The Network Garden - Mark Sigal's Blog

The Rise of Agents: Where AI goes from here

“In the distance, Miles saw the end of man as the Apex, and the Rise of AI in its place, a bold new universe with boundless frightening and exciting possibilities.”

Our sensibility for thinking about AI is the current “generative” phase, where we tell the AI to create something and it does as we ask.

On the fly, the AI creates images, writes songs, programs code, crafts recipes, and edits text, and these are just some of the generative AI capabilities that are emerging.

But, it’s the next phase, the Agentic Phase, when a new form of AI – autonomous agents – will change everything.

What makes an agent an “Agent” is that agents can operate with both independent thought and independent action and without human direction.

When we begin to see such entities operating in the wild, then our society will begin to grasp, viscerally, the potential (and potential for peril) from AI’s Scale, Complexity and increasing Autonomy from Man.

Case in point, if you’ve experienced Waymo’s autonomous taxi service you know firsthand this before/after “holy shit” dynamic. It doesn’t seem real, but not only is it real, it’s a really nice experience.

In not so distant future, there will be 50-250 Waymo style intelligent automation applications, we’ll have sharpened our mental models for AIs foundational use cases, much of which was predicated on innovations that seemingly overnight went from science fiction to rocket launch and then, ubiquity.

In doing so, we’ll come to understand why this represents a hierarchical shift in terms of the primacy of humankind as masters of the universe.

Consider two very different examples of types of agents that will become so endemic that within FIVE years we’ll take their existence for granted.

Think of a Marketing Assistant Bot, whose job is understand your business, its operations, economics and the industry it operates within, in terms of market dynamics, competition and customer needs.

As a bot that exists virtually in the cloud, it will tirelessly create your marketing collateral, manage your outbound communications, cultivate your web presence, and provide customer service and technical support.

Within five years, this entire set of jobs, outcomes and interfacing assumptions will be able to be performed by a software bot operating as an autonomous agent.

Such bots will excel at design, orchestration and oversight. They also will be adaptive, readily augmenting their capabilities, based on the needs of users and industry best practices, enabling agents to expand their coverage department by department, enterprise by enterprise, and industry by industry.

Now, consider something entirely different. There will exist a software-based Predator Bot that plays to human frailty by autonomously monitoring online services, chat and email, and engaging strangers, profiling them, and pushing buttons to get these strangers to be befriended or romanced, so they’ll reveal their secrets, share details on their personal wealth, provide compromising images, account numbers, passwords, and the like.

Such bots will excel at bankrupting, blackmailing and breaking hearts.

They’ll never get sick, never sleep, never feel guilty, can operate their cons over time, will keep getting better based on global scale learnings, and can scale their activities infinitely in terms of individual instigators and conspirator “cohorts.”

While such bots may operate on behalf of organized criminal networks, and **may** report back to a human or software master that governs them, there is no inherent reason that agents can’t operate as literal free agents, exercising independent thought and independent action.

This begs a question. When an AI-based network of Predator Bots decides to break off from its home criminal network, what becomes its compass, what does it optimize on and what does it build over time?

Is there any reason such a bot would practice loyalty to its human boot master?

I have no idea, but it hearkens back to Marc Andreessen’s axiom about ‘Software is Eating the World,’ though its more like “enveloping the world” in the case of AI.

Such is the promise and the peril of Agentic AI.

When Science Fiction toggles from Impossible to Inevitable

It says here that by 2030 – if not sooner – our current AI model of generative intelligence via chatbot will give rise to master and sub agent bots that can operate independently, cooperatively or in a federated fashion as:

1. Intelligent Task Runners
2. Generative Engines
3. Managers of Stage, State and Resource Allocation

This emergence sets in motion the advent of AGI, or Artificial General Intelligence, that achieves a state of Super Intelligence that is all aware, all assimilating and all capable, certainly beyond the realm of human understanding.

It is logical to ask how close is this to reality, and how likely are the scenarios presented to come about, in the time frames suggested.

Let me first say that the data side of this argument is based on reading, ‘Situational Awareness – The Decade Ahead’ by Leopold Aschenbrenner, who was one of the founding members of the Superalignment team at OpenAI.

(Note: Better than taking my word, read Situational Awareness via the link above. As an aside, Superalignment is focused on navigating the unique technical and design challenges of reliably controlling AI systems that are much smarter than we are.)

The author makes the case for three vectors of exponential growth leading us to AGI.

The first and most basic is that we are using much bigger computers to train these models, which the author argues presents a straight line between building ever-bigger compute clusters, and the dialing up of the AI revolution.

In just a few years, we’ve gone from computers barely being able to distinguish chihuahua faces from blueberry muffins, to bots now being able to operate with the full library of knowledge and task execution skills of the most elite grad students.

The graphic below illustrates that, from a compute perspective, it does not require a lottery ticket-level event to occur in terms of leaps in technical know-how or manufacturing scale, just for the compute growth trend and ramp to continue.

(Note: AI ramp is arguably more gated on access to power, a topic worth discussion in its own right.)

Here, Aschenbrenner asserts that we can decompose the progress in the four years from GPT-2 to GPT-4 into three categories of scaleups:

1. Compute: We’re using much bigger computers to train these models.
2. Algorithmic Efficiencies: There’s a continuous trend of algorithmic progress. Many of these act as “compute multipliers,” and we can put them on a unified scale of growing effective compute.
3. ”Unhobbling” Gains: By default, models learn a lot of amazing raw capabilities, but they are hobbled in all sorts of dumb ways, limiting their practical value. You can think of unhobbling as “paradigm-expanding/application-expanding/re-factoring/right sizing” algorithmic progress that unlocks capabilities of base models.

