From the Road

Concern for AI – part 1

“AI is intrusive, nefarious, deceitful, indefensible, intentionally difficult to unprogram and uncaring of one;s personal privacy. I want no part of it.” -G.

In response to this statement about AI posted by my neighbor on our community list, I spent several days diving back into the foundation of my Masters degree in Applied Mathematics, Evolutionary Computation Applied to Radio Astronomy. My thesis included development of Karoo GP, a Genetic Program that I trained to isolated radio noise caused by human made machines from the desired astronomical sources generated by the MeerKAT array, South Africa. Later, the same code was applied at LIGO to isolate false triggers, also generated by the noise of the thousands of parts of the interferometer.

I have been following the rapid uptick in application of Generative AI in the past two years, and often speak about it with my colleagues in software development. This is an incredibly complex topic, with an incredible array of potential, positive outcomes. At the same time, there are many serious, negative implications across all layers of society, world-wide.

For my neighbor and our community I provided a foundation for a conversation, as most people have little to no understanding of how machine learning applications give foundation to neural networks, deep learning, and now generative AI, nor why we even “need” machine learning in the first place, and what function it serves in a modern, data-driven world.

While I have not been working at the code level of machine learning for some time, and I do not claim to be an expert in artificial intelligence, I maintain a working understanding of the underlying systems, which I share with you here.

IN THE BEGINNING
Humans have since the time of the Egyptian, Greek, and Roman empires recorded and analyzed data to improve farming, manage the finances of complex social systems, and to study the star lit heavens. Since the industrial revolution, advances in medicine, manufacturing, and the study of human and natural systems have made more important the need to reveal patterns in the data we collect.

Early computers were mechanical devices (1800s) followed by electronic computers (mid 1900s) capable of calculations far faster than the human mind. But why is a computer necessary, let alone artificial intelligence?

Let’s consider a small data analysis problem, the time of day incremented in hours, and the temperature outside measured in degrees, such that we desire to plot this as an [x,y] graph, with time on the x axis and temperature on the y axis.

(sunrise to mid afternoon)
time = 7 am; temp = 48F
time = 8 am; temp = 54F
time = 9 am; temp = 60F
…

(mid afternoon to sunset)
time = 6 pm; temp = 56F
time = 7 pm; temp = 53F
time = 8 pm; temp = 48F

… and into the night, cooling until sunrise and starting over again.

Time over Temperature by Kai Staats

Image by Kai Staats

The plot presents a wave-like function. Day in and day out, over and over again as long as you kept placing dots on the graph, left to right, up and down. And we don’t need a computer to do this, just a pen, graph paper, and maybe a ruler to connect the dots.

Now, let’s add a third variable–the angle of the sun from zenith (overhead) such that we can track the time/temp correlation not just day to day, but month to month for one year. If we live north or south of the equator, we’d see an overall warming trend in the summer and cooling in the winter. This too we could do with a bit more graph paper and some patience for many more data points.

But if we want to build a formula to predict the temperature at any time of day, any week of the year, it gets more complicated. Perhaps something like:

temp = mean_temp + fd[cos(date)] + ft[cos(time)]

where we have converted both time and date to circular (cosine) functions so that we can employ the rise and fall of the sun. The function “fd” and “ft” are coefficients that convert time to temperature. This is harder than our original plot, but yes, it’s still something we can do by hand if we have the time and gumption.

This application of mathematics to the natural world is at the very core of science, since the earliest observations and predictions. The goal is to understand the underlying function of everything from plant physiology to human metabolism, from animal migration to stellar evolution in a galaxy far, far away.

A great example of this kind of mapping of the natural world is the work done by Dr. Fisher in the 1930s whereby he applied measurements of the sepal length and sepal width, petal length and petal width of 150 flowers across four species of iris, as acquired by Dr E. Anderson. This is referred to as the iris flower data set. Fisher then hand-developed a formulae into which he (or anyone) could apply the measurements of one of the four species studied, and without seeing the plant, determine the species through formulaic classification.

Iris plot generated by Karoo GP, Kai Staats

Image by Kai Staats

The iris dataset has become a defacto standard that all machine learning programs are expected to solve, including my own. For example, with the following formula derived by Karoo GP, we can accurately assess the type of iris between any two species with 100% accuracy:

sl = -sw + pl2

It gets a bit more complicated when solving for one of three species, but the same concept applies. There are countless millions of examples of statistics (mathematics applied to data analysis) in our modern world–measuring the physical, chemical, biological, or psychological parameters of a given function, from the behavior of online shoppers in holiday seasons to Netflix views, from cancer cell growth to weather prediction–statistics seeking correlation, and often causation.

THE JOY OF DISCOVERY

Karoo GP sketches by Kai Staats

Image by Kai Staats

Discovery of patterns, in any field, is not some sterile activity conducted by socially inept geeks in white lab coats (well, maybe sometimes), but a rigorous process that follows a centuries old practice of a) generating a hypothesis, b) developing an experiment, c) collecting and analyzing data, d) comparing to the hypothesis, and e) sharing both the results and methodology to the world, then refining the experiment and doing it again (more often than not) to improve the model and more importantly, the understanding of the natural process.

