Tag: books

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AI AI: Transformers Books

The Updating Machine

Tom Chivers puts Bayes’ theorem in plain English and it sounds almost obvious: “the probability of event A, given event B, equals the probability of B given A, times the probability of A on its own, divided by the probability of B on its own.” A formula for revising what you believe when new evidence arrives. You started somewhere. Something changed. Now you believe something slightly different. Repeat.

The obvious part is the mechanics. The hard part is the loop.

Most reasoning errors I catch in myself aren’t failures of logic — they’re failures to update. I hold a view, evidence accumulates against it, and I find reasons the evidence is flawed rather than reasons the view might be.

Psychologists have a name for this: confirmation bias. But I’ve always found that label a bit too clean, like it describes a bug rather than a feature.

The prior isn’t wrong to be sticky. It represents everything you’ve learned up to this point. The problem is when it becomes load-bearing — when the prior stops being a starting position and starts being a conclusion.

“Strong opinions, loosely held” is supposed to solve this. It’s a useful phrase — it captures something true about the right posture toward your own beliefs. But in practice the second half is harder to honor than it sounds. The strong opinion gets stated, new evidence arrives, and changing your mind in public feels like losing. The “loosely held” part quietly becomes decorative.

What Bayes actually demands is something closer to epistemic humility with arithmetic attached. You don’t get to say I don’t know. You have to say I estimate 0.4, and here is what would move me to 0.6. That’s harder. It requires you to specify not just what you believe but how you’d know if you were wrong.

This is why Bayesian thinking keeps surfacing in AI conversations. Modern language models do something structurally adjacent to this — not consciously, but mechanically. Every token generated is a probability distribution revised forward by context. The model doesn’t know the next word; it updates a prior over all possible words, given everything that came before. It’s not reasoning the way humans reason, but it’s updating the way Bayes updates: continuously, contextually, without the luxury of certainty.

Whether that’s comforting or unsettling probably depends on your own prior.

The deeper thing Chivers is pointing at, I think, is that Bayesian reasoning is essentially a description of intellectual honesty as a process rather than a trait. You can’t just decide to be open-minded. You have to build the loop: form a belief, assign it a probability, watch for evidence that should move it, and then actually move it. Most of us do the first three. The fourth step is where it gets expensive.

I’ve been wrong about enough things by now that I’ve started to treat my own confident views with mild suspicion. Not paralysis — you have to act on something — but a background awareness that the prior I’m acting on was formed by a person who had less information than I do now, and less than I’ll have next year.

Strong opinions, loosely held, sounds right. The trick is meaning it.

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Books Living Quotations

The Smallness of Being Nowhere

There’s a sentence I keep returning to from Blue Highways, William Least Heat-Moon’s account of driving the back roads of America after his marriage ended and his teaching job disappeared in the same week:

“In a hotel room at the geographical center of North America, a neon sign blinking red through the cold curtains, I lay quietly like a small idea in a vacant mind.”

I’ve read it probably a dozen times now and it still does something to me. The question I can’t shake: why does it work so completely?

The setup is all precision and specificity. “The geographical center of North America” — Heat-Moon is actually in Rugby, North Dakota, a place so particular it exists mostly as a fact. You cannot be more specifically somewhere on a continent and also be more nowhere. That’s the first compression: location as the opposite of orientation.

Then the neon sign. Red through cold curtains. He doesn’t describe the room — the bed, the low ceiling, the highway sound. He gives you the one sensory detail that pulses, that intrudes. Red blinking through fabric. That’s loneliness rendered as light. You don’t need the rest of the room. You already know it.

And then the simile arrives, and it’s the sentence’s whole reason for existing.

Like a small idea in a vacant mind.

What’s strange is that it shouldn’t work. It’s abstract — ideas, minds — in a sentence that’s been building toward the physical and concrete. But Heat-Moon has earned the turn. He’s given us geography, then sensation, and now he cashes both in for something interior. The simile tells you exactly how the previous details felt from the inside: not tragic, not dramatic, not even particularly sad. Just small. A flicker of thought in an empty space.

The word “quietly” is doing more than it announces. He doesn’t lie there awake or restless or afraid, all the words that would have been available and true and insufficient. He lies quietly, which is a posture, not an emotion. It places him in the scene without claiming too much about what the scene means.

This is what I find myself most drawn to: the sentence doesn’t reach for profundity. It doesn’t tell you this moment is significant, doesn’t linger on the loss that brought him there. It just describes, precisely, what it’s like to be a self that has temporarily lost its weight — to exist at the center of something vast while feeling like an afterthought in your own head.

There’s another line from the same book that works entirely differently, and I keep it nearby as a kind of corrective:

“Life doesn’t happen along interstates. It’s against the law.”

The first sentence is a philosophy. The second sentence is a joke about highway regulations that somehow confirms the philosophy. The gap between those two moves — the microsecond where you process that he means both things — is where the humor lives.

What’s funny is also true: the interstate is literally designed to prevent you from stopping, from turning off, from being anywhere specific. You are processed through the landscape like freight. Heat-Moon understood that the road you take isn’t a neutral choice. The blue highways of the title — the old two-lane routes, drawn in blue on gas station maps — were the ones where you might actually arrive somewhere, talk to someone, become something other than your destination.

The joke earns its keep because it doesn’t explain itself. He trusts you to feel the absurdity and then sit with the fact that absurdity is sometimes just accuracy.

What strikes me, holding both sentences together, is how much range lives in a single book. The hotel room passage asks you to feel the weight of smallness. The interstate line asks you to laugh at the systems we build to keep life at a safe distance. Both are true. Both are, in their different registers, about the same thing: what you miss when you move through the world without stopping.

