It’s tough to make predictions, especially about the future 😽
~ Yogi Berra (the inimitable baseball-playing philosopher)
— Reader: Hey Akram, so what do you know about making predictions?
— Me: So I only now scant little…
— Reader: So how come you wrote up this essay?
— Me: So I could rant a little…
— Reader: Okay… Let me put it another way and ask, What got into you to serve up this balderdash?
— Me: So I could pant a little… (Pavlovian salivating dogs notwithstanding!)
— Reader: Hmm… Will you, um, deceive us with fake news?
— Me: No. Never, but of your trust you must grant me a little…
— Reader: I see. Well, how did you imagine us reacting to this bizarre start?
— Me: So I had wished to beguile you as I chant a lot and enchant a little…
— Reader: Groan, this is clear as mud… We’re not getting anywhere!
— Me: Oh, perhaps we should decant a little…
— Reader: You might as well go ahead!
So the time has arrived to decant the contents… (Check out the lush garden below, with the flowering-can in the decanting position!)
Shall we proceed? 👀
Decanting The Contents (Predictably Enough!) 🚿
- Prediction About Life In A World Awash In Data 🐘
— Patrick Tucker (in The Naked Future — Published by Current) 🐘
- Prediction About The Impact Of A Significant Other On One’s Journey Through Life! 👪
— John Hattie and Gregory Yates (in Visible Learning and the Science of How We Learn — Published by Routledge) 👪
- Prediction About What It Takes For A Writer To Succeed 🏄
— Stephen King (in On Writing: A Memoir Of The Craft — Published by Scribner) 🏄
- Prediction About Cash In The Hand 💸
— Jelaluddin Rumi (in the translation by Coleman Barks entitled The Essential Rumi — Published by HarperOne) 💸
- Prediction About What A Computer Program Is (Really) Up To 🔬
— Pierre-Yves Saumont (in Functional Programming In Java: How Functional Techniques Improve Your Java Programs — Published by Manning) 🔬
- Prediction About The Words “Nerd”, “Dude”, And “Geek” Becoming Entrenched 🐙
— Steven Pinker (in The Sense of Style: The Thinking Person’s Guide to Writing in the 21st Century — Published by HarperOne) 🐙
- Prediction About How Much Students Will Learn 🎓
— David Perkins (in Making Learning Whole: How Seven Principles of Teaching Can Transform Education — Published by Jossey-Bass) 🎓
- Prediction About The Real Secret Of Shakespeare’s Monumental Success 🎭
— Shakespeare (in William Shakespeare: Complete Works — Published by Random House Publishing Group) 🎭
- Prediction About Predictable Stack Usage (in Computer Programming) 📶
— Paul Chiusano and Rúnar Bjarnason (in Functional Programming in Scala — Published by Manning) 📶
- Prediction About The Limitlessness Of Inventing New Theories 🐝
— Edward Ashford Lee (in Plato and the Nerd: The Creative Partnership of Humans and Technology — Published by The MIT Press) 🐝
— Reader: Dude, are you done already with decanting?
— Me: Um, so I am, but only on the plants in that lush garden, and that, too, a little…
— Reader: Ooh la la, this blogger needs a brain transplant!
— Me: Methinks, too. Let’s proceed with the implant, though only a little…
— Reader: I’m crying uncle, and aunt!!
— Me: Hey, no fair… But I suppose I shan’t be doing so now… For crying out loud, I had barely warmed up to tell all the truth, but tell it slant a little…
Oh my! Check out the selfie below. Right now. (Okay, so it’s already inspiring a brewing narrative in your blogger’s mind and deserves an essay of its own; stay tuned.) 📺
Now we dive headlong into our collage. Check out the picture below: Two brave souls waltzing away stoically even as they find themselves shoulder-deep in the deluge of data… What’s going on?
1. Prediction About Life In A World Awash In Data 🐘
THE date is February 29, 2012. The setting is the O’Reilly Strata Conference in Santa Clara, California. Xavier Amatriain, engineering manager of Netflix, is concluding his presentation on how the company recommends movies to users. In 2009 Netflix launched a $1 million prize to build a better recommendation engine. The conditions for the award were: the winning algorithm had to correctly predict the next 2.8 million ratings, around 6 per user, 10 percent more accurately than the current Netflix system (10 percent defined by rote mean-square deviation).