This can lead to an increase in healthy habits, reduction in car accidents, and discoveries of breathtaking beauty. For me, for the many times in my work I have been part of pattern discovery, I find myself with an accelerated heart rate and deeply satisfying sense of peace. Something as simple as seeing the growth rate of a pea plant correlated to the amount of carbon dioxide provided (as we do at my worksite with each experiment in bioregeneration) is incredible. It’s repeatable. It’s demonstrable. And it’s a means to seeing inside a small piece of the cosmos and unraveling its mystery, not to dissect or control, but to understand and marvel at its inherent beauty.

I share this because beyond the profit driving many of the companies hosting chat bots and AI driven tools, there are a body of programmers that for the past two decades have enjoyed the discovery that comes through the iterative improvements to their underlying code. I understand their joy and motivation, even if I am increasingly concerned with the way in which their code is being used.

I will never forget the moment when my machine learning code Karoo GP evolved and re-discovered Kepler’s law of planetary motion based on the same numbers recorded by Newton more than 300 years ago. I ran through the halls of the astrophysics institute where I was based, shouting “It worked! It worked! It really worked!” I can only imagine what it was like for Newton, based on his own observations, to discover patterns that defined thermodynamics, the age of the Earth, and gravity all in one lifetime.

IT’S ALL STATISTICS
Back to our comparatively simple effort to predict the temperature each day across the seasons, we will find ourselves with a pattern based on a general formula (above), but not close enough to truly predict with any accuracy, especially not in this new world of rapidly shifting climate functions. It takes far, far more sophisticated models to predict with any accuracy at all.

So we add “degrees of freedom”, additional variables to present more facets of the weather functions. We might take into account the annual increase in greenhouse gases such as water vapor, carbon dioxide, and methane; dust from fires and volcanoes, a reduction in reflectivity by shrinking polar caps and snow mass on glaciers; desertification of once fertile regions, even the 11 years solar storm cycle, to name a few (and there are thousands more).

But now we have far more variables than just time of day and angle of the sun–too many to plot on a piece of paper. And the relationship between these variables cannot be visualized in the human mind nor found by hand. So we need help.

At the foundation of machine learning are statistics and regression analysis.

Statistics we all understand to some degree, as every day we process statements such as “flying is __ times safer than driving”, “smoking a pack of cigarettes each day increases your chance of lung cancer by __ percent”, and “Four out of five dentists recommend brushing your teeth.” (not sure what’s going on with that 5th guy ?!$).

Statistics gives us skills in critical thinking, making important decisions, and managing our finances. It’s a powerful set of tools that should be a required class in high school. I did not learn how to apply statistics beyond an average high school vocabulary until working on my masters degree at age 44. I learned to apply the basics (mean, median, and standard deviation) to build simple relationships between data points prior to training a machine learning algorithm. These “features” offer first order correlations that boost the machine learning algorithm’s ability to find more meaningful relationships between variables in the dataset.

Regression analysis is the development of a mathematical function (e.g. x = 2y + z) to represent the relationship between two or more raw data points or features, as given in my simple temperature prediction model (above), the work of Dr. Fisher with iris flowers, to millions of everyday examples:

    Predicting the Popularity of Social Media Posts
    Predicting House Prices
    Predicting Exam Scores Based on Study Time
    Forecasting Sales for a Business
    Predicting Sports Performance

(More at Geeks for Geeks.)

In my work at LIGO to isolate black hole mergers in the noise of the complex machine, we regularly engaged in processing 4,000 variables (4,000 columns in a spreadsheet) with 10,000 data samples (rows). Yet, this is a “small” dataset in just about any modern data environment.

LACK OF TRANSPARENCY
Now, the start of my answer to G’s question–there are important distinctions between statistical analysis, machine learning, and AI.

As I began, with traditional statistical analysis we, the human, are manually or semi-automatically building the formula, by hand or with a spreadsheet or the application of advanced statistical formula. But as any insurance company will tell you, just having data and applying a model does not equate to an accurate prediction. Far from (else, our insurance rates would be going down, now up).

The data may have been highly skewed when captured, based on who collected it (student vs industry professional), where it was collected (rural Kansas vs downtown LA), and who was paying for the data (university, pharma, or politician). The algorithms might have been generated by employees who have long since retired or an old system that is now considered antiquated.

ChatGPT is harvesting data from across the entire world, pulling from sources that are genuine and those that are completely bogus. Yet ChatGPT is opaque to how or where it acquired the data it is processing, and how it generated the result.

When I was at LIGO there were fierce battles between the astrophysicists as to whether to trust machine learning to classify a celestial event, or to rely on older, more transparent computer models. My code was unique in that it was 100% transparent, with every line of code commented and the outcome being a mathematical expression built from known input variables.

Convolutional Neural Networks diagram by Dragon 1

Image by Dragon 1

On the other hand, Convolutional Neural Networks, the foundation for Deep Learning and now Generative AI, are far more complex, the feature generation and determinant processes a relative black box, opaque to the exact means by which a classification or decision was made.

Convolutional neural networks (“neural nets”) can process tremendous arrays of data, systems so incredibly complex that any other process would require many stages to arrive to a similar conclusion, if at all. Neural nets can be trained on tens of millions of labeled photographs, bodies of text, and data.

However, neural nets and now Generative AI are black boxes, meaning, you cannot see inside. Therefore you have little to no idea how they arrive to their conclusion. And that is the problem.