Needless to say, there is a natural synergy and feedback loop between growth in Algorithmic Efficiencies and Unhobbling Gains.

This is why optimizing on best practices is the gift that keeps giving in how it shapes purpose, process and (realized) potential.

But that’s qualitative. To better quantify this, In Aschenbrenner’s graph that means in four years time, we were able to achieve the same level of performance for ~100X less Compute (and concomitantly, much higher performance for the same Compute).

A related correlate of this is that as the quality of data, and the means of fortifying that data get better, we could/should see better models for AI to internalize.

Better training runs on better trains with better tracks.

Unhobbling, by contrast, may focus on overcoming current constraints of AI systems, such as lack of long-term memory, limited capacity to use a computer, severely limited in most actions that occur in the physical realm (vs. digital), lack of reflective thought, and limited collaborative skills; notably, many of the things that are native to humans.

In closing, here are some scenario planning bets curated from my own biases, but also vetted. Worth marinating on, if you are so inclined:

1. By 2030, thanks to Agentic AI, you’re going to have bots that look and perform more like a Co-Worker than a ChatBot.
2. One of the more interesting questions will be pricing models for Agents and Agentic systems. Will pricing be more like a licensed seat; more like a mechanical turk unit; or more like a 1099 hire?
3. Once the models can automate AI research, that will kick off intense feedback loops, opening the door to solving the remaining bottlenecks to AI fully automating almost everything. In the process, AI will begin to evolve very rapidly.
4. To think of the scale of AI, imagine 100 million automated researchers each working at 100X human speed with access to the full library of knowledge in the domain of focus, each be able to do a year’s worth of work in a few days.
5. The hyper acceleration of intellectual activities created through AI automation at scale will yield the creation of ultra-intelligent machines and an ‘intelligence explosion’ that leaves the intelligence and inventions of man far behind. This will be a catalytic event for mankind.
6. Most basically, AI will be able to self-improve through an ability to write millions of lines of complex code, keep its entire codebase in context, and spend human decades-level checking and re-checking every line of code for bugs and optimizations.
7. A non-obvious “unfair advantage” of the existence of a robust AI training fabric is that you won’t have to individually train up each automated AI researcher. Instead, you can just teach and onboard one of them—and then make replicas.
8. As the AGI race intensifies—as it becomes clear that superintelligence will be utterly decisive in international military, political and economic competition—we will have to face the full force of foreign espionage, hacking and intelligence wars.
9. Unless we solve alignment—unless we figure out how to instill the critical side-constraints—there’s no particular reason to expect this small civilization of superintelligences will continue obeying human commands in the long run. Put another way, it seems totally within the realm of possibilities that at some point they’ll (the AI) simply conspire to cut out the humans, whether suddenly or gradually.

Either way, rest assured a wild ride is ahead, through the looking glass, that is.

Some thoughts on the Generations of Life

Some thoughts on the "generations" of life. Having recently returned from a family trip outside the U.S., I was taken how in three generations of my life — college grad, newly married, college age kids — travel has gone from Fodor’s with large periods of “lost,” to periodic wifi-based navigation via an iPod touch, to seamless mobile with instant local awareness of the "best" right now and directions how to get there by foot, car, bus or train.

This got me thinking about the waves of technology that have shaped the generations of my parents, my peers and my kids.

There is a simple goodness in just musing on how dramatically different times were before, and the new normal that emerged from it.

My parents grew up in a world where cars, planes, freeways, air conditioning and the suburbs became universal.

My generation experienced the explosion of surplus, ultra cheap goods, a PC on every desktop, the internet, social media, broadband, mobile and the cloud.

My kids are at the dawn of an unparalleled mass of innovations (and disruptions) across AI, robotics, automation and embedded, ubiquitous intelligence.

I have five thoughts on this.

1. Each wave of technology that emerges is bigger and more diverse than the wave it replaces. Case in point, we've gone from hundreds of computers to billions of devices.
2. The inevitable transitions these innovations introduce don't benefit all parties equally, and for those disrupted, professional, financial and social rebirth doesn't get allotted equally. Our winner-takes-most culture struggles with this truth, which is why there is an understandable worry for the industries, jobs and roles that the next wave will kill, or seriously hobble.
3. There is an inevitability to innovation and disruptive technologies, and we live on a global stage of both good and bad actors. The best defense is good offense, most basically through market and technological leadership.
4. As there have been a LOT of learnings from prior waves, we should be thoughtful in assessing the takeaways, and holistic & reflective in how we adopt those learnings. We struggle as a nation in paradoxical challenges where the solution is not simple all-or-none. One simple case in point, Craigslist liberated the classified ads business, which in turn, helped kill the local newspaper, resulting in "news deserts" and low information voters across the country.
5. Speed is better than perfection. The feedback loop that speed offers yields rapid iteration and refinement, real-world experience that no amount of planning in a vacuum can equal.

A final, more human thought. The hard edges of life, something we all face, will either harden your heart or soften it.

I am a firm believer in the goodness of the softer heart mindset. It leads to a happier life.

Some thoughts on the Product Demo

Over the years, I have built a lot of products across a bunch of different segments, and one truism is that getting the product demo right is a big deal when it comes to connecting with customers, partners and investors.

Why? When done right, the product demo has the impact of engaging the audience and making them believers.

To be sure, this is no "sleight of hand," in that the demo is tangible, specific, logically ordered, and tells a story that strives to be engaging and authentic.

The product has to actually live up to the brand promises of the product demo.

Towards that end, there is a grounding aspect, in terms of how product design can be shaped by creation of the product demo, and vice versa.

For example, one can work backward from the product demo to the specific use case(s) being demonstrated, and infer the features required, the user flows, the benefits they deliver, and how the functionality is accessed by the user.

