on b to understand it better, then go back to a. People resist this approach because they like doing things they know and are good at, and switching contexts can also be expensive. If success at b were guaranteed then finishing a first would have been more efficient. If you aren't failing often in research, you aren't solving hard enough problems and taking enough risks. If there's a reasonable chance of failure, then a breadth first approach to the problem allows the faster failure and consequent saving of effort.
Here another on complete understanding:
One lesson is, you must understand something fully before you can do something simply. It's okay to go through complex solutions and then simplify later, at least on really hard problems. John Vlissides always told me you need to implement something at least 3 times before you can generalize. Understanding something fully before generalizing and simplifying it is as important in software engineering as in theoretical problems.
And one more on problem selection:
Choose a problem that will move you in a direction you want to go. In other words, choose a problem that will teach you something useful as you tackle it, or have you build something that will also be helpful in future work, regardless of whether you succeed or fail on this problem.
He referenced the wikipedia page for Heilmeier's Catechism:
There's also a page with lots of advice for researchers: http://www.cs.utexas.edu/users/dahlin/advice.html. This has been a great resource. I am excited about research, but I lack some confidence to jump in. This is because of the way I like to learn compared with the way I have been expected to learn for the past few years at my university. I could be a researcher, come to face it, if that's what I decided I wanted and ought to do. Now that is another question, and a good one at that.
Also, I learned that pedagogy can be defined as the art or study of teaching or instructive strategies.
In any research problem you are taking a risk. This requires great courage. Don't think for a moment that it doesn't. Each of the sub-problems might stump you and you might fail at the whole task.... The right approach to a risky endeavor is to go more breadth first. Do a bit of work on b to understand it better, then go back to a. People resist this approach because they like doing things they know and are good at, and switching contexts can also be expensive. If success at b were guaranteed then finishing a first would have been more efficient. If you aren't failing often in research, you aren't solving hard enough problems and taking enough risks. If there's a reasonable chance of failure, then a breadth first approach to the problem allows the faster failure and consequent saving of effort.
Here another on complete understanding:
One lesson is, you must understand something fully before you can do something simply. It's okay to go through complex solutions and then simplify later, at least on really hard problems. John Vlissides always told me you need to implement something at least 3 times before you can generalize. Understanding something fully before generalizing and simplifying it is as important in software engineering as in theoretical problems.
And one more on problem selection:
Choose a problem that will move you in a direction you want to go. In other words, choose a problem that will teach you something useful as you tackle it, or have you build something that will also be helpful in future work, regardless of whether you succeed or fail on this problem.
He referenced the wikipedia page for Heilmeier's Catechism:
A set of questions credited to Heilmeier that anyone proposing a research project or product development effort should be able to answer.
- What are you trying to do? Articulate your objectives using absolutely no jargon.
- How is it done today, and what are the limits of current practice?
- What's new in your approach and why do you think it will be successful?
- Who cares?
- If you're successful, what difference will it make?
- What are the risks and the payoffs?
- How much will it cost?
- How long will it take?
- What are the midterm and final "exams" to check for success?
There's also a page with lots of advice for researchers: http://www.cs.utexas.edu/users/dahlin/advice.html. This has been a great resource. I am excited about research, but I lack some confidence to jump in. This is because of the way I like to learn compared with the way I have been expected to learn for the past few years at my university. I could be a researcher, come to face it, if that's what I decided I wanted and ought to do. Now that is another question, and a good one at that.
Also, I learned that pedagogy can be defined as the art or study of teaching or instructive strategies.
Saturday, January 21, 2012
Rabin
I just finished reading a pretty cool article about Michael Rabin in a 2010 issue of "Communications of the ACM". He did some really neat work with math and computer science, to say the least. I particularly liked some of his closing words in the interview.
After noting that computer science has evolved and even revolutionized itself many times in the course of his career, he referenced the obviously fundamental work of Alan Turing's theoretical computing machine. Then finite automata represent models for sequential circuits (essentially state transition diagrams). "Nondeterministic and deterministic so-called push-down automata play a pivotal role in the syntactic comilation of programming languages." The study of algorithms will always play a critical role in computer science and life. After the emphasis on formal languages and the like, focus has shifted to networking and communication through the Internet and other distributed systems. "The developments are giving rise to a torrent of research in information retrieval, in machine learning, in computerized language understanding, in image understanding, in cryptography security and privacy protection, in mult-agent systems..."
It lead me to think 1) that I have come a long way since the 8th grade, when I knew nothing of programming and life was easy and breezy, and 2) there is a long way to go. I try to make plans on what I will do in my future, but I just am not able to see that far ahead. I need to be flexible and adaptive moving forward, and we'll see where life takes me. I believe the changes in the next 5-10 years will continue to change the face of where computer science and the world go. And as that unfolds I will play my role, whatever that role may be.
After noting that computer science has evolved and even revolutionized itself many times in the course of his career, he referenced the obviously fundamental work of Alan Turing's theoretical computing machine. Then finite automata represent models for sequential circuits (essentially state transition diagrams). "Nondeterministic and deterministic so-called push-down automata play a pivotal role in the syntactic comilation of programming languages." The study of algorithms will always play a critical role in computer science and life. After the emphasis on formal languages and the like, focus has shifted to networking and communication through the Internet and other distributed systems. "The developments are giving rise to a torrent of research in information retrieval, in machine learning, in computerized language understanding, in image understanding, in cryptography security and privacy protection, in mult-agent systems..."
It lead me to think 1) that I have come a long way since the 8th grade, when I knew nothing of programming and life was easy and breezy, and 2) there is a long way to go. I try to make plans on what I will do in my future, but I just am not able to see that far ahead. I need to be flexible and adaptive moving forward, and we'll see where life takes me. I believe the changes in the next 5-10 years will continue to change the face of where computer science and the world go. And as that unfolds I will play my role, whatever that role may be.
Tuesday, January 17, 2012
Tabbed browsing is nice. For one, as we all know, it is nice to be able to switch between web page sessions in the same window without web navigation.
But it is also nice because it allows for more efficient tree traversal of a web site's pages because you don't have to go forward and backwards: once you have expanded a given node (i.e., visited a given page) you can return to it in constant time no matter where it is in the tree (although there is a practical limit of probably around 8-20 tabs, depending on your resolution).
Monday, December 12, 2011
Money
Gotta love Randall Munroe's xkcd.com. It's full of interesting stuff, like this poster: http://xkcd.com/980/ I don't know what motivates him to undertake these sizeable projects by himself (I assume), but it's impressive to me even if there are flaws to be found.
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