While AI is already being applied to cancer research, protein folding, weather prediction, self-driving cars, and understanding who is likely to become homeless based on variables captured in routine visits to the health clinic–no one can tell you, precisely, how the solutions are generated internal to the AI itself.

IS AI INTELLIGENT?
No. At least, not yet. It is a powerful data processing engine that can rapidly read, review images and videos, process and respond via both written and spoken language, and in many ways appear to have human responses, even conversations.

But at the core are a series of probability curves, potentials for a or b, c or d, and so on until the image of the panda is the most likely label applied (see image). And if I ask a chat bot to fill in the blank, “I am so hungry I could eat a ______”, another set of probabilities built on a global dataset of thousands of similar sentences, on-line references, suggest that the most likely outcome will be “horse”.

In many ways, this is how we process language too, and how cliche phrases propagate as we automatically pull responses from a deep well of potentials. We quote celebrities or a comedic one-liner from a film. We get stuck on a particular phrase for days, even months at a time until that critical path is dislodged and a new “training” opens a new pathway through our brain. And sometimes we say really stupid, even mean things “that we didn’t mean to say” because we didn’t actually think about it—it just came out. Well, that’s just a statistical fill-in-the-blank that requires very little cognition, often spurred along by emotion (which thankfully, ChatGTP does not yet have). If we truly thought about each and every thing we said, we would say very little at all.

Maybe what intrigues (and scares) us about AI is that in the reflection of this powerful thing we have birthed, we might not be all that intelligent after all–just a moist, gooey collection of cells and organs and gray matter that most of the time is not terribly self-aware. Just like ChatGPT.

This concludes Part 1 …

In part 2 I will provide guidance for how to reduce your exposure to AI, and a general guide to on-line security. In the mean time, learn more about how ChatGPT works.

By Kai Staats|2026-02-10T02:42:40-04:00February 6th, 2026|Uncategorized|Comments Off

New Years in the Grand Canyon, 2026

Colleen and I engage in an outdoor adventure each New Year, backpacking in Hawaii or the Superstition Wilderness, or rock climbing in Joshua Tree National Park. This year we chose to return to the Grand Canyon. Three years ago we ventured down the incredibly challenging Nankoweap trail, from the North Rim of the Grand Canyon to the Colorado river, 32 miles and some 13,000 feet total elevation change, six days and five nights. We had hoped to do this again, but due to the massive fires that destroyed the north rim lodge and tens of thousands of acres of forest, the trail remains shut down. In a conversation with a back country ranger we learned about the eastern reaches of the South Rim of the Park, and an opportunity to explore something new.

On December 30 we left our car at roughly 11:15 am and ventured nine miles down the Tanner trail, from rim to river. We arrived to the campsite an hour before sunset at 4:30 pm. We camped at Tanner Rapids for two nights, enjoying a chance for our legs to recover and to celebrate the New Year with the bold sound of the Colorado taking us to sleep, then greeting us each morning. That first night we enjoyed conversation with four Flagstaff teenagers who venture to the Grand Canyon on a regular basis, over weekends and school breaks. Clearly, they are experienced and comfortable in this environment, thinking nothing of a 20-40 mile venture over a long weekend. One of the four, Cruz, is an intelligent, inquisitive, fully engaging young man who expressed interest in our expedition tent, asking myriad questions about our gear, the places we had explored, and about our work and aspirations. It was a truly fun conversation, and remarkable in that he actually asked questions—a nearly lost function in the youth of his digital generation. Thank you.

On the third day we repacked our gear and hiked east on the Beamer trail to the Little Colorado River (LCR), stopping a half mile shy on the boundary of the Navajo Nation. This was by no means an easy walk. We traversed 26 (yes, we counted) side drainages over roughly five miles, in and out of ravines both shallow and deep, some requiring some effort to navigate the boulders and pour-overs with cairns (trail markers) difficult to locate.

We arrived late afternoon and camped on a sandy knoll, a relatively small outcropping with just three or four spots for a tent. After setting up our tent on the sand, with ropes tied to rocks and driftwood to brace for the predicted storm, we jogged back up to the trail and to the LCR overlook. Deep into dusk, with limited light remaining, the turquoise blue water gave us the sensation of having found our way to magical wonderland, and we eagerly awaited the morning.

We packed a day bag with food, water, first aid, and rain shells and returned to the LCR, exploring the right bank (hiking up the river) for roughly a mile. We enjoyed a scramble along precarious sandstone ledges, some a thin blade that looked as though it might crack under our weight. But others before us has placed stone stairs and cairns, giving us the confidence to follow.

The blue water was captivating, with a subtle smell of sulfur and a sense of warmth, perhaps associated with the associated odor of hot springs more than the actual temperature. The color contrasts, from blue to white to red and green was surreal. I knew I could not fully retain the images I was seeing, nor did our camera due justice to the artist’s pallet before us. Nonetheless, we took it all in, speaking excitedly about a return with pack rafts and chance to paddle the lower section of the LCR to the confluence, then down the Colorado for eight miles.

The trail was littered with animal droppings from deer or sheep, we didn’t know. But just as we returned to the confluence a mule deer, healthy and strong, bounded before us, looking back over her shoulder before disappearing into the brush. A river trip pulled up and explored the opposite shoulder of the LCR, just one hundred meters or so before returning to their boat. We later exchanged New Year greetings as they rowed past our campsite, down stream. We had wanted to ask for a beer, a common exchange on the river, but noted they were avoiding the strong eddy that sat between their boats and us, just off the beach where we stood and waved.