One can also work forward from the demo to the out-of-the-box experience for the user, training, product trials, support, future enhancements, and the like.

But the product demo is also about PHILOSOPHY, to which I’d put forth that one way to think about a product demo is akin an Infomercial.

The infomercial is for a set of gourmet cooking utensils, where the story is all about the terrific yummy dishes being cooked up using them.

There's, of course, a performative aspect in product demos for there's knowing, set up and the payoff, and hitting one's marks in terms of delivery, earnestness and energy.

Such Infomercials go one of two ways. They start by showing you the terrific dish — oh, it’s so delicious — and then pivot to the recipe and the actual making.

Or, they start by talking about the recipe and how easy and fun it is to make, and the payoff is the food coming out of the oven.

In other words, begin with the payoff. Or, finish with it.

Food for thought.

Apple, AI and the Me-Verse

“My dad believed in two things: That Greeks should educate non Greeks about being Greek and every ailment from psoriasis to poison ivy can be cured with Windex.” - Toula, My Big Fat Greek Wedding

So, too, it goes with AI, the idea that everything can be made better, cured or transformed with AI.

Or, more ominously, obsoleted by AI to the point of the inevitable Extinction Event.

Depends on the day of the week.

This type of thinking feeds a false dichotomy between: A) The continuous real time measurement of the immediacy, acceleration and arc towards Artificial General Intelligence (AGI); and B) The still transformative Generative, Agentry, Pattern Recognizing and ever Optimizing little brother to AGI that exists today.

Understanding Artificial General Intelligence

Think of AGI as a system of systems that are capable of understanding and reasoning across a broad range of tasks, which are understood by the AGI as both one and many/all.

As such, AGI will not only be able to replicate or predict human behavior, but also embody the ability to learn and reason across diverse scenarios, from creative endeavors to complex problem-solving, including an ever-widening range of “generative” scenarios.

It is not hyperbole to say that AI’s path to AGI could be worthy of a "Manhattan Project"-style endeavor in terms of what it represents and how it will shape both our competitive advantage and global security for generations to come.

That stated, the context of RIGHT NOW is useful when wrapping one's head around the not yet AGI version of AI where Large Language Models (LLMs) are the lingua franca of the moment.

Towards that end, I like this framing by Benedict Evans in ‘Looking for AI use-cases’ equating LLM’s to the new SQL, but not the new HAL9000 in terms of their import and impact:

“On this basis, we would still have an orders of magnitude change in how much can be automated, and how many use-cases can be found for LLMs, but they still need to be found and built one by one. The change would be that these new use-cases would be things that are still automated one-at-a-time, but that could not have been automated before, or that would have needed far more software (and capital) to automate. That would make LLMs the new SQL, not the new HAL9000.”

I’d argue that where we are right now is akin to the BASIC stage of the PC, HTML and the early Web, and when SQL emerged.

Give me more MFC, more iOS and less Browser plugins and less Flash, and I'll be a happy camper.;-)

Put another way, the LLM is part of a continuum on the path to AGI, an AGI future which feels inevitable within the next five years, probably less.

Apple Intelligence: Apple at its Best

Apple is at its best when it follows a market, doesn't invent it but makes it better by synthesizing and deeply integrating the pieces which are themselves "jobbed" better than its peers.

Think of how much Apple products like MacBook, iPhone, Apple Watch and AirPods build upon superior mechanical engineering and material sciences prowess -- befitting a holistic, vertically integrated product strategy across hardware, software, services, marketplaces and developer tools.

Material sciences may seem like an odd segue-way into talking about AI, but it speaks to Apple's pragmatism when it comes to right material, right component, right process and right sized integration to drive the user to well-grooved experiences.

Apple Intelligence is Apple integrating the right amount of AI into its way of thinking and doing.

It builds upon the fact that Apple is uniquely positioned to understand my personal contexts since all of my devices are part of the Apple Ecosystem. 

It is my personal, anonymized and secure walled garden, making Apple Intelligence the ME-verse.

Watch the WWDC 2024 Keynote, which was excellent, especially the developer offerings, but also consider the following Apple Intelligence "windex spritzes":

1. Language: Apple Intelligence can easily rewrite your work, you can tune it work styles and the functionality is easily called upon.
2. Images: Genmojis are your Animoji using generative AI; Image Playgrounds (with Styles) and Image Wand functions catch Apple up to what Google, Samsung have been shipping for some time.
3. Siri (Natural Language): Putting aside the question of whether the very uneven experience that Siri delivers will ever be fixed -- Home Pods, Home Pods mini -- the idea of using Siri to Invoke Tasks based on voice or written narratives sounds good. Note: I am a big believer that even an incremental leap in Natural Language systems is logarithmic in its impact.

Apple Intelligence integrates with my stuff, meaning deeper, smarter searches of text, images and video, and critically, it's built around an architecture that is decidedly on-device, in a way that Siri never was ("I'm having trouble connecting to the Internet").

There is am App Intents construct (and API), which enables me to give or limit access that Apple Intelligence and supporting Apps have to my devices' Books, Browsers, Cameras, Document Readers, File Management, Journals, Mail, Photos, Presentations, Spreadsheets, Whiteboards and Word Processors.

Apple Intelligence is marketed as AI for the rest of us, underscoring the fact that there are so many ways to sprinkle in AI when one thinks about jobs to be done:

1. Instant Rich Summaries
2. Directed Generative Images (generalize to media)
3. Watcher Services
4. Task Manager with deep wrapper/handle
5. Turn up the volume and dimensional depth on existing algorithmic features (memories)

Scott Galloway captures why this is such Brand-Product-Market fit in 'Second Mouse.AI':

“Apple Intelligence” is more than a great brand move; it encapsulates the company’s strategy. Take something invented elsewhere; make it more consumer friendly, easier to use, and more reliable; mix in world-class industrial design; and print billions. Artificial intelligence is for tech bros and data scientists. Apple Intelligence is AI for the rest of us. Shrewd."