~ Patrick Tucker (in The Naked Future — Published by Current)
Here Be Where I Bake My Take: Thus wrote Tucker in Chapter 5—a chapter with the intriguing title of “Unities of Time and Space”—of his fine book, The Naked Future. I think Tucker does a really good job of bringing palpable excitement to the narrative of how we came to be inundated by the tsunami of data. His writing style is slick, his reporting accurate, and his mastery of the domain (of Big Data) admirable. All in all, if you want to find out what it takes to make predictions in this domain—including of course the Netflix Prize of a million dollars—check out The Naked Future.
2. Prediction About The Impact Of A Significant Other On One’s Journey Through Life! 👪
So we find that (a) positive student-teacher relationships can buffer effects associated with poor home background factors, and (b) good home and parental factors can buffer effects associated with less-than-optimal teacher-student relationships. But furthermore, Benner and Mistry established that students with the most favourable educational outcomes enjoyed congruence between the home and school. That is, positive relationships and expectations stemming from both parents and teachers predicted just who the most successful students were. The worst outcomes were associated with low expectations from both parents and teachers. Such research findings give strong support to the notion that every child needs a significant adult to express positive regard in him or her.
~ John Hattie and Gregory Yates (in Visible Learning and the Science of How We Learn — Published by Routledge)
Here Be Where I Bake My Take: Thus wrote Hattie and Yates in their fine book, Visible Learning and the Science of How We Learn. And as someone who has searched high and low for the core components of what makes the learning machinery tick, this book is a godsend! It’s all stuff, no fluff. I won’t be surprised if each and every one of us—as we cast a glance back at our past—can identify one individual (or perhaps even more) whose mentoring made all the difference. Don’t you want to thank your lucky stars as you remember your mentor (or mentors)?
3. Prediction About What It Takes For A Writer To Succeed 🏄
I predict you will succeed swimmingly … if, that is, you are honest about how your characters speak and behave. Honesty in storytelling makes up for a great many stylistic faults, as the work of wooden-prose writers like Theodore Dreiser and Ayn Rand shows, but lying is the great unrepairable fault. Liars prosper, no question about it, but only in the grand sweep of things, never down in the jungles of actual composition, where you must take your objective one bloody word at a time. If you begin to lie about what you know and feel while you’re down there, everything falls down.
~ Stephen King (in On Writing: A Memoir Of The Craft — Published by Scribner)
Here Be Where I Bake My Take: Thus wrote the one and only Stephen King in his extraordinary book, On Writing: A Memoir Of The Craft. Take it from a doting of King’s memoir that if you were to read only one of his books, make it this one; I simply can’t say enough good things about it! He knows what he’s talking about, and, best of all, he knows how to tell it—dude, King is awesome! See how he grab your attention with his Spartan simple sentence above (“I predict you will succeed swimmingly…”) and took you along for a delightful ride? I could go on and on and… (As a matter of fact, I have done exactly that: Check this essay!)
4. Prediction About Cash In The Hand 💸
There are some mysteries that I’m not telling you.
There’s so much doubt everywhere, so many opinions
that say, “What you announce may be true
in the future, but not now.”
But this form of universal truth that I see
This is not a prediction. This is here
in this instant, cash in the hand!
~ Jelaluddin Rumi (in the translation by Coleman Barks entitled The Essential Rumi — Published by HarperOne)
Here Be Where I Bake My Take: Thus wrote the phenomenally gifted Jelaluddin Rumi—as presented here by his phenomenal translator Coleman Barks—in the gem entitled The Essential Rumi. Oh goodness, we do I even begin to tell you about the wonders that await you between the two covers of this gem? (Much like the pearl embedded inside the two clam-like shells of its resident chambers, you have to dig in and find out for yourself…).