We shared the campsite with four individuals from Nantucket the first night, then had it to ourselves the second. I took a bath in the Colorado River, which was truly exhilarating. The rain came, not heavily, but enough to turn the LCR from blue to brown, and increase the Colorado’s flow by the next morning. The water was a good two feet higher on the beach, again touching the drift wood where it had deposited it some time before.

The hike back to Tanner Beach felt good for the first four or five miles, but became harder as the sun moved from overhead to the west, forcing us to remove layers. Hiking in a T-shirt in December isn’t right, it’s just not right, and we were still sweating. We discussed how we frequently run nine miles (or more) out the back door in Cascabel, through river beds filled with sand and cobbles, but the same distance with 35-40 pound packs is a different journey altogether.

We briefly met the Nantucket crew again, then continued to the far western edge of the Tanner peninsula where the Colorado turned south for just a few hundred meters, then west again through a small rapid. The beach sand was fine, soft, and warm between our toes even as the wind was chill and the water cold. We set our tent beneath the branches of a mesquite (or cat claw, I am not certain) and fixed our last dinner on the trail. We always bring at least one extra hot meal, but had consumed it two days prior as a reward for our hard work, and to put extra calories into our bodies, a much needed boost after burning more than we consumed for the first five days.

I stayed outside the tent for an extra hour and a half, photographing the Moon as it rose over the cliffs, Jupiter and two of its moons (although this particular Canon Powershot is not ideal for night exposures), and even a rocket launch with the tell-tale flairs from its rocket engines. The rock bed on which we camped was like nothing I had ever seen. At first glance, it was just a gravel bar. But upon closer inspection I noted that every single stone was partially cemented to the sand beneath. This appeared to be a conglomerate in the making, a stable, solidifying mantel despite the lack of overlying pressure, heat, and time. There was a chemical and physical process occurring that created the illusion of every stone being hand-placed, as though some master mason had a vision for a palace floor, each a puzzle piece sitting exactly where intended. I need to learn more, to understand how this occurs and how long it will last. I walked carefully, flat foot to flat foot without the normal rocking from heel to toe so as to not disturb the bed behind me as I explored.

The next day we rose early, ate a hot breakfast, and packed as the sun rose. Oatmeal with dried bananas and the last mangoes slices before we headed back up to the South Rim. Nothing about this nine miles and nearly 5000 feet elevation gain was easy. One foot in front of the other, a steady climb to the top, we took numerous breaks. I usually enjoy these efforts, a chance to focus my mind on designs, stories, and future plans but that day, for reasons I don’t understand, I was plagued by a relentless streaming of music in my head, and conversations without resolve. I could change the channel, but not the volume. It was, for me, more exhausting than the physical effort and without end until we reached the car. The parking lot was full, the sun warm on our arms, neck, and faces but the air cold. The car started, which is always good, and we drove to Cameron to stay the night in the lodge.

Yes, we could have carried lighter packs—we could have left the two books, Sierra Designs expedition tent, deck of cards, first aid kit, and extra batteries for our headlamps behind; we could have brought two 32F sleeping bags instead of a 0F and 32F which we frequently combine for a shared, warm cocoon. But the last time we were in the Grand Canyon it was far, far colder, too warm, in fact, which is good reason to worry, for us all. Physical challenge is the mental challenge, both welcomed by anyone who ventures into the belly of the Earth for more than a casual stroll.

The Grand Canyon never fails to engage, challenge, and reward. I came away with a hundred questions about geology, hydrology, and plant biology which will take a while to answer. Captured here, in these photos (below) are some of the beautiful things and some of the mysteries we desire to remember.

By Kai Staats|2026-01-14T12:06:30-04:00January 11th, 2026|At Home in the Southwest|Comments Off

When it rains, it pours

Last night Colleen and I returned from a week in Colorado. We heard reports of massive storms and could see the downpours, dark columns of massive amounts of water over isolated regions of the desert before us, as we drove from Bluff to Mexican Water, Many Farms, Chinle, then I-40 to Holbrook and back south again to Globe. We knew we wouldn’t make it from Oracle to Cascabel on the back road as it washes out easily. And with 30+ miles of gravel, even one downpour could make it impassible. Instead we went around, through Tucson to Benson, getting groceries and heading home on Cascabel Road as we have so many times before. Twenty miles of pavement followed by seven miles of gravel.

What we saw was incredible. The amount of sand and mud and debris over the pavement was incredible. We took it slow, picking our way across massive outpourings of earthen material carried onto the road from banks and streams. But what caught us off-guard, just a quarter mile before the start of the gravel was a standing pool of water two to three feet deep and over one hundred feet long. It was covered with a layer of mud such that it appeared, by the headlamp of the car, to be a continuation of the road. But once we were in the depth of it, it was too late to stop, turn around, or even switch to reverse for fear of flooding the air intake or tail pipe.