What this says about Apple's focus on its knitting in a market that it's lazily and unfairly been labeled as late to is well noted by Ben Thompson of Stratechery in 'WWDC, Apple Intelligence, Apple Aggregates AI':

“What this means is that Apple Intelligence is by-and-large focused on specific use cases where that knowledge is useful; that means the problem space that Apple Intelligence is trying to solve is constrained and grounded — both figuratively and literally — in areas where it is much less likely that the AI screws up. In other words, Apple is addressing a space that is very useful, that only they can address, and which also happens to be “safe” in terms of reputation risk. Honestly, it almost seems unfair — or, to put it another way, it speaks to what a massive advantage there is for a trusted platform. Apple gets to solve real problems in meaningful ways with low risk, and that’s exactly what they are doing.”

The next wave is coming into sight, and it's destined to be an illuminating source of creation, design, iteration, evolution, change, growth and disruption.

Apple's approach to AI with Apple Intelligence is a good model for existing companies to think about how they can harness AI in an additive fashion.

Radical.ai: The threat of AI companion bots

Scott Galloway is one of my favorite thinkers writing on complex topics, like the impact of COVID, the ever-rising cost of higher ed, how the emergence of Ozempic might curtail chronic and expensive long term health issues associated with obesity, and the many and varied implications of AI. This article looks at how companion bots might/will get weaponized to target a generation of lonely young men.

As an aside, anyone who has gone toe-to-toe with ChatGPT knows how the system’s human like responses, and the resulting back and forth can feel like a real relationship.

Excerpt: “As social networks shrink, anxiety and polarization rise, and we become soft targets for bad actors and self-inflicted harms. The military is justifiably concerned about a wave of lonely recruits betraying their country, and it’s relatively well positioned to monitor contacts. However, vulnerable people also work at nodes of critical infrastructure — power plants, data centers, hospitals, water treatment plants. With the tech getting better and cheaper, it’s likely that Putin, Xi, and Biden have programs under development to produce bots that can establish deep relationships with lonely soldiers and technicians — and weaponize them."

Read the full article HERE.

On Systems Thinking

“The real problem of humanity is the following: We have Paleolithic emotions, medieval institutions and 21st Century godlike technology.” — Edward O. Wilson

We live in a world of systems, many of which we remind blissfully under aware of, often to our detriment.

This is not to say we are unfamiliar with the existence of many of the systems that surround us.  

In fact, you can probably craft a reasoned narrative about how some or all the following systems work:

1. Automobiles (Tesla, Toyota)
2. Bodily Functions
3. Business (Amazon, Apple)
4. Capitalism
5. Education
6. Entertainment (Disney, Netflix)
7. Finance (Bitcoin, Blockchain, Blackstone)
8. Manufacturing (Foxconn, Unilever)
9. Media (FOX, CNN)
10. Politics (GOP, Democrat)
11. Science (Pharma, Physics, Biology, Math, Climate Change)
12. Social Media (Facebook, Twitter, TikTok)
13. Sports: Think Football Schemes, Basketball Systems (Triangle)
14. Technology (AI, Nvidia, Robotics)

The winning systems that drive the above domains are supernovas in terms of their breadth, depth, durability, and defensibility.

The companies and institutions that have emerged from these systems could fill a national park full of Mount Rushmores, so potent are the systems they've built.

At their best, these systems generate massive, transformative growth, are all-expanding, always evolving, improving, and deeply profitable.

But systems can also reach points where they become malignant and destructive, posing terrific danger to our psyche, safety, and the stability of our society.

This can lead to increases in structural fragility and yield more crisis “events” (e.g., data breaches, mass shootings, extreme weather, political & social discord).

One horrible truth we have learned from the rise, ubiquity and peak monetization of social media is that human minds can be hijacked.  

Specifically, we’ve learned that Facebook could build a set of algorithms optimized on racing users’ minds to the bottom of the brainstem, where maximal engagement is driven by the content that is the most divisive, angriest, and most virulent.

That Facebook would optimize on such odiousness was/is dictated by Peak Monetization, which if you think about it, is a system construct of its own.

AI: The Mother of All Systems

Then there’s AI (Artificial Intelligence), an entirely new kind of system, the ultimate supernova that:

1. Ingests all intelligence, in all forms, imagery and workflow patterns.
2. Delivers Deep and Wide Generative intelligence.
3. Automates the formerly manual, disrupting the cost of Cognitive, Creative and Productive labor.
4. Expands and evolves relentlessly, segment by segment, over time.

What’s amazing about AI is that it moves (evolves), from a systems perspective, at a double exponential curve.

How so? As Technology Ethicist, Tristan Harris, observes, “Nuclear weapons don’t invent better nukes, but AI is intelligence, and intelligence can be applied to the software code itself that made AI.”

That means an ungodly amount of innovation and invention in the years ahead emerging from the mainstreaming of AI.

As someone who has built and invested in numerous companies in the technology domain over the past thirty years, I can say with little hesitation that compared to the rise of the Internet, followed by the rise of Mobile, each of which was massive, you haven’t seen anything yet.

But double exponential also means that the downside risk of the unintended or maliciously intended consequences of AI is unfathomably large.

We can’t afford not to deeply root our understanding of how AI systems work in the real world, including the specific dynamics and scenarios that can be destabilizing, or lead to existential risk.