5. Prediction About What A Computer Program Is (Really) Up To 🔬
In functional programming, you won’t see much logging. This is because functional programming makes logging mostly useless. Functional programs are built by composing pure functions, meaning functions that always return the same value given the same argument, so there can’t be any surprises. On the other hand, logging is ubiquitous in imperative programming because in imperative programs you can’t predict the output for a given input. Logging is like saying “I don’t know what the program might produce at this point, so I’ll write it to a log file. If everything goes well, I won’t need this log file, but if something goes wrong, I’ll be able to look at the logs to see what the program’s state was at this point.” This is nonsense.
~ Pierre-Yves Saumont (in Functional Programming In Java: How Functional Techniques Improve Your Java Programs — Published by Manning)
Here Be Where I Bake My Take: Thus wrote Pierre-Yves Saumont in Chapter 13—a chapter with the rather workmanlike title of “Functional Input/Output”—of his interesting book, Functional Programming In Java. So this is where my true colors might be showing: I am, first and foremost, a hard-core software designer and developer who revels in the domain of the IoT (the Internet of Things). What better to capture one of the conundrums which besets us developers than taking a stab at the functional take on the crucial area of the logging done by a computer application?
In an intriguing section entitled “Why logging is dangerous” ( which you find in Chapter 13, as I mentioned above), Saumont takes the lid off on what it takes to make predictions about what a computer program is (really) up to… A fair warning: The narrative isn’t for the faint of heart! But if you are up to it—if you are ready to stomach some of your fondest assumptions challenged—you’ll find much of interest in Saumont’s marvelous take on making predictions about what a computer program ( from the vantage point of computer application logging).
6. Prediction About The Words “Nerd”, “Dude”, And “Geek” Becoming Entrenched 🐙
In the last edition published in his lifetime, White did acknowledge some changes to the language, instigated by “youths” who “speak to other youths in a tongue of their own devising: they renovate the language with a wild vigor, as they would a basement apartment.” White’s condescension to these “youths” (now in their retirement years) led him to predict the passing of nerd, psyched, ripoff, dude, geek, and funky, all of which have become entrenched in the language. The graybeard sensibilities of the style mavens come not just from an under-appreciation of the fact of language change but from a lack of reflection on their own psychology. As people age, they confuse changes in themselves with changes in the world, and changes in the world with moral decline— the illusion of the good old days. And so every generation believes that the kids today are degrading the language and taking civilization down with it.
~ Steven Pinker (in The Sense of Style: The Thinking Person’s Guide to Writing in the 21st Century — Published by HarperOne)
Here Be Where I Bake My Take: Thus wrote the one and only Steven Pinker in his top-notch book, The Sense of Style. What can I add to Pinker’s scintillating account above of the guts of making predictions about the words “nerd”, “psyched”, “ripoff”, “dude”, “geek”, and “funky” becoming entrenched?
7. Prediction About How Much Students Will Learn 🎓
Academic learning time predicts rather well how much students learn, much better than time sitting in class. Such research reveals the tricky logistics of settings of learning. Just because the learners are there does not mean that they are learning much. Effective learning requires artful management of the entire situation to lift academic learning time toward something close to the total time available, making the most of it rather than letting it slip away like sand.
~ David Perkins (in Making Learning Whole: How Seven Principles of Teaching Can Transform Education — Published by Jossey-Bass)
Here Be Where I Bake My Take: Thus wrote David Perkins in his fabulous book, Making Learning Whole. Oh my, just in case you haven’t read this awesome book, run to your nearest brick-and-mortar bookstore to buy your own copy! Rather than repeat what I’ve already written about Perkins’ work in this area, here I’ll refer you to that essay itself!
8. Prediction About The Real Secret Of Shakespeare’s Monumental Success 🎭
The great scholar Edmond Malone predicted that “A time may arrive, in which it will become evident, from books and manuscripts yet undiscovered and unexamined, that Shakespeare did not attempt a single play on any subject, till the effect of the same story, or at least the ruling incidents in it, had been tried on the stage and familiarized to his audience.” He has almost been proved right.
~ Jonathan Bate and Eric Rasmussen (in William Shakespeare: Complete Works — Published by Random House Publishing Group)
Here Be Where I Bake My Take: Thus wrote Jonathan Bate and Eric Rasmussen in their sparkling commentary in the stellar tome entitled William Shakespeare: Complete Works, brought to lovers of the English language by the RSC (Royal Shakespeare Company), which is a world-renowned ensemble theater company in Stratford and London, dedicated to bringing the works of Shakespeare and his contemporaries to a modern audience. So if ever you’ve wondered what led to Shakespeare’s monumental success, read up this amazing analysis by two distinguished Shakespearean scholars—dude, these two guys (Bate and Rasmussen) sure know what they’re talking about.