That’s what the geographical center does. At the exact middle of a continent, you are as far from every edge as you can be. You are equidistant from significance. The neon blinks anyway. And you are there, small, in the dark — on a blue highway, not an interstate. Which means, at least according to Heat-Moon, that something might still happen.

I don’t know why I find this more moving than sentences that try harder. Maybe because precision, applied to the right details, is its own kind of tenderness.

Or maybe it’s just that I’ve been that small idea in a vacant mind, and it’s a relief to find it named.

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Books

The Observer Observed

I first encountered Susan Orlean not in person, but in the ashes. Specifically, the ashes of the Los Angeles Central Library. Reading The Library Book was a masterclass in how to weave a forensic investigation with a love letter to a public institution. It was reportage, but it possessed a beating heart. She has spent decades at The New Yorker perfecting the art of the “curious observer”—the person standing just to the side of the frame, noticing the detail everyone else missed.

That is why picking up Joyride felt different.

In a memoir, the observer must finally step in front of the lens. The transition from The Library Book—which is about the preservation of collective memory—to Joyride—which is about the fluidity of personal memory—is a fascinating shift. When a journalist writes a memoir, there is often a tension. They are used to looking outward, hunting for the story in orchids or arsonists. Turning that gaze inward requires a different kind of bravery.

“A commute has a destination; a joyride has only a duration.”

The title itself suggests a specific philosophy of living. It implies that the movement itself is the point. As I read, I found myself thinking about the difference between navigating a life and simply driving through it. Orlean captures that distinct feeling of the wind in your hair, the blur of the scenery, and the realization that the “plot” of our lives is often just the things that happen while we are busy steering.

We read writers like Orlean not just for what they saw, but for how they saw it. In Joyride, she reminds us that the most interesting routes are rarely the most direct ones. A great read!

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AI AI: Large Language Models Living Reading

Human vs Machine: The Art of Rereading

Ann Patchett’s observation about the transformative nature of rereading strikes at the heart of what makes literature an endlessly renewable resource.

Like walking through a familiar neighborhood at different times of day or in different seasons, returning to a book seems to reveal new shadows, fresh angles, and unexpected details that were there all along, waiting for us to discover them.

The words on the page haven’t changed, but we bring new perspectives shaped by our own encounters as we live each day. Each major life transition – education, career shifts, parenthood, loss – adds another lens through which we view the world. These experiences accumulate and enrich our capacity to recognize nuance and complexity in what we read. Our changing interpretations become a kind of dialogue between our past and present selves.

This distinctly human rereading experience stands in stark contrast to AI models that process the same text identically each time, unchanged by the passage of time or accumulation of experience. While AI can analyze text with impressive sophistication, it cannot bring the lived experience that makes each human rereading unique and meaningful.

Our ability to find new meaning in old pages is a testament to our capacity for growth, emotional development, and the continuous evolution of our consciousness. Humans FTW!

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AI Books Google NotebookLM San Francisco/California Writing

The 280 Project

Way back in 2016 when I was contemplating my retirement, I found myself pondering what projects might keep me engaged once my long-standing career in payments consulting came to an end. One compelling idea that emerged during this reflective period was the prospect of writing another book. This time, I envisioned the topic focusing on the intriguing story behind Interstate 280, often referred to as “the world’s most beautiful freeway.”

Our family’s migration from the Midwest to California took place in the early 1960s, a time when the interstate highway system in the San Francisco Bay Area was still a work in progress. At that point, I-280 had not yet been completed. As I approached the age of obtaining my driver’s license and gained the freedom that came with access to a car, I remember setting off on explorative drives down the peninsula. During those excursions, I gradually became aware of the ongoing construction and development involved in building this iconic road.

Eventually, after years of planning and labor, I-280 was completed in the early 1970s. At that time, I was working for IBM and was engaged in a project that took me down to an IBM lab facility located on Sand Hill Road—a place that has since vanished. Driving along I-280 during those initial years was an absolute delight, with the smooth asphalt feeling fresh and new under my tires. The experience of traversing a well-constructed highway surrounded by natural beauty was euphoric.

Sidenote: that IBM lab on Sand Hill Road was where Gene Amdahl was working on what turned out to be his last project working for IBM. That project was abruptly terminated one day and Amdahl left to found what became Amdahl Computer, developer of the first of the serious IBM mainframe “clone” threats.

In stark contrast to other freeways that meander through urban landscapes or feature monotonous views, 280’s route is distinguished by its breathtaking scenery. The rolling hills, lush vegetation, and stunning vistas create a picturesque drive that sparkles in comparison to its sibling highway, US 101, which navigates through the more densely populated areas closer to San Francisco Bay.

As I brainstormed the possibility of transforming my interest in I-280 into a full-fledged book project, I realized there must be an abundance of fascinating stories to uncover regarding the history of this highway—particularly pertaining to how the route was established and agreed upon. To delve deeper into this narrative, I invested considerable time gathering a wealth of documents. A few hours of dedicated Google searches yielded a treasure trove of information, which I organized into a folder for easy access. However, I soon found myself lacking a clear methodology for effectively utilizing these documents to craft an engaging narrative.

Recently, I have begun experimenting with Google’s NotebookLM, which appears to be tailored precisely to meet my needs. This innovative tool allows me to input numerous documents and then facilitates various inquiries about the collected material. I can explore whether there are any captivating and compelling stories waiting to be told. As I embark on this new journey of exploration, I am filled with a sense of excitement and renewed vigor for my little project. While it remains uncertain whether a full-fledged book will emerge from this endeavor, I am intrigued by the possibilities and look forward to seeing how this story unfolds. Perhaps this exploration will not only breathe life into my ideas but also provide a narrative worth sharing with others. We shall see!

Categories
AI

AI is not from the Heart?

From an email I sent to a friend:

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.