00:00:24
You give me a lever long enough and a fulcrum on which to place it, and I shall move the world. Humans are the cleverest animals in the known universe, but our brains, forged over millions of years in the unforgiving furnace of natural selection, are still primitive. They evolved to be good at hunting animals, making tools, recognizing facial expressions, and maintaining social bonds, but they're just not very good at working with several difficult ideas simultaneously. They're particularly bad at reasoning about the counterintuitive emergent behavior of complex non-human systems.
00:00:44
And that's a problem because complex non-human systems now dominate our world. Abstraction is our solution to this problem. Abstraction works as an adapter between the fearsome complexity of the universe and our simple primate minds. When the real world is too detailed, confusing, or counterintuitive for us to work with directly, abstraction gives us big friendly levers to pull on instead. This one powerful idea underlies computer design, culture, language, and everything else we rely on in our daily work.
00:01:09
So, I'm going to talk a bit about abstraction—where it comes from, what it's for, and how we can use it to make our programs better. Let's begin by talking about numbers. Numbers seem obvious and natural to us, but they have no independent existence. They are a human invention, a technology designed by us to solve problems we have. There was a point in our cultural history where we had no concept of numbers, but then we created them and gave ourselves a new and powerful tool for categorizing, understanding, and predicting the real world.
00:01:57
Imagine you're living in prehistoric times, and the concept of numbers hasn't been invented yet. You've grown some apples—here they are—which is great, but you've been eating apples every winter for years and are kind of tired of them. Fortunately, a visitor arrives from the next village, and they have some bananas. Now, you feel that swapping an apple for a banana is a fair trade, and you would like as many bananas as possible. But are you prepared to swap your entire collection of apples for the visitor's collection of bananas? Is that fair to both of you?
00:02:49
Well, yes, it is fair, because this collection of apples has something in common with this collection of bananas. There's a special property that they both share, even though they're made of different fruit. This property allows us to agree on their value and makes the trade fair. In fact, we can come up with other collections that also have this property, like a collection of cherries. They can be paired up with the apples, allowing for an equal exchange, thus demonstrating that the kind of fruit is irrelevant. What matters is the property that connects them.
00:04:06
So, what do we call this property? How do we identify the property that those apples, those bananas, and all those cherries have? Our usual name for it is three. Now, technically speaking, what you're seeing isn't actually the number three; it's just a pattern of light made of pixels that represents a specific glyph from a typeface, which denotes the number three in the base 10 positional numeral system, widely used in Western culture.
00:05:00
The number three itself is an abstract structure and represents the relationship we're identifying. If you have a collection with three things, you can visualize it easily. You learned about the concept of three when you were very young, and you likely have a mental image of it. Once we have the idea of a number, we can build other concepts from it. For instance, we can identify particular relationships between collections, such as when we pair them up, which leads to identifying successors in numeric relationships.
00:06:01
As we continue to explore the idea of numbers, we learn that the successor of a number is the next number in the series. This concept of successor helps us generate new numbers—like four being the successor of three, and so forth. Furthermore, when two numbers are connected by an unbroken sequence of successors, we can say that the first number is less than the second one. This gives us a way to build operations on these collections.
00:07:08
For example, consider the operation of addition. If we take every item in the first collection and add the successor of the number represented by the second collection, we can see how addition works in real-world terms. The abstract operations in the world of numbers accurately predict what happens in reality; they allow us to keep track of situations without needing to physically manipulate items.
00:08:06
This ability to simplify complex problems using abstraction allows us to predict outcomes efficiently. As we develop an understanding of complex relationships and how to represent them numerically, we begin to see the underlying simplicity in problems that initially appear complicated. All of this knowledge is built from our ability to abstract and utilize mathematical operations effectively.
00:09:03
Now, moving from simple addition, let's examine a more challenging problem—finding the sum of all numbers between 1 and 100. The traditional method of calculating this sum might take a long time, especially when comparing pairs. However, the mathematician Carl Friedrich Gauss purportedly developed a shortcut. He noticed that the property of addition allows us to rearrange and group numbers, leading us to a more efficient calculation.