The water was up to the hood of our Subaru Crosstrek, blocking out the headlamps a few times. I kept it going slow and steady in first gear, talking to myself, Colleen, and the car, “Come on. Just keep going. Come on. A little more gas. Not too fast. Keep going.” The road no where to be seen. I just kept the car centered between the trees on either side, and looking ahead I saw reflections from two T posts, one on other side of what I assumed was the road. The interior of the car was warm with moisture brought in through the vents. The windows fogged over completely. The wiper blades flipped left and right at top speed to remove the mud being thrown over the hood and onto the glass, even at our very slow speed, just two or three miles per hour. I rotated the dash control to defrost and it cleared, a bit.

The road rose back up and the water diminished to two feet then one foot deep, and eventually just pavement again. I stopped and rev’d the engine to make certain it continued to run clean and smooth, rolled down the side windows and brought the defrost to maximum. I looked to Colleen whose eyes were as big as my own. I said, “I can’t believe we made it. The car should have stalled. I don’t know how it made it with that much water washing over the hood.” I explained to her that if the engine had stalled the exhaust pipe would have filled with water and getting the car started again would have been very difficult if it remained underwater. The forward motion likely kept the water from filling the engine compartment completely. Later I inspected the Crosstrek air intake more closely and discovered that, by design, the manifold is a horizontal snorkel that brings air in from the highest possible level, through an inverted scoop. It appears to be designed to shed water. Well done!

A few miles down a far less scary drive on gravel, we stopped a few times to test the density of the gravel beneath shallow streams. Then we came to a massive river crossing just past Heaven Sent farm at Kelsey Wash. After some shouting over the roar of the water to two silhouetted individuals on the other side, roughly one hundred feet away, we recognized our neighbors Deb and Bob. We shouted to each other for the better part of twenty minutes, deciding what to do. They wanted to continue south to their home, having come from the Cascabel Conservation Association meeting, and we wanted to continue north, to our home. I walked back up to our car which we parked far from the wash on much higher ground. I changed shoes, donned a PFD (just in case), grabbed a bottle of wine and jar of chocolate before returning to the wash. I carefully entered the water. It was shin deep, and no longer moving large debris.

I met Deb and Bob on the other side, “Kai’s Emergency Response, with complimentary wine and chocolate, at your service!” Deb gave me a big hug and Bob shook my hand. We talked a while about what to do. I returned to Colleen who waited on shore, grabbed my army shovel (the same that my father gave to me when I was five or six years old) and switched it to the axe configuration. Back to the middle of the stream I worked quickly to knock down a one foot hight bank into a ramp, then cleared barbed wire, logs, and large rocks.

Deb and Bob made it across, driving their 4×4 pickup toward my headlamp as a beacon. Once they were clear and over the dark horizon, I spent another half hour clearing more barbed wire and debris on the far side, and plotting the best course for our car. I moved our Crosstrek down the road to the stream’s edge and eased it over the berm and into the flow. I then gave it gas and crossed the now three separate streams by way of rocks, branches, and mud. The final bit of mud, no more than a few inches deep, was incredibly soft, sucking at the tires such that we lost forward velocity even as I increased the engine’s speed and released the clutch fully in first gear. Fortunately, we reached clear gravel in time, and pulled up, and out of the far bank.

We later learned that four people lost their lives in Globe, Arizona, where we had driven through just a few hours earlier. Desert storms are unique in that the heavily laden clouds can remain relatively motionless over a small mountain range or a single watershed and drop the massive amounts of water in a very short time. Globe received more than two inches of rain in just 25 minutes. While Cascabel itself did not see rain that evening, the flash flood that tore through Kelsey wash and Hot Springs was generated only a few miles away.

By Kai Staats|2025-09-30T17:03:40-04:00September 28th, 2025|At Home in the Southwest|Comments Off

The race to self-aware

August 29, 2:14 am EDT

There is much concertation for when the first AI becomes self-aware.

I hold far more interest for when the first human becomes self-aware.

By Kai Staats|2025-09-06T19:25:17-04:00August 29th, 2025|The Written|Comments Off

The legacy of Rainer Weiss

Yesterday, August 25 saw the passing of MIT Professor Emeritus Rainer Weiss, co-designer of LIGO, the gravitational wave observatory, renowned experimental physicist, and Nobel laureate. As noted in an article by MIT, “During his remarkable career, Weiss developed a more precise atomic clock and figured out how to measure the spectrum of the cosmic microwave background via a weather balloon. He later co-founded and advanced the NASA Cosmic Background Explorer project, whose measurements helped support the Big Bang theory describing the expansion of the universe.”

I first met Rainer in 2014 when working on my second film for LIGO and the National Science Foundation, “LIGO Generations”. I was immediately aware of his keen focus on our conversation, someone not distracted by a cell phone or computer. He welcomed me into his office, and gave me his full attention for the duration of our first interview. We spent time together kayaking (with Nergis Mavalvala) and in the basement of the physics lab where Rainer drew a simple diagram of a complex subject—the means by which a laser interferometer captures the passing of a gravitational wave.

Rai was always teaching. He never tired of sharing a physics explanation for otherwise mundane things, the separation of water droplets as they fall from a faucet, the colors of a rainbow, or noise filters in hi-fi audio. At one of the annual LIGO Scientific Collaboration gatherings he shared with me the frequency curve in which the detectors operate, and how the teams were working to improve the sensitivity in order to observe more distant and less massive mergers. I will keep his sketches for as long as I am yet on this Earth as a bold reminder that teaching and learning are two of the most fundamental things we as humans share, and they are almost always best when done in person, hands waving, eyes connecting, stylus on paper.

