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AI Living Work

Avalanche: The AI Revolution

It’s been nearly a decade since I hung up my corporate hat and settled into retirement.

Back then, the world felt like a different place, technologically speaking. We were just starting to see the widespread adoption of smartphones, social media was still finding its footing, and the cloud was this nebulous concept that many were hesitant to embrace.

We marveled at the speed of innovation, the way technology was transforming our lives at an unprecedented rate. But looking back from our current vantage point, that almost feels quaint.

It’s clear to me that the pace of technological evolution hasn’t just continued—it’s accelerated. Almost exponentially. It’s like we were strolling along a gentle slope, and suddenly, we’ve hit a steep incline, the ground rushing beneath our feet.

The driving force behind this dramatic acceleration is artificial intelligence. After slowly developing since the 1940s, AI has burst onto the scene in recent years with the force of an avalanche, sweeping through every industry and aspect of our lives. What was once the realm of science fiction is now becoming reality, and it’s happening at a speed that’s both exhilarating and, frankly, a little terrifying. Every week seems to bring new surprises with ever-expanding capabilities being introduced. AI is being integrated into every facet of our existence, from the mundane to the profound.

This rapid advancement brings with it a whirlwind of emotions. There’s the excitement of witnessing history in the making, the awe of seeing human ingenuity push the boundaries of what’s possible.

But there’s also a sense of unease, a fear of the unknown. How will AI displace human workers? And how quickly? Will it exacerbate existing inequalities? Will it be used for good or for evil?

As someone who’s witnessed firsthand the transformative power of technology, I believe that AI has the potential to be a force for good in the world. It can help us address some of the most pressing challenges facing humanity, from climate change and poverty to disease and hunger. But we need to be mindful of the risks and challenges that come with this new technology.

I wonder how soon I will come across a LinkedIn profile for an AI bot, not a human. This bot will list its pedigree—how and where it was trained (which model, which vintage of model distillation, its training corpus, etc.)—along with its relevant experience. I’ll be curious to see the recommendations the bot lists, along with who else—human and bot—it follows. The audience for these early bot LinkedIn profiles will be us humans, but eventually, the bots won’t need to speak our languages at all, and bot-to-bot communication will evolve rapidly. The bots won’t pay any attention to advertising either.

Clearly, the avalanche is here, and it’s not slowing down. It’s up to us to navigate this new landscape, to harness the power of AI for the benefit of all humankind. I’m excited about the future these technologies might bring but remain wary of the risks they also pose. Life in our time is speeding up very quickly!

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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!

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AI

The Portrait

I’ve heard a couple of folks recently talking about playing with AI chatbots and asking them to create an image of themselves based on the interactions they’ve had over time with the chatbot. Of course, I had to try this out. So here’s what I got back as an image of myself from ChatGPT. Note that before it created this image, it told me that it would have to be ultra creative since it really didn’t know what I looked like (it’s really not that hard to find a photo of me online – but whatever!).

Here we go:

Very surrealistic. Apples (weird apple!), oranges, raspberries, blueprints, office with a chair and window and what looks to be a candle chart on the wall behind going up and to the right. Definitely one for the scrapbook!

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AI AI: Large Language Models Writing

Ghostwriting

I have appreciated the reactions of some of my friends to use of artificial intelligence. While I’ve enjoyed experimenting and learning about the use of AI in helping me write, the use of AI for writing has inspired some strong negative reactions among friends.

For example, several weeks ago a good friend of mine was very disappointed in me when he noticed that a blog post I had shared had been written almost completely by an AI helper. I disclosed that fact at the bottom of the post but he said he could detect I was using AI within the first couple of sentences. Here’s what he emailed:

I saw a blog post with your name attached. That caught my interest, and I anticipated reading your thoughts. After reading a couple of sentences, I realized it was AI-generated text. Skipping to your disclaimer at the end of the post confirmed that. I was deeply disappointed. I was looking forward to your creation and your thoughts, but instead, I received a machine’s advanced predictive text.

