Why outsiders in physics—and in all fields of science, really—are crucially important

The phenomenon described in the below video by Mark Jeffery about Stephen Wolfram is also what accounts for Dr. Randell Mills' work: the greatest advances in science almost always come from outsiders

After returning home from my visit with Dr. Randell Mills in Princeton this past Wednesday (about whom I’ll be writing more in the coming months), I was feeling the fatigue of three days of travel through New York City and Princeton catching up with me.

I had been staying near La Guardia Airport (I like the new terminal B quite a lot) and I had driven down to Princeton and back on Tuesday; this took me through parts of New York City that I had never seen before.

Gotham from the air, as my plane approached La Guardia to land. No evidence of the Canadian firesmoke that day…

The 12 lanes of traffic on I-95 south from NYC was pretty amazing to see. But it made me long for a UAP-inspired antigravity car that would have made the whole air-travel experience—including the take-your-shoes-off kabuki theater of TSA—completely obsolete.

Bring it on, already! The experience reminded me of the post on private air travel that I had written a few years ago.

I had been born in nearby Niagara Falls back in the late 60’s, but had only been to NYC a handful of times since 2018.

The greatest advances in science almost always come from outsiders: independent thinkers who advance their fields with radically different ideas, instead of from the groupthink-riddled process of so-called “scientific consensus”.

When I arrived home, I decided to relax in my office chair and watch some videos to unwind. I was hoping to discover a few fresh perspectives from recent developments in AI over the past week to help me wrap up the next article on AI that I’m still working to bring to completion.

Instead of the AI topic that I had been surveying over the past month, however, a new suggested video surreptitiously popped up from a channel I hadn’t been aware of before.

The title and topic of the video captured my attention, because I had just met with a man on Tuesday—Dr. Randell Mills—whose work in Physics is also marginalized by mainstream academia for most of the same reasons that are mentioned in the video below.

With my feet up and feeling a bit sleepy, I pressed ‘play’ and settled in.

In this brief video, Mark Jeffery does a masterful job of explaining how the culture of our educational institutions—and the process of acquiring advanced “credentials” in a particular field—can act as brake on forward progress.

Although he’s describing Theoretical and Particle Physics here, his insights are equally applicable to many areas of our world—including government and politics—where groupthink and conformity-to-advance have become entrenched, which is then responsible for slowing down or completely stalling forward progress.

Sabine Hossenfelder, another favorite of mine from the world of theoretical physics, has also written about the stagnation in physics that has occurred over the last 40 years (see below for a particularly stinging quote of hers.)

To my delight, I discovered that not only was Mark Jeffery talking about Stephen Wolfram in this video piece (whose work, coincidentally, is actually a significant cornerstone of my upcoming piece about AI—I serendipitously stumbled onto the perfect video to help inspire my work to complete the AI article!) but Mark also has a whole YouTube channel—The Last Theory—dedicated to explaining how to grasp Wolfram’s surprisingly insightful work on theoretical physics.

I love his approach and have learned a lot already about how to understand Wolfram’s Physics concepts.

I agree with Jeffery that Wolfram’s work on approaching theoretical physics from an entirely new direction is crucially important and may help relieve the stagnation in Physics—but—as you’ll learn in my upcoming AI article—I believe it is important for reasons that are much, much more thought provoking.

Wolfram is himself a particle physicist who broke from the mold (he received a PhD from Caltech in 1980.) In 1988 he went off in a different career direction, and created a brilliant bit of software for mathematics, science and engineering — Mathematica— that has become a favorite tool of mathematicians worldwide.

I first learned of it in the mid 90’s from my own mentor, who besides being an avid Mathematica user (he has been using it for more than 30 years, well into his mid 80’s) was also an acquaintance of Wolfram’s.

Wolfram has since extended the power of Mathematica into the reach of many more people by building Wolfram Alpha which was first released in 2009.

If you have some interest or competency in engineering, science and math but have never played around with Wolfram Alpha…you should. If you are trying to help a teenager with algebra or calculus homework…Wolfram Alpha is also for you, trust me.

More about Wolfram Alpha and its surprising role in my new piece on AI coming soon…but for now, if you haven’t seen it yet, take a dive into the world of Wolfram Physics.

From the Wolfram Physics project: examples of how simple “rules” applied iteratively to simple graphs and hypergraphs can lead to fantastically complex results—structures which may in fact be good models for better understanding our Universe.

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As mentioned above, here is Sabine Hossenfelder, in a quote from this article of hers:

We are today making more investments into the foundations of physics than ever before. And yet nothing is coming out of it.

“Ten-thousands of wrong predictions sounds dramatic, but it’s actually an underestimate. I am merely summing up predictions that have been made for physics beyond the standard model which the Large Hadron Collider (LHC) was supposed to find: All the extra dimensions in their multiple shapes and configurations, all the pretty symmetry groups, all the new particles with the fancy names. You can estimate the total number of such predictions by counting the papers, or, alternatively, the people working in the fields and their average productivity.

They were all wrong. Even if the LHC finds something new in the data that is yet to come, we already know that the theorists’ guesses did not work out. Not. A. Single. One. How much more evidence do they need that their methods are not working? “

Spot on, Sabine.

More to come soon on Wolfram Alpha and its potential role in the future of AI.