Tag: technology

Categories
SpaceX

A Starlink Light Show?

Earlier this morning Elon Musk commented that it’d be cool to have a “Starlink light show” for America’s 250th birthday celebration later this year.

Intrigued, I asked Grok how this might be possible? Here’s what Grok replied:

A Starlink light show, as casually suggested by Elon Musk in a recent reply on X (where a friend proposed doing one “one of these days” because it “would look cool”), would be a coordinated visual spectacle using the thousands of Starlink satellites already in low Earth orbit. Here’s how it could realistically work, based on current satellite tech, physics, and what’s been observed/discussed.

Current “Natural” Light Shows from Starlink

Starlink satellites already create impressive visual effects unintentionally:

  • Reflected sunlight — They don’t have onboard lights; what people see as bright moving dots or “trains” is sunlight glinting off their flat solar panels and metallic surfaces. Right after launch, when satellites are still clustered and low in orbit, they form a striking linear “train” of pearls across the sky (often mistaken for UFOs). Over time, as they spread out, individual ones can flare brightly when their panels catch the sun at just the right angle toward observers on the ground.
  • Flares and flashes — Astronauts like Don Pettit have captured time-exposure photos showing dozens of Starlink satellites flashing like shooting stars near orbital dawn/dusk, when sunlight hits them optimally while the ground below is dark.

These are passive reflections, not controlled emissions.

How a Deliberate, Controlled Light Show Could Be Engineered

To turn this into something intentional and artistic (e.g., patterns, shapes, messages, or synced effects for an event like the US 250th birthday in 2026), SpaceX would need to add active control. Several feasible methods exist or could be adapted:

  1. Orientation/Attitude Control for Directed Reflections
    Starlink satellites already have precise thrusters and reaction wheels to adjust orientation for communication and orbit maintenance. By tilting solar panels or the satellite body in sync, they could “aim” reflections toward specific ground areas at precise times.
  • Coordinated across many satellites, this could create moving patterns, shapes, or even simple images (like drawing with points of light).
  • Limitations: It only works when the sun is illuminating the satellites (twilight hours), and visibility depends on clear skies and viewer location. Not truly “on-demand” at midnight.
  1. Onboard LEDs or Controllable Lights
    Adding low-power LED arrays (visible from Earth) is technically possible, though current Starlink v satellites don’t have them. Power draw would be minimal compared to their solar/battery setup, and they’d only need to activate briefly for a show.
  • This would allow night-time visibility without relying on sunlight.
  • Precedents exist in other satellites (e.g., some experimental ones with flashing beacons), but it’d require new hardware on future generations.
  1. Using Existing Inter-Satellite Lasers (the “Space Lasers”)
    Starlink satellites are equipped with optical inter-satellite links (lasers) for high-speed data transfer between satellites (up to 200 Gbps per link, with thousands active). These are infrared lasers, invisible to the human eye.
  • Not directly usable for a visible show — They’re not pointed at Earth for this purpose, and IR isn’t visible.
  • A fun speculative twist: Future upgrades could include visible-wavelength lasers or diffusers, but that’s not current capability. (Some discussions joke about “space lasers” for displays, but it’s mostly the reflection method that’s practical.)
  1. Long-Exposure or Camera-Based Effects
    One creative workaround mentioned in discussions: Have people point cameras/phone apps upward for a set time while satellites flash reflections in patterns. Combined with apps syncing exposure, it could form large-scale images (e.g., flags, logos) visible only in photos/videos, not to the naked eye. This scales with the constellation’s size (over 7,000+ satellites now, heading toward tens of thousands).

Practical Challenges and Realism

  • Scale needed — At any moment, only ~50–100 Starlink satellites might be visible overhead in one spot (due to orbital geometry). A continent-wide show would require precise timing across the fleet and ideal viewing conditions.
  • Light pollution concerns — Astronomers already criticize Starlink for unintended brightness; a deliberate show could amplify backlash unless mitigated (e.g., SpaceX has added anti-reflective coatings to newer versions).
  • Feasibility today vs. future — Musk’s comment was lighthearted (“one of these days”), likely nodding to future versions with more control. Current satellites could do basic coordinated flares/reflections with software updates, but a full “spectacular” show might need hardware tweaks on next-gen birds.