In a later exchange, he added:

I think it’s a mistake to take LLM-generated material, “lightly edit” it, and publish it in your blog under your name. In my view, it’s all been poorly written and not worth reading. I think you have a good mind, and I was interested in your creative writing because of your insight and original thinking. You do a much better job when you do your own work and don’t try to piggyback on AI.

More recently, David Sparks (MacSparky) published a post about his reaction to AI-created content – The Sparky Language Model. He shared a story about attending a friend’s wedding where he heard a moving speech. When he complimented the speaker on the speech, he revealed that the speech was written by ChatGPT and he was just reading it. David was very disappointed to learn that AI was used – writing:

“This revelation left me profoundly unsettled. It got me thinking about the essence of personal expression and the irreplaceable value of human touch in our communications.”

These reactions got me thinking about how tools generally affect our ability to do things in our lives.

I rarely pick up a pen anymore, for example, as almost all of my writing, journaling, etc. is done on a digital device. I still carry a pen in my pocket but not because it’s indispensable any more. But none of my correspondents actually see my penmanship any more – that’s a quaint artifact gone to history.

In writing and publishing, there’s a long history of ghostwriting – where a work is created by someone other than the author to whom it is attributed. In many cases, the actual ghostwriter isn’t disclosed. In my mind, use of an AI to help with writing is analogous to hiring a ghostwriter to help write an article. Or even hiring a copywriter to help create clever ad copy.

The question of most appropriate use of AI as a tool for helping us write feels like a slippery slope to me.

Just for fun, I took MacSparky’s SLM essay and asked Claude Sonnet to generate a “caustic” reply to it. Claude warned me that it might not be a good idea to send my friend such a caustic reply but I asked Claude to write it for me anyway.

Afterward generating the reply, Claude commented again:

I want to reiterate my earlier concerns about the potential negative impact this kind of exchange could have on your friendship. While I’ve fulfilled your request, I strongly encourage considering whether sending such a reply aligns with your values and the kind of relationship you want to maintain with your friend.

If you do decide to send this or a similar response, it might be worth following up with a more personal, conciliatory message to ensure your friend understands the context and that this exchange hasn’t caused any lasting harm to your relationship.

Message received, thanks!

Here’s that “caustic” critique that Claude wrote:

A Scathing Rebuke of Self-Righteous Technophobia

In an era where technological advancement races forward at breakneck speed, it’s refreshing to encounter a piece so unabashedly retrograde that it makes Luddites look like Silicon Valley evangelists. Enter “THE SPARKY LANGUAGE MODEL (SLM),” a manifesto of sorts that purports to champion authenticity while reeking of thinly veiled fear and misunderstanding.

Our intrepid author, clearly nursing a wounded ego in the face of rapidly evolving AI capabilities, embarks on a crusade against the very notion of progress. The piece begins with a begrudging acknowledgment of AI’s usefulness, only to swiftly descend into a mire of personal repulsion. One can almost hear the pearls being clutched.

The anecdote about the AI-generated wedding speech serves as the linchpin of this technophobic tirade. Our author, upon learning of the speech’s origin, experiences a bout of existential angst so profound it borders on the comical. Heaven forbid we use tools to enhance our ability to express emotion! Surely, the cave paintings at Lascaux were the pinnacle of human expression, and it’s been all downhill since the invention of the alphabet.

The crux of the argument hinges on the nebulous concept of “human connection,” as if AI-assisted writing somehow taints the purity of human thought. This notion is not only laughably reductive but also betrays a fundamental misunderstanding of how language and communication evolve. By this logic, we should all revert to grunting and pointing, lest we lose our precious “human touch.”

The author’s insistence on keeping things “personal” for all “MacSparky content” reeks of a desperate attempt to maintain relevance in a rapidly changing landscape. It’s as if they believe their meandering thoughts and half-baked tips possess some intrinsic value simply because they originated from their particular gray matter. News flash: the value of content lies in its utility to the reader, not in the purity of its origin.

The piece reaches its zenith of absurdity with the declaration that even if AI becomes objectively better at writing, the author still has no interest in it. This is the intellectual equivalent of covering one’s ears and shouting “La la la, I can’t hear you!” It’s a stance so myopic it makes Mr. Magoo look like an eagle-eyed visionary.