9. Prediction About Predictable Stack Usage (in Computer Programming) 📶
The StackOverflowError problem manifests itself in Scala wherever we have a composite function that consists of more function calls than there’s space for on the call stack… The StackOverflowError problem manifests itself in Scala wherever we have a composite function that consists of more function calls than there’s space for on the call stack… But there’s no I/O going on here at all. So IO is a bit of a misnomer. It really gets that name from the fact that Suspend can contain a side-effecting function. But what we have is not really a monad for I/O—it’s actually a monad for tail-call elimination! … Using TailRec can be slower than direct function calls, but its advantage is that we gain predictable stack usage.
~ Paul Chiusano and Rúnar Bjarnason (in Functional Programming in Scala — Published by Manning)
Here Be Where I Bake My Take: Thus wrote Paul Chiusano and Rúnar Bjarnason in Chapter 13—a chapter with the rather workmanlike title of “Functional Input/Output”—of his interesting book, Functional Programming In Java. By the way, real quick, did anyone notice the uncanny coincidence as you relate this back to the fifth element—“5. Prediction About What A Computer Program Is (Really) Up To”—in this pictures-and-commentary-mashed-into-one collage? Indeed, in the eeriness of the choices that were available to me, I ended up selecting an excerpt each (of the only two excerpts dealing with computer programming) from the 13th chapter of the respective books! Goodness, I did a double take on realizing this, whereupon I had set out to make sure this wasn’t a factual error (of commission) on my part…
Anyhow, this is going to be times number two in this essay where my true colors are showing: Much as I said on the first occasion earlier, I am, first and foremost, a hard-core software designer and developer who gets a kick out of working in the domain of the IoT (the Internet of Things). As such—given the premium I place on using computer resources efficiently—making accurate predictions about predictable stack usage is bread-and-butter for me. Enough said. (Should you wish for the gory details, I invite you to check this out…)
10. Prediction About The Limitlessness Of Inventing New Theories 🐝
What is the relation between Gödel’s theorem and whether we can formulate the theory of the universe in terms of a finite number of principles? One connection is obvious. According to the positivist philosophy of science, a physical theory is a mathematical model. So if there are mathematical results that cannot be proved, there are physical problems that cannot be predicted.
As we will see, Gödel’s theorems tell us that within any (consistent) formal system, some statements cannot be proven true or false. So Hawking is saying that, given some formalism for modeling the physical world, inevitably some statements within that formalism we cannot know to be true or false. Although this could be a huge disappointment to scientists striving for that ultimate goal, the grand unified theory, Hawking draws a more optimistic conclusion:
“Some people will be very disappointed if there is not an ultimate theory that can be formulated as a finite number of principles. I used to belong to that camp, but I have changed my mind. I’m now glad that our search for understanding will never come to an end, and that we will always have the challenge of new discovery. Without it, we would stagnate.“
With this conclusion, Hawking reaffirms my observation that scientists, like engineers, will never be finished. Although each formalism that we might come up with has its limitations, there is no end to the suite of possible formalisms. There will always be room for invention of new theories.
~ Edward Ashford Lee (in Plato and the Nerd: The Creative Partnership of Humans and Technology — The MIT Press)
Here Be Where I Bake My Take: Thus wrote Edward Ashford Lee in his extraordinary book, Plato and the Nerd: The Creative Partnership of Humans and Technology. which was published just last year (in 2017). Okay, no beating around the bush: Much as I’ve said in a bunch of earlier essays—most recently for example when I said parenthetically in an essay elsewhere that this is my book-of-the-decade—so if ever you remember your blogger for having fallen in love with a book, this is the one. This book is my spark; it’s my joy.
You’re so predictable
I knew something would go wrong (something’s always wrong)
So you don’t have to call
Or say anything at all
You’re so predictable (so predictable)
~ Good Charlotte (lyrics from the song Predictable)