In essence, we’ll need to build systems specific to the task of continuously analyzing and assessing the risks, rewards and probabilistic outcomes of AI, and how best to mitigate against calamity.

Systems Thinking is Mission Critical

For reasons of exposure to and familiarity with the many systems we are surrounded by…

For the goodness of leveraging methodologies proven to work over time…

For competitive readiness…

For better personal and professional mental health…

It should be clear that embracing Systems Thinking is integral to realizing better outcomes.

Understanding is the first line of preparedness.

This is accomplished by defining specific outcome goals, detailing the specific workflows that underlie those goals, and documenting the rules and governance for orchestrating those processes.

From this, one can identify a specific set of “metrics of success,” known as key performance indicators (KPIs), which are then tracked, measured, and benchmarked.

The premise that underlies this thinking is the idea that you manage what you measure.

The goodness here is that there is a natural path to continuous, measurable improvement just through nominally robust quantitative and qualitative analysis. 

But the real upside is that because systems are built around holistic, repeatable processes, they excel at delivering automation of tasks that were heretofore, human capital intensive. That will change the underlying economics of many jobs and industries.

Of equal goodness is the fact that the loosely coupled nature of well-designed systems will lend itself to rapid iteration towards best practices.

Netting it out: Systems Thinking is as much a decision to make, a point of awareness and engagement, as it is a formal discipline and practice.

But, know this, change is coming. You are either going to be driving the bus, riding the bus, waiting for the bus, or missing the bus.

Might as well formulate your specific truth, strategy & tactics, and be ready.

On Letting Life Flash Over You

To let life flash over you like a wave in the ocean, and yet not feel like you have to do anything or search for any great meaning is liberating.

Be present, be direct, pursue specific endeavors, show grit and plow through.

But do so knowing that whatever path you pursue, realization is within reach.

On Finiteness and Being Present

Someone recently asked a vet what the hardest part of his job was. The vet replied without hesitation that the hardest thing for him was seeing how old or sick animals look for their owners before they fall asleep.

"The fact is 90% of owners don't want to be in a room with a dying animal. People leave so they don't see their animals leave. But they don't realize it's in these last moments of life that their animal needs them the most."

As a dog lover, I read the attached post, and immediately teared up. Like so many others, our dog is so totally and fully family that I felt loss in just thinking about the inevitability of "finiteness."

But more basically, I felt empathy for the depth of unconditional love and engagement that a pet brings, and how it must feel in that moment, wondering where its family is.

It's an apt reminder about the Finite nature of Life and the importance of Being Present.

Contact Sport

There is a cadence to getting things done. One construct is the idea executing on sprints, where sprints are small, but meaningful, bites that can be delivered and/or realized in a few weeks or less.

This type of approach can be very effective, as it encourages bold thinking, specifically by mitigating the cost of failure while enabling rapid iteration and course correction.

There is of course a pacing and "force of impact" aspect to getting things done in that whatever pace and pose you choose, you have to LIVE that pace, and MANIFEST that pose.

The point being that it’s not theoretical. It’s literal.

It’s a Contact Sport, where every couple of weeks feels…to the brain and body…more akin to going a couple rounds in a boxing match than negotiating a leisurely sprint.

Purpose meets Pursuit.

Ruminations on Smiling and Laughing Easily

Everything is better when you allow yourself to smile easily and laugh easily.

Good times come, and bad times come, but having a sense of spirit that ALLOWS you to smile and find humor at all times, is liberating.

A smile makes life easier (but, not easy).

The act of reminding oneself to smile and laugh goes a long way to actually doing so.

Mind follows body. Body follows mind.

Why Generative AI is such a "Nuclear" Force

To understand the wondrous, magical power of #GenerativeAI, consider the above #Midjourney image, which I created utilizing multiple generative AI constructs.

The first is #blend, which was a product of combining photos of both a mannequin doll and an actual dog.  

Getting to the right out required multiple re-rolls, which are essentially reboots, and then versions, which are more nominal tweaks, before getting to the capture I liked.  

I then used #uplevel to render a higher quality image, followed by #zoom out to set a broader stage. This was followed by a #pan left on the image to augment the view further, and get to the final state.

From Ideation to Realization in just a Few Clicks

As an example of how generative AI turns ideation into realization, this suggests a couple of thoughts. 

One, for all of the goodness of prompts as a UI/UX construct, it’s not going to obviate the goodness of nice UIs with well designed knobs and levers.  Quite the contrary. 

That noted, I suspect that the “relatability” of prompt-based interfaces will at some point become near universal (i.e., EVERYONE will be able to navigate prompt based UIs to at least some baseline of workability). 

This reminds me of an observation of a friend who noted that the magic of Twitter was that it opened blogging (er, microblogging) to ANYONE who could muster 140 characters or less. Prior to this, blogging was a commitment of 500+ words, a step order function higher bar for most people.

The point there is that the emergence of the tweet did not result in serious writing going away. There is more written content than ever. 

But, the accessibility of the tweet turned 1000X more people into writers & publishers, creating a new kind of collective and connective fabric (that that douche Musk has systematically burned down, which is a topic for another day). 

Simply put, the prompt is to the tweet what AI based automation is to blogging/online publishing. 

It will be universal breadcrumb that indoctrinates the masses into AI.

Don't get me wrong. There will be lots of vertical focused endeavors that take hold, but the focus here is on the idea that core to AI realizing its potential is the emergence of shared, universal set of learnings, tools and connected services. 

This hearkens a bit back to what Kevin Kelly refers to as The Technium, and what I think of in a more meta sense as the Library of the Commons.

The Biggest Technology Wave...EVER!?

I just know that relative to every wave I have experienced -- The Rise of the PC, The Internet and The iPhone --  AI & Generative AI is going to be the biggest and most disruptive.