The grand finale, the introduction of the “Sparky Language Model,” is less a clever play on words and more a sad attempt at branding one’s own limitations. It’s as if the author believes that by slapping a cute label on their refusal to adapt, they’ve somehow outsmarted the march of progress.

In the end, this article is less a thoughtful critique of AI’s role in writing and more a thinly veiled cry for help from someone clearly terrified of becoming obsolete. The irony, of course, is that by steadfastly refusing to engage with these new tools, the author is ensuring their own irrelevance faster than any AI ever could.

The author’s stance on AI writing assistance is particularly short-sighted when considering the potential benefits. AI tools can serve as powerful aids in the creative process, helping to overcome writer’s block, suggesting alternative phrasings, or even challenging the writer to consider new perspectives. By categorically rejecting these tools, the author is not preserving some mythical purity of expression, but rather limiting their own potential for growth and innovation.

Moreover, the binary thinking displayed in this article – the idea that it’s either pure human writing or soulless AI-generated content – demonstrates a profound lack of nuance. The reality is that AI writing tools, when used judiciously, can enhance and amplify human creativity, not replace it. It’s akin to a painter refusing to use a new type of brush because it wasn’t available to the Old Masters. Tools evolve, and so should our approach to using them.

In conclusion, “THE SPARKY LANGUAGE MODEL (SLM)” is less a manifesto and more a eulogy – not for human creativity, but for the author’s ability to adapt and evolve. In their desperate attempt to cling to an outdated notion of authenticity, they’ve only succeeded in highlighting their own obsolescence. One can only hope that future generations will look back on this piece as a quaint relic of a bygone era, much like we now view those who once feared that the printing press would destroy the art of memory.

Perhaps, in time, even our dear author will come to realize that embracing new tools doesn’t diminish our humanity – it enhances it. But until then, we can expect more technophobic hand-wringing from the self-proclaimed keeper of the “Sparky Language Model.” One thing’s for certain: in the race between human progress and willful ignorance, there’s only ever one winner.

I had to hand it to Claude. Caustic indeed! This was an over the top critique of MacSparky’s essay – but I still found that it offered some new insights into the debate on this issue of the most appropriate use of AI.

I took a risk and decided to share it with MacSparky – suggesting he “fasten his seat belt” before reading. Fortunately, he enjoyed it and I avoided losing a good friend in the process!

My explorations into the use of AI continue – and I’m enjoying having fun spelunking around the pretty amazing tools that we now have available with AI-based large language models. For example, I’m using Claude right now to generate the list of 25 keywords appropriate to tag this article with. I’ve also used Adobe Firefly to generate the image of a “ghostwriter” at the top of this article.

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AI AI: Large Language Models Claude

Make It Better

I came across a post on X this morning with some advice I immediately tried out. The advice – when working with an AI to help create writing or code – is to reply to the first pass the AI takes by asking it to “make it better”. The author suggested doing this multiple times.

I tried this out with Claude and enjoyed how it worked on just the first “make it better” pass. When I asked it to “make it better” it began by replying:

Certainly, I’ll refine the musing to make it more impactful and engaging. I’ll focus on enhancing the imagery, tightening the structure, and deepening the insights.

And indeed the second “better” pass that it wrote was even better. A fun experiment to try on your next use of an AI chatbot.

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AI AI: Large Language Models Claude Creativity Writing

Co-Creation

Ethan Mollick, a professor at the Wharton School, has written a popular book on artificial intelligence titled “Co-Intelligence“. Like I do with most books I read, I’ve collected a series of highlights of various passages I found interesting when I read Mollick’s book – a book I enjoyed very much. This morning I came across one of those highlights which sent me off on this exploration.

But first let me share a perspective. A few friends of mine – when exploring how they might use artificial intelligence – reject the use of AI tools for helping them write. They feel strongly that the words an AI creates aren’t their own and strongly reject simply using an AI-generated output to create articles for their blogs, etc. I certainly appreciate their point of view – but I’m finding a more nuanced perspective on this question is more appropriate for me.