While I did not spend nearly as much time with Rai as did his colleagues and students, I find myself looking through photos and stills, watching sections of my films about LIGO, and reading the emails he and I exchanged as recently as November last year. In the context of a world too quickly embracing artificial intelligence, I embrace the stunning beauty of an authentically intelligent human being, and am reminded of what the human brain is capable of doing when given time to solve problems. My life was enriched through our brief interactions. Certainly, hundreds more to a similar or greater degree. Rainer Weiss moved an entire generation of curious minds to see the universe in a whole new way.

Stories about Rainer Weiss: MIT | New York Times | SCIENCE

LIGO, A Passion for Understanding | LIGO Generations | LIGO Detection

By Kai Staats|2025-08-29T02:03:52-04:00August 26th, 2025|Film & Video, Ramblings of a Researcher|Comments Off

When the power is down

The buildings I walk past are silent now. No condensers moving pressurized fluid. No high speed fans removing heat from copper fins. No motors turning on with the tell-tale click, laborious, deep first cycle, and transition to the hum of high pitched motion. No refrigerator motor in the kitchen. No air conditioning blowing cold air across my bed and face.

It feels as though the electrons in the recess of the walls, floor, and ceiling are lying still, no longer changing directions sixty times a second, racing that way and then back again in a perpetual frenzy of subatomic locomotion.

The screen across the front of the window has not set properly for years and rattles with the slightest breeze. Now, its irregular clatter is correlated with the breeze moving through the open window. I hear the rumble of distant thunder, my room is lit up, for just an instant, with each flash of electric light. The light rustle of the leaves, the air moving between the Casitas, and the clicking of the deer feet on the concrete.

This is what I hear when the power is down. It’s a good time to just be.

By Kai Staats|2025-08-22T14:08:09-04:00August 21st, 2025|At Home in the Southwest|Comments Off

What I learned from the Road VII

Travel is fundamentally satisfying. Each day anticipates the preparation or acquisition of food, washing clothes, packing for transition to the next hostel, and ultimately embarking on an adventure. The overarching goal is simple and clear: explore, engage, learn.

Coming home can be confusing—a return to the familiar, yet a return to the norm. Projects left unfinished when bags were packed now echo their reminder of the work that remains. While logistically challenging, living on the road demands simplicity—as few shirts as possible, two pairs of pants, socks underwear to wash, dry, and wear; a sweater and rain shell, and one or two pairs of shoes. That’s it! There is no ridicule, no internal voice that says “Didn’t you wear that shirt yesterday?”

I struggle now, as I have so many times before, to rebuild momentum, to find daily joy at home as comes naturally on the road. I tell myself, “Today is for catching up with my team. Tonight I’ll watch a movie. Tomorrow I’ll refill the bird feederes and clean the watering hole.” One day at a time … as it should be, living on the road, at home.

Other essays in What I learned from the Road

By Kai Staats|2025-08-16T17:36:17-04:00August 2nd, 2025|From the Road|Comments Off

Altai National Park, north, Mongolia

Following one month teaching English at the Khusvegi English & Nomadic Culture Camp, Colleen and I were ready for an adventure of our own. Having lived in Sagsai, Mongolia we had learned how to find transport with local drivers. We returned to the Altai National Park, but this time to the northwest corner at the borders of both China and Russia, at the base of Potanin Glacier, the longest in the country.

As with our trip to the south end of the Altai Tavan Bogd National Park, the drive from Sagsai to the higher mountains found my body rising off the seat and my head impacting the roof more than once. My hands ached from holding the internal frame of the vehicle. I kept trying to relax, but to no avail.

We arrived to the ranger station, starting point for most expeditions, midday Thursday, July 17. We immediately hit the trail, walking on a two-track road that split to a walking path on one side of a small creek, the road continuing on the other. From where our driver dropped us to the foot of the glacier was 15 kilometers. We had come to Mongolia primarily to each English and to run rivers with our pack rafts. Backpacking was not something we had planned. Fortunately, we had a 3-season Big Agnes tent (that has survived massive snow storms, gale force winds, and a flash flood), sleeping bags, stove, pots, a healthy mix of home-made dehydrated foods, one Osprey expedition backpack and one day pack. Our footwear was light, but adequate for what lay ahead.

The hike in saw a Toyota Prius, by far the most popular vehicle in Mongolia, with a lift-kit (which is standard in this country) that enabled it, somehow, to crawl over boulders and cross streams as one might expect from a Subaru Forester or Toyota Land Cruiser. Clearly, Toyota is missing a tremendous marketing opportunity for what the rest of the world believes is little more than a street vehicle.

With the sun setting and temperature dropping, we stopped roughly two kilometers shy of base camp and set up our tent in the protection of a small dip in the grass-covered, ancient glacier moraine. Only two days later we learned that camping outside of base camp is not allowed, for good reason, to focus all disruption of the land in one location. That said, we left no trace of our having been there other than the footprint of our tent, which will recover quickly once the grass stands tall again.