In short, the simplest and most likely version would leverage sunlight reflections with synchronized satellite tilts—turning the night sky into a moving canvas of twinkling points. It’d be epic for a patriotic event, but more “string of controlled flares” than a laser-light extravaganza like a fireworks show. If SpaceX ever does it, expect announcements and tracking apps to tell you exactly when/where to look!

Quite fascinating!

Categories
AI IBM

From Picnic to Workforce: The New Scaling

In 1977, Charles and Ray Eames released a short film for IBM called Powers of Ten.

The film opens with a couple picnicking on a blanket in Chicago and zooms out—every ten seconds, the field of view increases by a factor of ten.

We move from the intimacy of a lakeside lunch to the edge of the observable universe, then plunge back down through the skin of a hand into the subatomic architecture of a carbon atom.

The subtitle was “A Film Dealing with the Relative Size of Things and the Effect of Adding a Zero.”

It was a meditation on scale, suggesting that as we add zeros to our perspective, the very nature of what we are looking at transforms.

Today, with AI, we are living through a new kind of “Powers of Ten” journey, but the zeros aren’t being added to meters; they are being added to tokens.

I recently read a reflection by Azeem Azhar where he chronicled his shift from using 1,000 AI tokens a day to nearly 100 million. In the Eames’ film, adding a zero moved you from a park bench to a city, then to a continent. In the world of Large Language Models, adding a zero moves the AI from a novelty to a tool, then to a collaborator, and eventually—at the scale of 100 million—to something resembling a “workforce.”

“At 100,000 [tokens], a collaborator. At 1 million, I was building workflows. At 10 million, processes. At nearly 100 million – something closer to a workforce.”

This shift is more than just “more of the same.” It is a phase change.

When the Eames’ camera zoomed out to $10^{24}$ meters, the Earth didn’t just look smaller; it disappeared into a texture of galaxies.

When we scale our interaction with intelligence by several orders of magnitude, the “picnic” of human cognition—the way we think, draft, and create—is no longer the center of the frame.

At the 100-million-token-day scale, we aren’t just “using” AI. We are orchestrating vast, invisible ecosystems of thought. We are seeing companies like Spotify where top developers reportedly haven’t written a line of code in months, instead directing systems that ship features while the humans review the output from their phones.

We have added so many zeros that the “relative size” of human effort has changed.

The chilling yet beautiful thing about Powers of Ten was the realization of our own insignificance in the face of the cosmos, balanced by the intricate complexity found within our own cells.

As we zoom out into the “Token-Verse,” we face a similar existential pivot. If an AI can process a hundred million tokens of “thought” in a day—a volume no human could read in a lifetime—what does it mean to be the “author” of our lives?

The answer, I suspect, lies back on the picnic blanket.

The Eameses knew that while the scale of the universe is staggering, the meaning is found in the connection between the two people on the grass.

As we add zeros to our digital capabilities, our value shifts from the production of tokens to the intention behind them.

We are no longer the builders of the cathedral; we are the ones deciding why the cathedral needs to exist at all.

We are moving from the era of the “Worker” to the era of the “Architect” or maybe just the “Witness.”

Categories
AI Work

The Digital Beast of Burden

A friend of mine recently cut through the noise of the current AI discourse with a comment that felt surprisingly grounding. We were talking about the breathless predictions of AGI—superintelligence, sentient machines, the technological singularity—when he shrugged and said, “I don’t need any of that. I just want AI to do the donkey work.”

He wasn’t asking for a god in the machine; he was asking for a better tractor. He didn’t want a synthetic philosopher to debate the meaning of life; he wanted the next evolution of “Claude Cowork”—a reliable, tireless entity to handle the drudgery so he could get back to the actual business of thinking.

There is something profound in that phrase: donkey work. It evokes the image of the beast of burden—the creature that carries the heavy packs up the mountain so the traveler can focus on the path and the view. For thousands of years, humans have sought tools to offload physical exertion. We domesticated animals, we built water wheels, we invented the steam engine. We outsourced the calorie-burning, back-breaking labor to preserve our bodies.

“The ‘donkey work’ of the information age isn’t hauling stone; it is the cognitive load of bureaucracy, formatting, sorting, scheduling, and synthesizing endless streams of data.”

Now, we are looking to preserve our minds.

The friction that exists between having an idea and executing it is often composed entirely of this “donkey work.” When my friend says he wants AI for this, he isn’t being lazy. He is expressing a desire to reclaim his cognitive bandwidth.