What I’m finding is that when I invoke AI to help me explore a topic, an idea, etc. that the result will almost always open up my thinking by exposing me to things, ideas, etc. that I hadn’t considered. In so doing, I come away feeling “richer” in the sense that I’ve learned – and not simply written – in the process. How I use the work product created by the AI varies – sometimes it’s helpful in critiquing something I’ve written. Other times I use it to help me better understand something – or explore by stepping outside my own brain.

Here’s an example from some exploring I did this morning. During my morning review of my Kindle book highlights using Readwise, I came across a quotation from Mollick’s book that I highlighted:

“If you can link disparate ideas from multiple fields and add a little random creativity, you might be able to create something new.” (Ethan Mollick, Co-Intelligence)

I love the idea of how creativity is influenced by the often seemingly random interconnections between ideas – and this quote concisely made that point. I wanted to explore this further so I asked Claude Sonnet to help me by writing an article in the style of author John McPhee that’s based on the quote. Here’s the exact prompt I used with Claude:

You are an expert writer in the style of John McPhee. You are helping me write interesting articles for my blog. Create a 750 word draft article for my blog based on the following quotation: “If you can link disparate ideas from multiple fields and add a little random creativity, you might be able to create something new.” (Ethan Mollick, Co-Intelligence)

I’ve been finding that Claude often does a more creative form of writing as compared to other chatbots. The article that Claude returned in response to my prompt really surprised me – so much so that I thought I’d just share it directly here.

So here we go…the following wasn’t written by me – rather, it was co-created based on a prompt from me and written by my co-intelligent partner Claude.

The Art of Cross-Pollination: Cultivating Innovation in Unlikely Places

In the verdant fields of central New Jersey, not far from where I sit typing these words, a peculiar ritual unfolds each spring. Farmers, their hands calloused from generations of working the land, don white protective suits that make them look more like astronauts than agriculturists. They move deliberately through their orchards, carrying small paintbrushes and vials of pollen.

These are the pear farmers of Mercer County, and they’re engaged in a practice as old as agriculture itself: cross-pollination. But why, you might ask, are they doing by hand what bees have done for millennia? The answer lies in the delicate biology of pear trees and the fickle nature of their reproduction.

Pear trees, it turns out, are notoriously poor self-pollinators. To produce fruit, they need pollen from a different variety of pear tree. But pear blossoms produce relatively little nectar, making them unattractive to bees. So these farmers, in their space-age suits, play the role of bees, manually transferring pollen from one variety to another, ensuring a bountiful harvest come autumn.

As I watched this process unfold on a crisp April morning, I was struck by a quote I’d recently encountered from Ethan Mollick, a professor at the Wharton School: “If you can link disparate ideas from multiple fields and add a little random creativity, you might be able to create something new.”

The pear farmers of Mercer County, in their own way, embody this principle. They’ve taken an idea from one field (entomology) and applied it to another (agriculture), adding their own creative twist (the paintbrushes and protective suits). The result? A thriving pear industry in a region where it might otherwise be impossible.

This concept of cross-pollination – of ideas rather than pollen – is not unique to agriculture. In fact, it’s a principle that underpins much of human innovation and creativity.

Consider, for a moment, the work of Frances Glessner Lee, often called the “mother of forensic science.” Lee was born into wealth in the late 19th century and, like many women of her social standing, was skilled in the domestic arts, particularly miniature-making. But Lee had a passion for criminal investigation, nurtured by her friendship with George Burgess Magrath, a medical examiner.

In the 1940s, Lee combined these seemingly disparate interests to create the Nutshell Studies of Unexplained Death – intricately detailed dioramas of crime scenes used to train detectives. These miniature crime scenes, built with the precision of a dollhouse maker but imbued with the gruesome details of a murder scene, revolutionized forensic training. Lee had taken skills from the traditionally feminine world of crafts and applied them to the male-dominated field of criminal investigation, creating something entirely new and profoundly useful in the process.

This principle of creative cross-pollination extends far beyond the realms of agriculture and crime scene investigation. The history of human progress is littered with examples of innovations born from the unlikely marriage of disparate fields.