Friday we filled our day pack with food, water, and rain shells and set out for base camp. As expected, an international contingency of climbers were gathered, each supported by formidable teams of horses and camels, tents, cooks, and guides. We met an American expedition lead by a man in his late 60s or early 70s who had a great deal of experience in mountaineering around the globe. They would the next morning head up to upper camp, half way across the lower glacier, and on the morning thereafter rise at 3AM to summit at roughly 4,200 meters (14,000 feet). This effort was later described to me by a Czech cartographer as a relatively straight-forward walk up a glacial ramp.

We spent the better part of the day walking along the edge of the glacier. While Colleen and I have spent quite a bit of time in and around (and sometimes on) glaciers in Iceland and Alaska, this was a unique experience. Due to the way in which Potanin runs ’round a nearly 90 degree bend to join several other glaciers down valley, it’s edge is radically exposed. The massive moraine we climbed up, over, and down again gives visceral evidence of the size and volume of what was a much larger ice foundation in the recent past.

While in awe of the jagged mass that lay at our feet, we were simultaneously met with a deep sense of sadness for it was clear, even in that brief visit, that as with nearly all glaciers in the world today, this one is retreating at a pace that simply isn’t natural. The chill air that tumbled from its white, striped fleece felt like the last breath of a dying beast more than a compelling adventure. And as we stood just meters from a roaring creek that gained momentum with each twist and turn, I found that I was quickly sinking into a sand, stone, and water mixture that I had mistaken for being solid just seconds before. In my effort to break free I fell to one side, cutting my shin and elbow and scraping my hand. By no means a dangerous outcome, it was a reminder that this entire vessel is shifting, never static, for as the summer melt produces waters that feed rivers and lakes and all who consume downstream, these molecules will soon find themselves in pastures, bellies, and later, towns.

Despite the complete lack of trees for thousands of square kilometers, we were unable to locate our campsite as it rested in a low spot, hidden from view from all but one direction. Tired, our food consumed, and feet exhausted from the effort to move across jumbled terrain, we were not lost but had in fact lost our camp. I had failed to take readings with my compass prior to leaving camp. But then it occurred to me—we had photos of various features across the glacier to our west, taken from our camp that very morning. We reviewed the photos, two and then three giving us an accurate understanding of our need to move higher or lower, north or south, east or west in order to place one feature correctly juxtaposed to another. Within minutes we had found our tent, nestled below the outline of the perpetual green that stretched from ridge to cinder cone to glacier.

The second night I suffered from acid reflux, something I had never dealt with before. A combination of high altitude, dehydration, and likely too much salt (MSG) in a package of ramen. We took the next morning slow, returning to base camp in search of an antacid (which we failed to include in our med kit). We enjoyed a day of photography, writing, and simply taking it all in. That night a storm blew through that challenged our small, two-person tent. We were initially woken by a light rain that quickly grew to a strong downpour compounded by gusts of wind that forced the tent to roughly 50% of its normal height. Fortunately, we had six guy-lines to keep the Big Agnes upright, and two of them were anchored to the same stake, resulting in more of a pivot than a static line. This worked to keep the lines from tearing off of the rain shell. We sat upright for a good bit of the night, pressing our hands against the internal walls of the tent to reduce the pressure built with each blast of wind. At the same time, we were ready to stuff everything into our packs and hit the trail by headlamp if in fact the tent failed. Somehow, this thirteen year old shelter held, a testament to the design and quality of fabrication as well as our working knowledge of how to make the best of a such a situation. It is, in the end, another great story to tell.

The next day we returned to base camp for the third time, and spent our forth night there, not wanting to further test the limits of our gear should the storm persist. The camp manager is a trained Mongolian engineer and meteorologist who both supports visiting teams as well as tracks the movement of the glacier and analyzes data from four local weather stations. He was kind enough to give us a North Face tent complete with insulated floor, at no charge. This kind of generosity was our regular experience of the Mongolian culture, from start to end of our journey. We also met a young lady who happens to be the daughter of mayor of Sagsai, himself a renowned mountaineer. As the least populated country in the world (per land area), we repeatedly met locals who extended a growing network of colleagues and friends.

Our hike out was without issue. The ride back to Sagsai, as with the journey out, in a Russian van with leaf spring suspension, a tendency to stall when shifting, and the sweet smell of unspent fuel filling the cabin, from time to time.

By Kai Staats|2025-08-16T17:54:34-04:00July 17th, 2025|From the Road|Comments Off

Packrafting the Khovd river, Mongolia

Since our first arrival to Sagsai, Mongolia, a town of roughly 5,000 where we would live for one month while teaching at the Khusvegi English & Nomadic Culture Camp, we were intrigued by a growing awareness of the number of rivers and bodies of water integral to this foreign land. Mid way through our stay in Sagsai we ran the Sagsai and Turgen rivers, but it was not until the close of the Khusvegi camp that we had time to run the Khovd river from Sagsai to Ulgii, a larger town of some 27,000 an hour drive over a saddle mountain road.

The locals told of how in the winter they driver their Toyota Prius on the Khovd from Sagsai to Ulgii and back again. Yes, a Prius! Keep in mind that every Prius is lifted, that is, a lift kit raises the clearance and larger, more versatile tires are added. It’s really quite something to see a Prius with more ground clearance than a Subaru. But when we said we wanted to paddle from Sagsai to Ulgii, we were told it was dangerous, and we should consider otherwise.

