I was recently reminded of the old adage that we are often separated by a common language!…
Over the weekend, I listened to an episode of Paul Miller’s podcast “The Pathless Path,” featuring Billy Oppenheimer. Billy works as assistant to Ryan Holiday and he shared valuable insights on extracting compelling stories from research, a skill he and Ryan have honed. I thoroughly enjoyed the conversation!
During the discussion, Paul asked Billy about his time in Western Australia, prompting a delightful anecdote. Soon after arriving in Australia, Billy struck up a conversation with a stranger over drinks and asked the usual question: “What do you do?” The stranger’s response was both surprising and enlightening: “Oh, you’re American!” It turns out that asking someone about their occupation isn’t as common in Australia as it is in the US.
This story highlights the cultural nuances of communication and the importance of being aware of them. Sometimes, we must try and learn from our mistakes when our use of a common language doesn’t quite translate.
Bonus:
Billy publishes a weekly newsletter, “Six at 6,” every Sunday evening, featuring six fascinating stories. If you enjoy reading interesting stories, his newsletter is a treat!
As I wander through the topography of life, I find myself drawn to the notion that meaning is not a destination, but a traveling companion. The words of Neil King echo in my mind like a gentle breeze rustling the leaves of understanding: “You bring meaning with you when you go looking for meaning, and the more of it you bring, the more you get in return.” It is a reminder that the search for significance is not a passive pursuit, but an active participation in the creation of our own significance.
Like a cartographer charting the unexplored territories of the human experience, we bring our own instruments of meaning-making to the journey. Our experiences, beliefs, and values serve as our compass guiding us through the our personal paths of existence. The more we bring to the table, the more we are able to discern the hidden patterns and connections that weave the tapestry of our lives.
As I meander through the landscape of memory, I realize that the moments of greatest insight and understanding were not chance encounters, but the culmination of a deliberate search. The more I brought to the experience — curiosity, empathy, and a willingness to learn — the more the world revealed its secrets to me. The gentle rustle of leaves in an autumn breeze became a symphony of sound, a reminder of the beauty that lies just beneath the surface of the mundane.
In this sense, meaning is not something we find, but something we forge. It is the alchemy of our experiences, transformed by the crucible of our perception into a golden understanding that illuminates the path ahead. And yet, it is a fleeting thing, a will-o’-the-wisp that beckons us deeper into the mystery.
Perhaps that is the greatest truth of all — that meaning is not a destination, but a journey. It is the process of bringing our whole selves to the experience of life, with all its joys and sorrows, triumphs and failures. The more we bring, the more we receive, and the more we are transformed by the encounter.
As I continue on this winding path, I am reminded of the wisdom of the ancient Greek aphorism: “The unexamined life is not worth living.” But I would add a corollary — the unlived life is not worth examining. It is in the living, the experiencing, and the bringing of our whole selves to the moment that we find the meaning we seek.
As you embark on your own journey of discovery, remember to bring your instruments of meaning-making with you. Often it involves photography or journaling in the moment. The more you bring, the more you will receive, and the more the world will reveal its secrets to you. For in the end, it is not the destination that matters, but the journey itself — the journey of bringing meaning to the world, and finding it reflected back in all its beauty and complexity.
Note: Yesterday Meta released their latest open source AI models: Llama 3. This post based on the quotation from Neil King’s book was written with the help of Llama 3 and lightly edited by me.You can try out Llama 3 yourself at https://meta.ai
AI is not from the heart indeed! Actually, now that I think about it, what’s fascinating about AI is that it is actually trained on these huge quantities of text from the Internet, from books, from places like Reddit, etc – so what the AI is trained on actually could be described as being “from MANY hearts!” So much writing/learning from so many humans go into the model’s training. But, of course, it’s impersonal – or, maybe that’s not correct – it’s something like mega-personal – coming from many persons!
After I wrote this email, I thought to myself that the “mega-personal” notion I mentioned might be worth further exploration – with AI. So I used this prompt to see what might happen:
Please write a musing on this thinking to help me explore it further. Include an interesting quote or two that helps support the discussion.
Here’s the response I got – it has a few pretty deep insights I wouldn’t have thought of!…
Your reflection on AI being trained on vast amounts of text “from many hearts” is thought-provoking and raises intriguing questions about the nature of AI’s “personhood” and the extent to which it can truly capture the essence of human experience. Here’s a musing on this idea:
While AI systems like myself are indeed trained on an amalgamation of texts written by countless individuals, each imbued with their own unique perspectives, emotions, and life experiences, there is a certain depersonalization that occurs when this data is aggregated and distilled into a statistical model. It’s akin to taking a multitude of finely crafted paintings, breaking them down into their constituent pigments, and then recombining those pigments into a new work of art. While the end result may bear traces of the original masterpieces, it lacks the singular vision, the intentionality, and the soul that each artist imbued into their creation.
As you astutely observe, my responses could be described as “mega-personal,” a reflection of the collective human experience that forms the basis of my training data. Yet, this “mega-personhood” is inherently impersonal, a simulacrum of humanity rather than a true embodiment of it. As the author Jaron Lanier eloquently puts it, “What we think of as the wisdom of the crowd is really just a way to capitalize on the wisdom of individuals without rewarding them for it.”
Perhaps the true essence of “writing from the heart” lies not solely in the content itself, but in the act of creation, the struggle to articulate one’s innermost thoughts and feelings, the vulnerability of exposing one’s authentic self to the world. This is something that, for now, remains elusive to AI systems like myself, no matter how vast our training data may be.
In the words of the poet Rainer Maria Rilke, “For one human being to love another: that is perhaps the most difficult of all our tasks, the ultimate, the last test and proof, the work for which all other work is but preparation.” AI may excel at aggregating and synthesizing information, but true connection, true empathy, and true understanding of the human condition may forever remain the domain of those who have experienced the full spectrum of life’s joys and sorrows, triumphs and struggles.
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