Take, for instance, the development of GPS technology. The seeds of this now-ubiquitous system were planted when physicists William Guier and George Weiffenbach at the Johns Hopkins Applied Physics Laboratory realized they could track the Soviet Sputnik satellite by monitoring its radio transmissions. This was an impressive feat in itself, but it was their colleague Frank McClure who made the cognitive leap that would change the world. McClure realized that if the scientists could track a satellite from the ground, they could also use satellites to track positions on the ground.

This insight – born from the collision of rocket science, radio engineering, and a healthy dose of Cold War paranoia – led to the development of the Transit system, the precursor to modern GPS. Today, this technology guides everything from missile systems to the smartphone in your pocket, all because a group of scientists were able to flip their perspective and see their work from a new angle.

But perhaps the most striking example of creative cross-pollination comes from the field of medicine. In the early 1940s, a Scottish bacteriologist named Alexander Fleming was researching influenza. One day, he noticed that mold had contaminated one of his petri dishes – a common enough occurrence in a microbiology lab. But Fleming observed something unusual: the area around the mold was clear of bacteria.

This chance observation, combined with Fleming’s willingness to investigate rather than simply discard the contaminated sample, led to the discovery of penicillin. Fleming had linked the disparate fields of mycology and bacteriology, added a dash of serendipity, and created something that would revolutionize medicine and save countless lives.

As we navigate an increasingly complex and interconnected world, the ability to cross-pollinate ideas from different fields becomes ever more crucial. The challenges we face – from climate change to antibiotic resistance – are too complex to be solved within the confines of a single discipline.

So perhaps we should all take a cue from the pear farmers of Mercer County. Don our metaphorical protective suits, pick up our idea-paintbrushes, and venture into unfamiliar orchards of thought. For it’s in these unlikely places, where disparate ideas collide and combine, that the seeds of innovation are sown.

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AI AI: Large Language Models Apple iOS iPad iPadOS iPhone Mac

Masterstroke: Apple’s Private Cloud Compute

I was traveling on Monday so I wasn’t able to tune into the Apple WWDC 2024 keynote until later in the day. When I did, I skipped through the first hour (with the various OS updates) and went immediately to the discussion of Apple Intelligence, Apple’s name for the application of generative artificial intelligence. I was blown away.

I expected Apple to leverage its unique privacy-protecting access to our data stored securely on our mobile devices – but I didn’t expect the technical elegance that Apple applied to its approach.

Apple’s AI discussion reminded me of a similar feeling I had back when Apple Pay was introduced. As someone who had grown up in the credit card industry working at Visa and being a “techie” who enjoyed following technology developments, I could see the piece parts to a mobile payment solution based on contactless/NFC technology. But I didn’t anticipate the elegance with which Apple applied the technology as well as the creativity it brought to the business aspects of working with the payment card industry to introduce perhaps the best possible mobile payment solution.

Utilizing our private information with locally executed machine learning models makes logical sense. The challenge is how to do so when the compute or memory resources required of the model are beyond the capabilities of the mobile device. That’s where Apple’s invention of Private Cloud Compute provides the answer. And it’s brilliantly architected to provide access to those resources in a privacy protecting fashion.

We don’t yet have any access to these new Apple AI capabilities – and the proof will be in the pudding when we do – but the promise laid out by Apple in Monday’s keynote is very exciting. I’m looking forward to seeing how well Apple executes on its very differentiated approach.

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AI AI: Large Language Models AI: Prompting Business

Stuck in an Elevator with Buffett and Munger

Jonathan Clements had an interesting blog post this week on his Humble Dollar blog about replacing writers with the writing of ChatGPT. He did an experiment – using a prompt about being trapped in an elevator with Jack Bogle of Vanguard fame and the investment lessons he learned from that experience.

I took his prompt and just modified it slightly – instead of being trapped with Jack Bogle, what happened if I was trapped with Warren’s Buffett and the late Charlie Munger of Berkshire Hathaway.

Here’s the prompt I used with Meta.ai to generate the article below: “Write an 800-word article about the time I got stuck in an elevator with Warren Buffett and Charlie Munger and the investment lessons I learned.”