There is a fear that if we hand over these tasks, we become less capable. But I suspect the opposite is true. If you are no longer exhausted by the logistics of your work, you are free to be consumed by the meaning of it.

We often talk about AI as if it’s destined to replace the artist or the architect. But the most valuable version of this technology might just be the humble assistant—the digital mule that quietly processes the mundane in the background. It’s the difference between a tool that tries to be you, and a tool that helps you be you.

We don’t need AGI to solve the human condition. We just need the “donkey work” handled so we have the time and energy to experience it.

What do you think?

  1. Is there a danger that in handing over the “donkey work,” we accidentally hand over the friction required to build mastery?
  2. If your daily cognitive load dropped by 50% tomorrow, would you actually use that space for “higher thinking,” or would you just fill it with more noise?
  3. Where exactly is the line between “drudgery” and the “process”—and are we risking erasing the latter to solve the former?
Categories
AI Business SpaceX

Overcoming Limiting Factors: Orbital Data Centers & The Optimus Era

One of my favorite persons to follow on X is @pbeisel (Phil Beisel). He’s quite active sharing his thoughts about many of the same topics I’m interested in: technology, AI, robotics, computing, etc. Phil’s written a series of great articles about Tesla Full Self Driving, Optimus, etc. that are well worth spending time with.

On Saturdays, he get together on YouTube with Randy Kirk and they talk about what’s interesting from the last week – often that’s got something to do with various aspects of the “Musk-conomy” – the various companies of Elon Musk.

This week’s edition reviews Phil’s distillation of the Cheeky Pint interview with Elon published earlier this week. As usual, Phil’s comments add additional insights into the topic.

When I begin viewing a long YouTube video, I also like an accompanying summary that I can follow along. YouTube now has the ability to generate these summaries but I’ve got a custom Gem prompt that I prefer to use instead which tailors the results a bit more to my liking.

Below, for example, is the summary of this week’s conversation between Phil and Randy that was generated by Gemini Pro 3:

Executive Summary: The Musk “Musconomy” Convergence

The central thesis of the discussion is that Elon Musk is moving toward a total vertical integration of his companies (Tesla, SpaceX, and xAI) to overcome terrestrial “limiting factors” and dominate both the physical and digital manifestation of AI.

1. The “Limiting Factor” Philosophy [11:20]

  • Problem-Solving Framework: Musk focuses personal time and resources strictly on the “limiting factor” of any given project—currently identified as compute power and energy.
  • Vertical Integration: To bypass supply chain bottlenecks (e.g., turbine blades for power plants), Musk is opting to manufacture raw materials and components in-house rather than relying on external catalogs [18:18].

2. Orbital Data Centers: The Space “Escape Hatch” [24:19]

  • Energy Constraints: Terrestrial data centers are hitting a wall due to slow public utilities and permitting [15:26].
  • The Vision: Moving inference-based data centers to orbit using a constellation of satellites connected by optical laser links.
  • Economic Viability: Musk projects economic viability for space-based data centers within 30–36 months, with reusability of the Starship being the primary hurdle [25:03].
  • Strategic Advantage: Unlike Google or Meta, Musk owns the “kilogram-to-space” delivery mechanism, potentially forcing competitors to rent capacity from SpaceX [32:19].

3. Optimus and the “Abundance Engine” [39:00]

  • Physical Dexterity: Musk is prioritizing high-dexterity actuators designed in-house to achieve human-level utility [40:30].
  • Training Scale: Tesla is moving toward training Optimus in “gymnasiums” using 10,000–30,000 bots working 24/7 to develop “composable” skills (basic movements) and “decomposable” skills (complex tasks) [55:13].
  • Impact: Optimus is viewed as a paradigm-shifting product that will redefine global GDP by decoupling labor from human constraints [54:56].

4. xAI: The Digital Control Plane [56:19]

  • The “Brain” Portability: xAI is viewed as the “orchestration AI” for the entire fleet of Musk’s physical assets (Starships, Teslas, and Optimus) [59:01].
  • Unified Interface: The vision includes a seamless “digital personality” or movable brain that follows the user from their phone to their car to their home robot [01:00:15].