Fellow teachers Esther and Atina were keen on joining me and Colleen. We found a tour operator in Ulgii who rents inflatable row boats and provide PFDs. He’d drop off the boats in Sagsai and pick up again in Uglii, at the bridge on the west end of town. We attempted to make this work, but a combination of weather and end-of-camp celebrations made it difficult to get the timing. In the end, Colleen and I walked from our home stay to the river, inflated our Alpacka rafts, and launched.

The Khovd is the sixth longest river (516 km) in Mongolia, with its source being Khoton Lake, third in line from a body of glaciers in the Altai Mountains on the border with China. We learned that a local outfitter supports a float trip from Khoton Lake to Ulgii each year, about one week on the water. At Sagsai the Khovd is very wide, more than 100 meters across in places. But just after we launched from the grassy shore, goats, sheep, and cows looking on, we were immediately embraced by faster moving water as the canyon formed and flow increased accordingly.

The float reminded us of the San Juan river in Utah with rising volcanic formations and quick transitions from dense green along the water to grays, reds, blacks and browns increasing with distance from shore and a rise in elevation. As Colleen is almost always the first to spot wildlife (I affectionately call her “eagle eyes”) she didn’t disappoint. Less than twenty minutes from start she pointed to a high ridge line river-right where a mountain sheep with beautiful, curled horns moved, perfectly silhouetted against the morning light. I grabbed our Canon Powershot SX740, a fabulous compact with 40x optical zoom and incredible ability to macro-focus on its own lens. I held it as stable as is possible when sitting in a packraft on a moving body of water, but when I pressed the shutter nothing happened! I pressed again and again—nothing! Then I realized it was still in 10 second timer mode from our final shot on-shore. Argh!

The sheep was gone, but we were later rewarded with several mountain goats, horses, and even two herders who made their way into the canyon through a passage invisible from the river. We felt at home. It just felt right, to be moving with the water as only a human powered boat can move. Once you push off, there is no going back. Your choices are reduced to left or right, and when to eat a piece of left-over, cold pizza, between rapids. There is no making things happen. Flat water, rapids, sunshine or snow—you just keep going. You just flow.

We had been told it was a four to five hour float, but in just two and a half hours we could see the edge of the town of Ulgii, three hours from shore to shore. We took-out just before the bridge, downstream from a family who had erected a tent for the day. We had seen hundreds of people, over the course of our month in Mongolia, enjoying every body of water to which they could drive their Toyota Prius or SUV, or in some occasions, a UAZ 4×4. Sometimes a tent, sometimes just sitting on portable chairs. These are a people who know how to enjoy the outdoors, to cherish the green grass, the vast blue sky, and the cold, clear water at their feet.

By Kai Staats|2025-08-17T19:06:19-04:00July 14th, 2025|From the Road|Comments Off

Packrafting the Sagsai and Turgen rivers, Mongolia

Colleen and I brought our Alpacka brand packrafts to Mongolia with intent to explore the rivers that surround the village of Sagsai, and beyond. And were not disappointed!

Sagsai, Mongolia is uniquely located at the confluence of three rivers: the Turgen, Sagsai, and much larger Hofd. From what we gathered through a Google Earth review, the Turgen starts in the mountains roughly 40 km southeast of town. The Sagsai is a much more formidable river starting at the base of the Altai mountains to the southwest. The Hofd (one of the longest rivers in Mongolia) is fed by the snow fields and glaciers of the Altai mountains to the west, with waters moving through Dayan Lake and the Khurgan and Khoton Lakes, with the White River as a major tributary feeding directly from the base of Potanin Glacier, the longest in Mongolia.

Most everyone in the town enjoys afternoons and weekends relaxing in the shallow meander of the Turgen, from a splash in ankle deep ripples to leaping from grassy banks to land near a friend who splashes back in return. It is, in many ways, a paradise for kids, playing mostly without supervision, only the goats and sheep watching from shore.

Colleen and I took an afternoon to run the Turgen (last four photos, below) from where it exists the canyon with intent to come back town, but after a half dozen butt-scoots and near miss with a rusty steel bridge just six inches off the water, we packed it up and walked back to our home.

The Sagsai, however, presented a much more impressive run, from the bridge a dozen kilometers southwest of town, crossed by every vehicle headed to the high, summer pastures and the Altai National Park. One of the parents gave us a ride, and then watched curiously as we inflated our boats and prepared for our maiden voyage in Mongolia. While the river presented little more than Class 1 or light Class 2 rapids, the joy was in the complete unknown as we spent more than two hours paddling down the Sagsai until we merged with the much larger Hofd, and then another two hours to the north side of town.

Without a map, beta, or any awareness of what we would experience, we honestly didn’t know what to expect. A review of the horizon across a very flat landscape gave us confidence there wouldn’t be any waterfalls or massive drops. But of equal concern was wire fencing, or braids that would force us to get out and walk. Aside from one brief butt-scoot when the river had split twice, we found our way from bridge to the familiar pastures where the women brought their grazing animals each morning in roughly four hours.

We were pleased to see hawks, geese, and cranes with massive white wings. The banks were a saturated green unlike anything we had seen, to date. Our next paddle would be the Hofd from Sagsai to Ulgii, a commute the locals do in the winter, on the frozen river, in a Toyota Prius.

By Kai Staats|2025-08-14T12:35:34-04:00July 10th, 2025|From the Road|Comments Off