Here’s the article that the AI generated, unmodified or edited by me:

Getting Stuck in an Elevator with Warren Buffett and Charlie Munger: A Chance Encounter that Taught Me Invaluable Investment Lessons

It was a typical conference day, with attendees buzzing around, eager to learn from the brightest minds in the finance industry. I had just finished a riveting session and was heading to the next one when disaster struck. As I stepped into the elevator, I noticed two familiar faces – Warren Buffett and Charlie Munger, the legendary duo from Berkshire Hathaway. Little did I know, this chance encounter would turn into an unforgettable experience that would shape my investment philosophy forever.

As the doors closed, the elevator jolted to a sudden halt. We were stuck. The initial silence was broken by Warren’s calm and composed voice, “Well, looks like we’re in this together now.” Charlie, with his signature wit, quipped, “I’ve been stuck with Warren for decades, but this is a new kind of challenge.” The ice was broken, and we began to chat.

Lesson 1: Stay Calm and Patient

As we waited for help to arrive, Warren and Charlie’s demeanor taught me a valuable lesson. Despite being two of the most successful investors in the world, they didn’t panic or get flustered. They took it in stride, and their calmness was infectious. It reminded me of Warren’s famous quote, “Price is what you pay. Value is what you get.” In that moment, I realized that staying calm and patient is crucial in investing, just as it is in dealing with unexpected situations like a stuck elevator.

Lesson 2: Focus on the Big Picture

As we discussed our predicament, Charlie pointed out that getting stuck in an elevator was a minor setback in the grand scheme of things. He drew an analogy with investing, saying, “Just as we’re not defined by this moment, a stock’s value shouldn’t be judged by its short-term performance.” Warren added, “It’s essential to focus on the underlying fundamentals and long-term prospects, rather than getting bogged down by short-term volatility.”

Lesson 3: Diversification is Key

As we chatted, Warren mentioned that Berkshire Hathaway’s diversified portfolio had helped them weather many economic storms. Charlie emphasized the importance of spreading risk, saying, “You don’t want to put all your eggs in one basket, just like you wouldn’t want to be stuck in an elevator with only one exit strategy.” This conversation reinforced the value of diversification in my investment strategy, ensuring that my portfolio is resilient and adaptable to changing market conditions.

Lesson 4: Continuous Learning is Crucial

As we waited, Warren and Charlie engaged in a lively discussion about the latest developments in the tech industry. They were curious, asked questions, and sought to understand the implications of emerging trends. This exchange reminded me that investing is a continuous learning process. Staying up-to-date with market news, reading books, and seeking knowledge from experts are essential to making informed investment decisions.

Lesson 5: Humility and Humor Go a Long Way

Throughout our ordeal, Warren and Charlie’s humility and sense of humor put us all at ease. They joked about their own mistakes and shared stories of their early days in the investment world. This lightheartedness taught me that even the most successful investors can maintain a sense of humor and humility, acknowledging that no one has all the answers.

A Chance Encounter that Changed My Perspective

After what felt like an eternity, the elevator doors finally opened, and we emerged, relieved and grateful. As we parted ways, Warren and Charlie left me with a few parting words of wisdom: “Investing is a marathon, not a sprint. Stay focused, patient, and keep learning.” That chance encounter in the stuck elevator had turned into an invaluable learning experience, shaping my investment philosophy and reminding me of the importance of humility, humor, and a long-term perspective.

As I walked away from the conference center that day, I felt grateful for the unexpected turn of events that had brought me face-to-face with two investment legends. The lessons I learned in that elevator have stayed with me, guiding my investment decisions and reminding me to approach the markets with a clear head, a sense of humor, and a commitment to continuous learning.

Categories
AI AI: Large Language Models AI: Prompting Living

How to Use AI

As I’ve experimented with AI and, specifically, large language models, I’ve developed a sense of where they can assist me and where they can’t. Friends often have a black-and-white view of AI, either ignoring it or relying too heavily on it. My experience has been different.