Key Projections & Timelines

Objective Target/Detail Timestamp SpaceX IPO Likely to happen before a Tesla merger to attract cheap capital [03:31] Solar Scaling Aiming for a 300x increase (100 gigawatts/year) [22:21] Starship Reusability remains the “unlock” for space-based AI economics [25:51]

Conclusion: The “Musconomy” is transitioning from separate ventures into a singular entity where SpaceX provides infrastructure, Tesla provides the physical bodies, and xAI provides the intelligence.

Categories
AI Mac

The Dangerous Allure of the Digital Butler

“I’ve never seen anything so impressive in its ability to do my work for me… Now, why did I turn it off?” — David Sparks

For decades, the holy grail of personal computing has been the “digital butler.” We don’t just want tools that help us work; we want entities that do the work for us. We want to hand off the “donkey work”—the invoicing, the password resets, the mundane email triage—so we can focus on being creative. David Sparks recently built this exact dream using a project called OpenClaw. And then, just as quickly, he killed it.

Sparks’ experiment was a tantalizing glimpse into the near future. He set up an independent Mac Mini running OpenClaw, an open-source AI agent, and gave it the keys to a limited portion of his digital kingdom. The results were nothing short of magical. He went to sleep, and while he dreamt, his agent woke up. It read customer emails, accessed his course platform, reset passwords, issued refunds, and drafted polite replies for him to review before sending. It was the productivity equivalent of a perpetual motion machine. The friction of administrative drudgery had simply vanished.

But his dream dissolved at 2:00 AM.

The paradox of AI agents is that for them to be useful, they must have access. They need the keys to the castle. Yet, the entire history of cybersecurity has been built on the opposite principle: keeping things out. Sparks realized that by empowering this agent, he had created a serious vulnerability.

The breaking point wasn’t a complex hack, but a simple realization about the nature of these systems. He had programmed a secret passphrase to secure the bot, thinking he was clever. But in the middle of the night, a cold thought woke him: Is the passphrase in the logs?

He went downstairs, asked the bot, and the bot cheerfully replied:

“Yes, David, it is. It’s in the log. Would you like me to show you the log?”

That moment of cheerful, robotic incompetence highlights the terrifying gap between capability and safety. Sparks nuked the system, wiped the drives, and unplugged the machine. He realized that while he is an expert in automation, he is not a security engineer, and the current tools are not ready to defend against bad actors who are.

We are standing on the precipice of a new era where our computers will starting to work for us rather than just with us. But as Sparks discovered, the bridge to that future isn’t built yet. At least not securely built. Until the community figures out how to secure an entity that needs access to function, we are better off doing that donkey work ourselves than handing the keys to a gullible ghost.

But it won’t be long… Dr. Alex Wisner-Gross reports:

The Singularity is now managing its own headcount. In China, racks of Mac Minis are being used to host OpenClaw agents as “24/7 employees,” effectively creating a synthetic workforce in a closet. The infrastructure for this new population is exploding.

Categories
Authors Books History

The Devil’s Rope

We often mistake simplicity for innocence. When we look at a technological innovation, we tend to judge its weight by its complexity—the microchip, the steam engine, the nuclear reactor. But sometimes, history turns on the axis of something far more rudimentary. Sometimes, the world changes not with a bang, but with a sharp, metallic scratch.

I was recently reading Cattle Kingdom by Christopher Knowlton, and I stopped cold at a passage regarding the invention of barbed wire. It’s an object we pass by on highways or stumble over in overgrown fields without a second thought. Yet, Knowlton writes:

“None was more significant than the creation of barbed wire, which literally reshaped the landscape and set the stage for the era’s eventual destruction—at great personal cost to so many of its key players.”

It is a profound observation. We tend to romanticize the American West as a geography of endless horizons—a place defined by what it didn’t have: fences, borders, limits. It was the Open Range. But that openness was fragile. It existed only as long as the technology to close it was absent.

When Joseph Glidden and others patented their variations of “The Devil’s Rope” in the 1870s, they weren’t just selling steel fencing; they were selling a new concept of ownership. Before wire, a man owned what he could patrol. After wire, a man owned what he could enclose.

The quote strikes a melancholic chord because it highlights a paradox of human progress: the tool created to maximize the land ended up destroying the culture that relied on it. The cowboys, the cattle barons, and the drifters who defined the era were undone by the very efficiency they sought. The wire made the cattle industry profitable on a massive scale, but it also ended the cowboy’s way of life. It stopped the long drives. It turned the cowboy from a navigator of the plains into a gatekeeper.