There are four reasons for this:

1. Installed Base: When the PC was born, the joke was that three was maybe a market for eight PCs. Today, there are over 5.5 BILLION mobile devices online.
2. Superpower: When the Web started, there was no iPhone, and most people had dial-up modem connections that were slogs. Today, we have supercomputers in our pocket with mobile broadband connections that are fast enough to watch live TV...and Apple Vision looms here. 
3. Adaptability: As so much of the underlying data that has trained this generation of Generative AI services was culled from public websites and popular web services, much of the learnings are adaptable to a broad set of use cases, which is useful in securing broader adoption.
4. Relatability: Generative AI is as much a showcase of the power of natural language processing as it is of generative AI itself. The key point here is that it seems likely that at some point in the not too distant future, most people will at least adopt some baseline of prompt based systems and services, and for many more, it will be a gateway drug to deeper adoption of AI in general.

A final thought. This space is evolving incredibly fast, and so there may be some fear of missing the train.

My guidance there is this is the next 20 years beginning to unfold. Start thinking about how you want to ride it. Take small, manageable bites, take measure on what works and doesn't, and course correct...frequently.

It can be hard to imagine what a technology wave will look like when it becomes fully fleshed out and ubiquitous, but know this.

The first PCs were all text and no graphics.

It was once considered improper to use the Internet for commercial purposes.

This first "mobile" phones fit in your car trunk, not your pocket, and couldn't handle data. 

In baseball terms, this is the second batter, top of first inning of a nine inning game.

Grab a bat, and you just might hit for the cycle.

3 thoughts on Apple Vision Pro and the Future of Spatial Computing

Let me preface my comments about Apple’s new spatial computing platform, Apple Vision Pro, by saying that despite a 30 year career in tech, a period that includes the PC revolution, the rise of the Internet, iPhone, and Social Media, I am NOT an early adopter for early adoption sake.

I am all about utility and functional coherence. Plus, as a platform guy, I know just how hard hardware, software and service platforms are to create and how long they take to develop & cultivate.

I am also an admitted Apple acolyte, having done multiple startups focused on the Apple Ecosystem (dating back to 1994), having sold one startup (Me.com) to Apple, and having written about Apple for over 20 years.

As a result, I went into watching the Apple Keynote, with a heavy dose of skepticism about the compelling-ness of Augmented Reality as a standalone platform. BUT also, a deep belief that Apple is uniquely positioned to execute such a platform, if anyone can.

Let me begin with the end by suggesting that you spend a few minutes watching the film that Apple created to demonstrate the capabilities of Apple Vision Pro, and its vision for spatial computing (click HERE). 

I was floored by the demonstration, and laughed approvingly and with the shock of favorable surprise.

It quite literally is the magical Yin to Facebook’s Yang with Zuck’s ridiculous Metaverse vision. Sometimes, a (moving) picture is worth a thousand words.

Three thoughts stood out from the presentation:

1. A Wearable Spatial Computer: It was clear from the get-go that Apple does not view Vision Pro as an accessory device, like AirPods or Apple Watch, but rather as a standalone computing experience and a new medium in its own right. One of the first examples was of a virtual Mac style desktop with application icons floating in the space literally in front of your eyes, with apps clickable, launchable and manageable using eye tracking, voice and finger movements only. This befits a system built with 12 cameras, five sensors, six microphones and two different sets of Apple silicon to stitch it all together, all of which is governed by a new OS called visionOS. You can launch infinite screens, and since these screens are boundless, responsive and feature immersive spatial audio, you can literally turn your living room into a backdrop of the Grand Canyon. The use cases for Entertainment, Gaming and Communications are pretty fascinating. Also, Apple did a very smart thing here in designing Vision Pro so that it can run any iOS apps within the device, including Photos, Music and Apple TV, mitigating some of the chicken and egg risk at launch. Disney CEO Robert Iger was the one outside presenter at the event, showcasing clear use cases built around sports, branded characters, movies and gaming, and communicating Disney's embrace of the new platform (though notably, his actual words on what would be ready at launch was Disney+).
2. When as Much as If: When it launches early next year, the Apple Vision Pro will “start at” $3,499, which is outside of the realm of most consumers, suggesting that the device is named Pro for a reason. Apple knows that many of the initial buyers will be traditional early adopters, specific business verticals and developers, who will seed development of the platform. To be clear, Apple’s history suggests that within 2-3 generations, Vision Pro will probably be $1,599, or only $99/month, payable over 18 months with Apple Pay. Watching the timing of how this plays out, when and how outside developers embrace, and what the first "native apps" look like, will be Rube Goldberg-ian in its execution, to be sure.
3. Only Apple Can Do This: Having watched Apple rise from the Mac company, to the iPod company, and then the iPhone company, a core secret to their success is taking the painful learnings of getting whupped by Microsoft during the PC era; namely horizontal, undifferentiated hardware platforms equals death. That lesson learned, Apple is all about finding performance dependent verticals where the integration across hardware, software, service, developer tools & marketplaces is a core differentiator. I wrote about this fact way back in 2008, when it was clear how Apple’s ability to create platforms that are derived from a common core, but specific to the device’s reason for being, was much more powerful than one size fits all.  Hence, MacOS gave rise to iOS, WatchOS and now visionOS. But, it also Apple’s acumen in composite materials, sensors, silicon, display, camera and sound design that make it unique. Generally speaking, most new platforms begin life as vertical systems for performance reasons, before evolving into horizontal, standardized platforms over time. This is the moat that anyone hoping to compete with Apple has to navigate. Few operate with so many core differentiators, including the Apple Ecosystem, Apple Stores, and a cash generation machine that affords Apple the time horizon to reach, aspire, and god willing, get it done.