00:10:05
For example, pairing up the first and last number allows us to find equal sums in fewer steps. We can generalize this approach to solve for higher numbers while maintaining efficiency. Thus, even when we look at more complex sums or sequences, we can distill them down to simpler operations that fulfill the same purpose efficiently. All of these patterns are simply different manifestations of the same underlying principles in arithmetic.
00:11:32
When we examine numbers visually, we see their relationships manifest as shapes, like triangles formed from consecutive numbers. By rearranging these shapes, we gain insights into their properties and criteria that seem complicated at first but are rooted in very simple relationships, leading us to concepts like the Pythagorean theorem—a key takeaway in geometry.
00:12:30
Furthermore, the application of abstraction extends beyond mere numbers into complex problems like the famous bridge problem in Konigsberg. Mathematician Leonhard Euler analyzed the structure of bridges and islands through a graph. In a graph, we visualize nodes (land masses) and edges (bridges) which facilitate our ability to explore the problem's structure above form.
00:13:50
Understanding the properties of graphs, like connectedness and trails, becomes a vital tool in solving mathematical puzzles that arise naturally in our world. We can classify these ideas and relationships, exploring their characteristics. By further developing useful frameworks, we derive profound insights into complex systems by reducing them to their fundamental relationships.
00:15:25
Ultimately, these abstractions allow us to infer answers from complex graphs, like the walking paths and bridges that cannot be traversed in certain configurations. By studying these properties, Euler proved that, for paths to exist while crossing each bridge precisely once, there must be at most two nodes of odd degree. This foundational work in graph theory teaches us profound lessons about the structures we encounter.
00:17:03
Returning to the context of triangles, we revisit how the lengths of a triangle's sides relate to one another. The Pythagorean theorem beautifully encapsulates this relationship when we arrange shapes and calculate their respective areas, thus solidifying our understanding of geometry through abstraction. It's crucial to note that even if the specific visual representation escapes memory, the formulas and relationships are what grant power.
00:18:00
As we explore concepts of abstraction, we delve into mathematics not as mere computation but as the computational reasoning that drives problem-solving. Mathematics is about recognizing patterns and building reusable abstractions to simplify complexities in various domains. This perspective opens up possibilities for programmers, juxtaposing abstract thought with practical applications that improve efficiencies and dwell on problem structures.
00:19:20
As we learn to abstract patterns in programming, we begin to see the beauty and richness that emerge from simplicity. Formulating abstractions within code, for instance, can streamline complex tasks that may initially feel burdensome and convoluted. Developing a solid foundation in abstraction allows us to tackle programming problems head-on, transforming them into manageable tasks while preserving their underlying structures.
00:20:10
Ultimately, what I have been discussing throughout this talk is essentially the art of abstraction. Whether we use a card rank analogy to define poker hands or delve into the motivations behind mathematical proofs, we engage with abstraction continuously. The journey of growth and discovery becomes evident when we approach programming with this mindset, prompting deeper learning and broader horizons.
00:21:50
In practical terms, though, it helps to understand that abstraction does not merely exist in theoretical realms. As we work in the software sphere, the aim must be to deliver tangible value—making users' lives better. The essence of great programming lies in this balance between beautiful abstractions and effective solutions tailored to meet real needs.
00:23:23
The exciting reality of programming is that by treating it as a mathematical endeavor, we gain the ability to articulate and enact abstraction in profound ways. This journey doesn't require memorization to thrive but rather an understanding of foundational concepts to express creativity and problem-solving capacity through mathematics and programming.
00:25:07
To wrap this up, realize that engaging in mathematics do equip us for life beyond academic boundaries. While it may feel uncomfortable or out of reach, we must leverage our ability to abstract for the greater good—both for our creative aspirations and the contributions we offer to others. In essence, we are harnessing our cognitive powers to explore new fields, transcend boundaries, and ultimately redefine problems.
00:27:10
As I leave you with these thoughts, remember that whether you're writing code or engaging in complex problem-solving, abstraction serves as a foundation for success. Embrace its beauty, build upon it, and never underestimate the significant impact of mathematics and its principles within programming and beyond. Thank you for listening.