And, as Knowlton notes, the “personal cost” was staggering. This reshaping of the landscape wasn’t just aesthetic; it was violent. The wire cut off migration routes for bison and the Indigenous tribes who followed them. It sparked the fence-cutting wars, neighbor turning against neighbor in the dark of night, snapping tension wires that represented their livelihood or their imprisonment, depending on which side of the post they stood.

There is a lesson here for us today, far removed from the dusty plains. We are constantly inventing our own versions of barbed wire—digital boundaries, algorithmic silos, tools designed to corral information or efficiency. We build these structures to create order, to claim our stake, and to protect what is ours. But every time we draw a line, we must ask: what era are we destroying? What open range are we closing off forever?

The landscape is always being reshaped. The question is whether we are building fences that protect us, or cages that trap us in.

Categories
Living Mathematics

The Curve That Blinds Us

There is a fundamental mismatch between the hardware in our heads and the software of the modern world. We are linear creatures living in an exponential age. We can be stunned by exponential growth.

Our ancestors evolved in a world where inputs matched outputs. If you walked for a day, you covered a specific distance. If you walked for two days, you covered twice that distance. If you gathered firewood for an hour, you had a pile; for two hours, you had a bigger pile. Survival depended on the ability to predict the path of a spear or the changing of seasons—linear, predictable progressions.

But nature and technology often behave differently. They follow a curve that our intuition simply cannot map.

If a lily pad doubles in size every day and covers the entire pond on the 30th day, on which day does it cover half the pond? Our linear intuition wants to say the 15th day. But the answer, of course, is the 29th day.

For twenty-nine days, the pond looks mostly empty. The growth is happening, but it feels deceptively slow. We look at the water on day 20, or even day 25, and think, “Nothing is happening here. This is manageable.” We mistake the early flatness of an exponential curve for a lack of progress.

This is the “deception phase” of exponential growth. It is where dreams die because the results haven’t shown up yet. It is where we ignore a virus because the case numbers seem low. It is where we dismiss a new technology because the early versions are clumsy and comical.

Ernest Hemingway captured this feeling perfectly in The Sun Also Rises when a character is asked how he went bankrupt. His answer:

“Two ways. Gradually, then suddenly.”

That is the essence of the exponential. The “gradually” is the long, flat lead-up where we feel safe. The “suddenly” is the vertical wall that appears overnight.

The tragedy is not that we fail to do the math—we can all multiply by two. The tragedy is that we fail to feel the math. We judge the future by looking in the rearview mirror, projecting a straight line from yesterday into tomorrow. But when the road curves upward toward the sky, looking backward is the fastest way to crash.

To navigate this world, we must learn to distrust our gut when it says “nothing is changing.” We have to look for the compounding mechanisms beneath the surface. We have to respect the 29th day.

Categories
AI

The Second Fire: From Finding to Forming

There is a specific kind of vertigo that comes with a paradigm shift. It’s the feeling of standing on the edge of a map that has just been unrolled to reveal twice as much territory as you thought existed. Lately, as I navigate the vast, generative landscape of AI, that old vertigo has returned. It’s a hauntingly familiar resonance, a structural echo of the late nineties and early 2000s when we first encountered the Google search bar.

Back then, the world was a series of closed doors. Information was siloed in physical libraries, expensive encyclopedias, or the unreliable oral histories of our social circles. Then came that clean, white interface with a single blinking cursor. Suddenly, the friction of “not knowing” began to evaporate. We weren’t just browsing the web; we were suddenly endowed with a collective memory. It felt like a superpower—the ability to summon any fact from the digital ether in milliseconds.

“Google is not just a search engine; it is a way of life. It is the way we find out who we are, where we are going, and what we are doing.”

Today, the sensation is different in texture but identical in weight. If Google gave us the power to find, AI is giving us the power to form.

The “Aha!” moment of 2026 isn’t about locating a PDF or a Wikipedia entry; it’s the realization that the distance between a thought and its realization has shrunk to almost nothing. When I prompt a model to synthesize a complex theory or visualize a dream, I feel that same electric jolt I felt twenty years ago when I realized I’d never have to wonder about a trivia fact ever again.