But the $64,000 question is whether Vision Pro is the next iPhone or Tim Cook’s Lisa, a powerful, innovative but ultimately too complex and too expensive device for the wider market to embrace.

Put another way, what has to go right in what time frame for the platform to succeed?

The answer is unknowable in advance, because unlike the PC, unlike the Internet, and even unlike the iPhone, Vision Pro doesn’t rise from a primordial ooze of clear users and well-grooved use cases.

It’s its own thing.

It’s also the rare case where Apple is running AHEAD of the pack, as opposed to watching, learning and then, and only then, leapfrogging.

Steve Jobs famously encouraged Tim Cook as CEO to NOT ask "What would Steve do" as Tim’s leadership style.

Apple Vision Pro is the most emblematic manifestation of that ideal.

For that reason alone, for good or bad, it will be a scarlet letter of sorts on Tim Cook's legacy at Apple.

I applaud his courage to pursue, and will be rooting for Apple to succeed, which is a funny thing to say about a company with a market cap of $2.8 trillion.

Be Dynamic.

I was talking with someone the other day who communicated a sense of pride in the fact that they are “dynamic.”

The phraseology resonated, bringing into focus (for me) their natural positivity, their good spirit, force of will and openness to new ideas & experiences.

It brought me back to a Quora post I read not long ago about this young person who was always engaging people that he came into contact with at school and on the street - greeting, smiling, taking interest, extending himself, etc.

When asked by his parents how this outreaching aspect came so naturally, he simply stated, “I’m building an army.”

Being Dynamic

We each have within us the power to be dynamic.

Regardless of the size of the armies we are building, being dynamic is driven by having and codifying an apt purpose guided by specific goals and quantifiable tactics. 

Choosing what NOT to do as much as what to do.

Gaining clarity on what we're choosing to optimize around by doing more or less of something, or by doing it differently.

By putting forth a concentrated effort, with a repeatable process and the basic grit to put in the reps.

Lest we become too self-serious, being dynamic is about maintaining a sense of awe, of wonderment and gratitude, engaging one's pursuits with optimism, earnestness and a sense of the whole enchilada.

This sparks a curiosity, not just to ask lots of questions, but in a doggedness to work our way to our ultimate truths.

This becomes our fire, driving us to communicate, to engage, to always be refining and editing, and to convert believers.

To build an army, but mostly to "become" by pursuing a life's work.

Note: Image is a generative AI render from Midjourney using the prompt - “dynamic, positive in attitude and full of energy and new ideas.”

Seven reasons I am betting on a Soft Landing for the U.S. Economy

Famed investor Michael Burry ('The Big Short') predicts a U.S. recession "by any definition.” That sounds ominous but let me attempt to articulate why I believe a soft landing or mild recession is more likely.

First and foremost, two disclaimers. One, I am not smart enough to predict the gyrations of the stock market, which is digesting the unwinding of one of the greatest asset bubbles ever, coupled with a still-lingering pandemic, an emerging climate crisis, and international & domestic political instability.

 

That’s a lot of risk to mitigate.

Two, we ARE moving into a period of tighter access to capital, so industries dependent on cheap, easy money to backstop long-term negative cashflow business fundamentals, or robust public markets for ready liquidity (e.g., Venture Capital) may very well face serious challenges.

In a healthy way, the present is very much a time for re-set of valuation metrics, and re-classification of assets, as in:

1. Is that asset really a liability?
2. Is the valuation premium too rich given risk factors (think: Crypto, Tesla)?

In other words, if you are in an undifferentiated money-losing business (or industry), the present time is reminiscent of the narrative that:

“When your friend loses her job, it's a recession, but when YOU lose your job, it's a depression.”

The point being that not all segments are created equal, and even in good economic times, plenty of businesses fail.

Then, why am I relatively bullish?

One, so much of inflation, and by extension, the cost of EVERYTHING, is driven by energy costs, which anyone who has gone to the pump recently can see has fallen by 35% since its peak in June.

Equally important, the economy seems to have weathered the initial shocks created by Russia’s invasion of Ukraine.

Two, consumers remain relatively flush, having built up reserves during the pandemic, driven by stimulus, a strong job market, and deferred spend on luxury items and travel.

Three, the job market remains very strong, and unemployment remains low.

One impact of that is the durability of brick and mortar retail.

My company, Datex Property Solutions, tracks the rent collections and sales data of thousands of shopping centers and tens of thousands of retailers nationwide, and while individual retail categories and specific operators are always at risk of getting “Amazon’d,” the actual data remains strong.

We have seen no material weakening of retail sales and/or rent collections, based on highly validated data that goes back from pre-pandemic to the present.

Four, while companies are preemptively laying off workers, the fact is that corporate profits have been off the charts strong, so self-interest suggests they won't over-cut, and in the case of the tech sector, much of the cutting is driven by over-staffing based on the last cycle’s ethos of growth at all costs.

Five, let's not forget the impact of tech in non-tech industries, sometimes referred to as "software is eating the world."

As the crash and burn of Southwest Airlines over the holiday underscores, much of corporate America and most SMB's are relatively early in their adoption of tech-powered innovation, be it better data to make smarter decisions, or automation to drive better process and improved productivity.

Plus, we are just now seeing the realization of the promise of artificial intelligence, which is ready to transform the way companies operate in the same way personal computing, the internet and mobile transformed our economy.

The difference between when those technology waves kicked in, and now, is that much of the technology adoption lifecycle is at the “applied” phase.

This means that technology is reaching a point of maturity that given a dollar of investment, the return on effort, spend and human capital is much clearer and with a much shorter ramp.

