What follows is a stream of thoughts on the nature of making sense of the world. It might not be perfectly coherent, but it’s a love letter to knowledge and also a mission-statement of mine, of sorts.
Understanding reality (even if only by approximation) can help us understand the goal of our own lives and work better: The better our approximations of reality, the better able we’ll be at making sense of the world. Part of what I’m hoping to achieve with this blog is to demonstrate just how interconnected reality is, and how you can dart and weave between topics as different as physics and biology and finance to better approximate your understanding of reality as a whole.
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Reality is the underlying fabric of our universe, weaving a tapestry that is both complex and unseen. Yet, the movement of the weave and the processes that have laid the threads into place are subject to physical law; laws that are possible for us to understand and translate into words that make sense to human eyes and ears. Ultimately, the better we understand these laws and the tapestry painted under their influence, the more we will know, the deeper we will see, and the better we’ll be able to make sense of what’s happening in the world.
Making sense of the world is the aim of each profession. As such, growing more knowledgeable is a prerequisite for doing each profession well. This is because knowledge is a framework by which we can approximate reality—a useful simplification of something that otherwise would be far too complex—lovingly stitched together one piece of data at a time.
Each nugget of information is a piece of data, binary and blind. Data, however, springs to life as it grows from one to two and from two to many. Indeed, the more data that we accumulate, the more complex and intricate the patterns that start to appear. Linear at first, the patterns will twist and weave in on themselves with an increasing frenzy until they run across the tapestry to connect distant motifs and reveal them as part of one underlying theme.
It’s by seeing and recognising these patterns that we make sense of the world; deriving patterns from data and then patterns from first-order patterns. Ultimately, these patterns mature into frameworks; more theoretical models of cause and effect that help us leverage insight to predict what comes next. At this point, our understanding has evolved from the passive seeing of revealed patterns to the active hunt for new ones, as if the framework is the flashlight that allows us to peer at parts of the tapestry still hidden in the dark. Each new pattern so discovered adds more power to our framework-flashlight, allowing us to peer deeper and deeper into the not-yet-seen.
Armed with a growing library of patterns, we can start forming hypotheses about how the world works. The better we understand the underlying processes, the more refined our frameworks will be—and the more informed the resultant hypotheses. Such informed hypotheses will, in turn, generate more accurate predictions. As such, a good framework is one that is a good approximation of reality; a useful simplification of something that otherwise would be far too complex. We keep iterating on these frameworks by asking a never-ending series of ‘Why’s, not resting until we’ve touched the ground at the very bottom of things.
From this it follows that the more accurate your approximations of reality, the more successful you will be. Indeed, success is nothing but the product of a long line of hypotheses and predictions that turned out to be less wrong than the average prediction, if not all-out correct. For this reason everyone owes it to themselves to become the most knowledgeable person who they can be; to keep hungering for information and to keep iterating their frameworks so they approximate reality more and more. (The more often we’re surprised, the more we’ve been blindly guessing, either because our framework isn’t a good approximation of reality or because we didn’t trust our approximations in the first place.)
Every piece of information tells us something, even if that ‘something’ might not be evident from the start. The more you learn and the deeper the patterns that you see, the easier it will become to put each piece of data into its proper place. And with each piece of data in its proper place, the easier it will be to generate predictions from smaller and more disparate nuggets of data. The more you’ve seen, the more you’ll see that each new scenario is just an iteration of a story that’s already played out in some shape.
The beautiful thing about the tapestry of reality is that the laws governing its weave have specified the use of a fixed palette of threads. Every motif that appears in the weave will make use of these threads, if not all of them at once, at least we’ll not be seeing any threads that are new. Thus, while we cannot predict what exact motif will appear at any given point of the tapestry, we can use our approximated understanding of reality to predict what average motif is likely to appear and what sub-palette of threads that is likely to have been (and will be) used.
The most (consistently) successful people among us have a better ‘feel’ for the weave of the tapestry than everyone else. They simply understand reality better; reality just makes sense to them. Such successful people also have enough confidence in their approximations to trust them to not lead them astray. That is not to say that all things are knowable. Oh no, there is enough randomness in the world to keep things interesting; not everything in life will be predictable. Oftentimes, having a vague hunch about the nature or likelihood of something is also typically more than enough.
Everything that we do is hypothesis-driven, and success depends on having the most accurate understanding of how the world works. The better you understand the world, the more everything that happens will start to make sense. For the person who knows everything there is to know, randomness is the only thing left to surprise.