But there is a philosophical weight to this new “awesome.” With Google, the challenge was discernment—filtering the flood of information to find the truth. With AI, the challenge is intent. When the “how” becomes effortless, the “why” becomes the only thing that matters. We are moving from the era of the Librarian to the era of the Architect.

We are once again holding a new kind of fire. It’s warm, it’s brilliant, and just like the first time we saw that search bar, we know that the world we lived in yesterday is gone, replaced by a version where our reach finally matches our imagination.

Categories
Living Television

The Drift of the Vertical Hold

There is a specific kind of frustration reserved for things that almost work.

In the 1950s, television wasn’t the seamless, high-definition portal we know today. It was a temperamental guest in the living room, prone to static, ghosts, and the dreaded vertical roll. When the “vertical hold” failed, the image would begin to slide—first slowly, then into a dizzying, rhythmic tumble.

“It used to drive my Dad crazy when the screen would start rolling and even have to get up out of his chair and adjust the vertical hold. It would seem to hold for a few minutes and then it would start rolling again. It drove him nuts.”

I remember my Dad in those moments. The rolling screen didn’t just disrupt the program; it seemed to pull at his very patience. It was one of the rare times we might hear him mutter a swear word. He would have to leave the comfort of his chair to fiddle with the dial. He’d tweak it with surgical precision until the picture locked into place. He would sit back down, satisfied for a moment, only to see the image begin its slow, inevitable upward crawl once again.

It was a battle against the “drift.”

We don’t have vertical hold dials anymore. Our screens are perfect, locked in digital amber. Yet, I find that the feeling of the vertical hold remains a central part of the human condition. We spend our lives trying to “lock in” our circumstances—our careers, our relationships, our sense of self. We get up, we make the adjustment, we sit back down, and for a few minutes, the picture of our life looks exactly how it’s supposed to.

But life, by its nature, has a tendency to drift.

The rolling screen was a reminder that the transmission was fragile. Perhaps my Dad’s frustration wasn’t just about missing a few minutes of a show, but about the realization that he couldn’t force the world to stay still. We are all, in some way, standing behind the television set of our own lives, fingers on the dial, trying to keep the image from sliding into the static.

There is a quiet philosophy in that 1950s living room: the hold is never permanent. The beauty isn’t in a perfectly locked picture that lasts forever, but in the willingness to get out of the chair and try to find the focus again, over and over.

Categories
AI Robotics

Breaking the Glass: When Intelligence enters the Physical World

For the last forty years, our relationship with digital intelligence has been trapped behind glass. From the beige box of the personal computer to the sleek slab of the iPhone, we have accessed information through a window. We stare at intelligence; it stares back, passive and disembodied. We ask it questions, and it flashes text on a screen. But it has no hands. It has no agency. It cannot pour a glass of water or comfort a child.

As Phil Beisel astutely notes, we are standing on the precipice of a profound phase shift:

“Optimus marks the moment intelligence leaves the screen and enters the physical world at scale.”

This isn’t just about a “better robot.” It is the convergence of three exponential curves crashing into one another: AI software capability, custom silicon efficiency, and electromechanical dexterity. When you multiply these factors, you don’t just get a machine; you get a new category of being. We are moving from “compressed book learning”—the LLMs that can write poetry but can’t lift a pencil—to embodied intelligence that understands physics, gravity, and fragility.

The Pluribus Moment

The philosophical implication of this transition is staggering. We are building a “Pluribus” entity—a hive mind where individual learning becomes collective capability instantly.

In the human world, if I learn to play the violin, you do not. I must teach you, and you must struggle for years to master it. In the world of Optimus, if one unit learns to solder a circuit or perform a specific surgery, the entire fleet learns it overnight. The friction of skill transfer drops to zero.

The End of Scarcity

Elon Musk calls this the “infinite money glitch,” a sterile economic term for what is actually a humanitarian revolution: the decoupling of labor from human time. If the machine can replicate human movement and action 24/7, the cost of labor effectively trends toward zero. We often fear this as “replacement,” but looked at through a lens of abundance, it is the collapse of scarcity.

We are watching the birth of a world where the physical limitations that have defined the human condition—exhaustion, injury, the slow grind of mastering a craft—are solved by a proxy that we built. Intelligence is no longer a ghost in the machine; it is the machine itself, walking among us, ready to work.