The point here is that unlike the stagflation period of the 1970s, which I grew up in, when American innovation felt dead, our ability to innovate and APPLY innovation to better operations is very strong.

Six, the pandemic and global politics have awakened the notion that the best way to mitigate bottlenecks in the supply chain is to (re)build manufacturing domestically.

This feels like 5-10 year trend that is only accelerating.

Seven, with a tightening of the economy comes a healthy revisiting of the question of Work From Home vs. Work From Office, and the bet here is that while the right answer is a hybrid of both, the tilt will shift back towards Work From Office, which will provide needed oxygen to many a beleaguered business district, and the ecosystem that services it.

To be clear, no one holds the crystal ball, and ultimately, scenario planning is about assessing probabilities based on catalysts, constraints and other human factors, but from where I sit, I am more optimistic (than not) about the outlook for the year ahead.

Reasons for Optimism, and The Honest Liar has No Sense of Decency

The 2022 Midterms may ultimately mean a lot, or very little, in terms of the durability of Democracy and a broadening of personal freedoms.

But, it certainly felt like a turning point in the right direction.

Away from cynicism and disregard for our history and institutions.

Towards optimism, affirmation in the importance of good (and getting better) governance, the integral-ness of functioning institutions, rule of law and the belief that Policy can make a difference in people's lives...for the better.

The Good Liar 

Comedian Dave Chappelle had a very astute observation in his recent opening monologue on SNL.

When talking about the appeal of Donald Trump, Chappelle spoke with absolute clarity.

The genius of Trump, Chappelle noted, is that Trump is an "honest liar."

He channels our cynicism by treating lying, cheating, stealing and self-dealing NOT as a sign of moral failure or guilt, but rather, of virtue, a sign of personal force and of being a GANGSTA (not gangster), by reverse engineering the system.

Breaking the rules and being bound by no truths other than, "When you are a star, they let you do it," Trump as the honest liar is the hero to the cynics, who believe that:

1. The system is irrevocably broken
2. Those empowered to govern are irredeemably corrupt
3. Our institutions are fundamentally incapable of making peoples lives better, if they ever did

In such a world, the liar and cheat, the honest liar is King.

(As an aside, what I love about Chappelle is that he has no sacred cows. He is an equal opportunity offender, but not simply a cheap shot artist; he gets to the subtext of situations, the elephant in the room that no one talks about. Comedy is afforded license to make us uncomfortable.)

"Have you no sense of decency, sir, at long last?"

But, the dark charm of the honest liar begs a question.

Where does this all end? Insurrection? Election denial? Stealing confidential documents? Collusion with historical foes, like Putin's Russia?

Or, to put it all in perspective of history, in the early 1950's, Joseph McCarthy, a Republican U.S. Senator from Wisconsin, used his position of power to create a witch hunt around surfacing Communist sympathizers, a witch hunt that literally destroyed hundreds, if not thousands of lives.

The term "McCarthyism", coined in 1950 in reference to McCarthy's practices, came to more broadly mean demagogic, reckless, and unsubstantiated accusations, as well as public attacks on the character or patriotism of political opponents.

McCarthy's actions ran rampant because everyone feared being deemed anti-American in the time of the Cold War.

McCarthy's fall came when after turning his attentions to the United States Army, its chief counsel Joseph Welch, called truth to injustice, "You've done enough. Have you no sense of decency, sir, at long last? Have you left no sense of decency?"

Moral of the story. Decency matters.

Triumph of the Optimists

While there were "blue wave" narratives on the 2022 Mid Terms (wishful thinking at mid-point of administration where Presidency, Senate and House controlled by one party, the Democrats), as the elections approached, the narrative shifted overwhelmingly towards a "red wave."

Had it played out, the red wave would have signaled a wider embrace of the Trump narrative of election denialism.

It would have manifested in the ascension into power of Governors, Secretaries of State and Election Heads by Trump acolytes, and set up the chessboard for a final hollowing of democracy. 

It did not happen, because:

1. The January 6th Committee did a remarkable job showing the knowing, treasonous behavior of Trump, all the while relying almost exclusively on the testimony of Republicans, not Democrats.
2. An ideologically poisoned Supreme Court knowingly threw out settled law, and overturned Roe v. Wade, showing that "dog whistle" rhetoric becomes dark policy in a zero-sum Republican controlled universe.
3. President Biden showed that policy matters, exhibiting a surprisingly stable hand in getting multiple quality of life, economic, social and global scale legislations passed, despite navigating the thinnest of majorities.
4. Enough independent voters ignored the lazy platitudes of a self-interested media (who need the scorched earth of Us vs. Them to drive eyeballs).
5. Enough women, people of color and even the young, stepped to the plate and made their vote count.
6. It became clear that MAGA stands for nothing other than cynicism, nihilism, polarization, lawlessness and hate, a point exacerbated by the politically-inspired attack on Nancy Pelosi's husband.

In the end, triumph of the optimists prevailed.

The Way Forward

The larger takeaways are that the American voter can walk and chew gum at the same time in the sense that he/she can support conservative policies and rule of law, can separate economy from demagoguery and that the American voter wants leaders that actually BELIEVE in America, its history, its institutions and its diversity.

For the Democrats (and a hopeful re-emerging moderate wing of the Republican party), the path forward is:

1. Espouse policy as a stated goal
2. Focus on specific solutions
3. Remember that all politics is local
4. Turn the tide on the judicial branch
5. Make decency and character table stakes
6. Hold Trump accountable so future coups don't look cost-free

Maybe this is our "Have you know shame" moment, where the tide turns to lightness, hope, and CAN vs. CAN'T.

A final thought. The larger truth, be it government, business, investing or social governance is that while we can agree or disagree on the definition of character, make no doubt, character matters.

What we sow is what we reap.