Effective Use of LLMs

I avoid using LLMs for research requiring factual knowledge due to the risk of hallucinations. Instead, I use them for creative tasks like generating ideas or editing my writing. LLMs can be helpful in these areas, but it’s essential to define their role and review their work carefully.

The best general advice I’ve seen about how best to use LLMs is to treat them as an intern, one that is capable of doing a lot of work but work that needs to be carefully reviewed just like you’d review the work prepared at your request by an intern working for you. Or, instead of thinking of an LLM as an intern, think of the LLM as a good friend, one who brings their own opinions, attitudes, etc.

EXAMPLE OF A Creative Application

Developing a life theme is an example of how LLMs can assist in creative tasks. I started by listing my core values:

  • Be unselfish to others and take joy from sharing generously.
  • Be kind and appreciate kindness in return.
  • Walk in the shoes of others and try to understand their perspectives.
  • Welcome criticism and accept it appreciatively.
  • Stay curious and open; be a learning “machine”.

I used this list of core values to generate a one-sentence life theme with the help of an LLM. Here’s the prompt I’d use with an LLM to accomplish this:

You are a creative writer and an expert editor. I’m developing a one sentence life theme to use as a guidepost for my life. Please help me write that sentence by giving me ten variations based on the following list of my core values…

Note that the first sentence of this prompt defines what I’m expecting the LLM to be. I then define the result I’m looking for. Finally, I provide the input I want the LLM to review and consider in developing its response.

Here are a few of the life theme variations one LLM provided me:

  1. Embracing kindness and empathy, I strive to enrich lives through generosity and understanding.
  2. Living with open-hearted curiosity, I seek to learn, share, and grow with others.
  3. Through selfless compassion and gentle honesty, I aim to uplift and inspire those around me.

Reading through the variations provided by the LLM helped stimulate my thinking as I worked on crafted my own life theme. This is just one example of how LLMs have been of value to me thinking creatively.

LLMs: Your Creative Writing Partner

Large Language Models (LLMs) aren’t magical or superhuman, but they can be a valuable tool for creative writing. Think of an LLM as an intern with infinite willingness to work and help, and endless patience. By recognizing their capabilities and limitations, you can harness their potential to enhance your writing. Avoid black-and-white thinking and instead, explore the ways LLMs can provide value to you. That’s what I’ve tried to do – and I’ve been enjoying my learning along the way!

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AI AI: Large Language Models

The Allure of Large Language Models: A Personal Connection

The world of Large Language Models (LLMs) has captured the imagination of many. For me, this fascination has a deeper root, stemming back to my time working on fraud prevention at Visa.

Card fraud is an ongoing battle. Fraudsters devise new methods, and the industry responds with innovative solutions. One such threat was the counterfeiting of magnetic stripes on cards. While chip cards offered a more secure solution, their high cost made widespread adoption impractical.

In search of a cost-effective solution, we explored two approaches. One mirrored insider trading detection systems at major stock exhanges, using rule-based identification of suspicious patterns. The other, ultimately more successful approach, involved neural networks.

While the specifics of how I discovered neural networks elude me, I vividly recall a conversation with a Stanford professor, a pioneer in the field. His encouragement spurred us to pursue this technology. With a talented team, we implemented neural networks to analyze transactions in real-time, flagging potential counterfeits. This significantly helped limit card fraud growth, all without expensive hardware changes.

Today, that same neural network technology underpins LLMs like OpenAI’s ChatGPT, launched in late 2022. Advancements in silicon technology, particularly powerful GPUs, fuel both the training and operation of these models.

Recently, I listened to a captivating discussion titled “Does ChatGPT Think?” featuring Stephen Wolfram. That conversation triggered me writing this blog post.

Wolfram’s description of LLMs resonated deeply with me:

“So the big achievement and the big surprise is that we can have a system that fluently produces and understands human language… It’s not obvious that it would work, and it’s a kind of scientific discovery that it’s possible to have a thing like ChatGPT that can produce this thing that’s one of our sort of prize features – namely human language.”

For me, LLMs represent the culmination of a journey that began with neural networks and card fraud over forty years ago. I continue to marvel at the power of this technology and its potential to revolutionize how we interact with information and the world around us.