Mind Matters Natural and Artificial Intelligence News and Analysis

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Closeup of woman's hands holding windup toy, selective focus

Before Digital: The World’s Most Amazing Windup Toys

Before electronics, there was mechanics — and it’s amazing what human ingenuity can do with a simple windup mechanism

Windup toys were what we had before we had electricity and robotics. Some very elaborate ones were designed by clockmakers, starting in the late sixteenth century. Most of these clever clockworks, if they survived at all, survive only as faithful replicas. In order of approximate dates, here are some that did — remarkable testimonies to human skill, artistry, and cleverness: 1560s: One of the earliest is a mechanical monk: “The lore surrounding the monk is that King Philip II, son of Charles V, commissioned [clockmaker Juanelo] Turriano to create the penitent automaton after Philip’s son had recovered from a deathly illness. The king of Spain had prayed for his son’s recovery, promising a miracle for a miracle, and this machine…

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Omega, the letter of a Greek alphabet. Greek numerals, mathematical eight hundred number concept. Abstract, digital, wireframe, low poly mesh, Raster blue neon 3d illustration. Triangle, line dot

Is Chaitin’s Unknowable Number a Constant?

One mathematics team has succeeded in the first 64 bits of a Chaitin Omega number

In this week’s podcast, “The Chaitin Interview V: Chaitin’s Number,” Walter Bradley Center director Robert J. Marks continued his conversation with mathematician Gregory Chaitin, best known for Chaitin’s unknowable number. In this segment, Dr. Marks and Dr. Chaitin discuss whether the unknowable number is really a number… or is it a constant? In earlier podcasts linked below, they have discussed a variety of topics ranging from gifted mathematicians of the past through how to understand creativity in a mathematical way—and more. https://episodes.castos.com/mindmatters/Mind-Matters-128-Gregory-Chaitin.mp3 This portion begins at 01:32 min. A partial transcript, Show Notes, and Additional Resources follow. Robert J. Marks (pictured): I want to clear up something first of all. Stanford’s Thomas Cover and Joy Thomas wrote a book that…

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Arrested man handcuffed hands at the back

How China’s “Hostage Diplomacy” Traps Unsuspecting Visitors

Canada’s “Two Michaels” await their fate in prison in China, hostages to the growing tensions in a high-tech war

Canadian entrepreneur Michael Spavor (pictured) and former Canadian diplomat Michael Kovrig were arrested in China in 2018 on charges of espionage and sharing state secrets, and held in prison since then. Spavor’s trial was on March 19, 2021, in Dandong near China’s border with North Korea. Kovrig’s trial was on March 22 in Beijing. As of this writing, no verdict has been announced. Their trials coincided with the U.S-China Summit in Anchorage, Alaska, on March 18 and 19, 2020, which involved a tense back-and-forth between the two countries. Court proceedings were closed-door and Spavor’s and Kovrig’s lawyers were not allowed to be present. That, according to Canada’s deputy chief of mission in China, violates the Canada-China consular agreement. Prime Minister…

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hand of scientist holding flask with lab glassware in chemical laboratory background, science laboratory research and development concept

A Question Every Scientist Dreads: Has Science Passed the Peak?

Gregory Chaitin worries about the growth of bureaucracy in science: You have to learn from your failures. If you don’t fail, it means you’re not innovating enough

In this week’s podcast, “The Chaitin Interview III: The Changing Landscape for Mathematics,” Walter Bradley Center director Robert J. Marks interviewed mathematician and computer scientist Gregory Chaitin on many things, including whether the great discoveries in science are behind us — not due to lack of creativity or ability on the part of scientists — but to the growing power of corporate and government bureaucracies to stifle research. But then a question arises: Could science, succumbing to the swamp of bureaucracy, be losing that inventive edge? https://episodes.castos.com/mindmatters/Mind-Matters-126-Gregory-Chaitin.mp3 This portion begins at 24:56 min. A partial transcript, Show Notes, and Additional Resources follow. Gregory Chaitin: What did an airplane engineers say once in a speech I heard? He said, “In the…

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technician standing in front of giant circuitboard, slight zoom effect

For Computers, Smart Is Not the Same Thing as Fast

In response to a reader’s good question …

In a recent article, I argued that computers are not, and never can become smarter. An insightful reader wrote to ask, “What if smartness is defined by speed?” This is a good point. The debate revolves around the definition of “smart.” and if we define “smart” as “fast”, then since computers are certainly getting faster they will necessarily become smarter. Such a definition has intuitive appeal. Think of the world’s best chess player versus a beginner. One of the big distinctions is the chess expert will choose a good move more quickly than a beginner, and in general will play faster than a beginner. As such, play speed demonstrates a certain level of intelligence on the part of the player.…

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Online education concept

How Stephen Wolfram Revolutionized Math Computing

Wolfram has not made computers creative but he certainly took a lot of the drudgery out of the profession

In last week’s podcast, “The Chaitin Interview III: The Changing Landscape for Mathematics,” Walter Bradley Center director Robert J. Marks interviewed mathematician and computer scientist Gregory Chaitin on many things mathematical, including why math or engineering geniuses (Elon Musk came to mind, of course) can’t just follow the rules. This week, we look at Stephen Wolfram’s new program that checks your hard math. What can — and can’t — it do for mathematicians? https://episodes.castos.com/mindmatters/Mind-Matters-126-Gregory-Chaitin.mp3 This portion begins at 13:22 min. A partial transcript, Show Notes, and Additional Resources follow. Gregory Chaitin: Now, there is what I regard as a piece of AI, so it might be interesting to talk about it. My friend Stephen Wolfram (pictured), the system he’s created,…

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SpaceX Concept Spacecraft in orbit of the Earth. SpaceX Elon Musk Mars programm 3d render

Why Elon Musk and Other Geniuses Can’t Afford To Follow Rules

Mathematician Gregory Chaitin explains why Elon Musk is, perhaps unexpectedly, his hero

In last week’s podcast, “The Chaitin Interview III: The Changing Landscape for Mathematics,” Walter Bradley Center director Robert J. Marks interviewed mathematician and computer scientist Gregory Chaitin on many things mathematical, including why great books on math, advancing new theorems, aren’t written much any more. This week, we look at why geniuses like Musk (whose proposed Mars Orbiter is our featured image above) simply can’t just follow the rules, for better or worse: https://episodes.castos.com/mindmatters/Mind-Matters-126-Gregory-Chaitin.mp3 This portion begins at 7:57 min. A partial transcript, Show Notes, and Additional Resources follow. Gregory Chaitin: Look at Elon Musk (pictured). He’s my great hero. He’s a wonderful engineer and he’s a wonderful entrepreneur and he doesn’t follow the rules. Robert J. Marks: He doesn’t,…

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DNA Computing - Abstract Illustration

Is Computing With DNA the Wave of the Future?

We are running out of conventional space to store information and life forms’ DNA stores it much more efficiently

Why would we want to compute with DNA? Well, first, we are fast approaching the limit of how small we can make computers. So some scientists are turning to the designs in nature for help: The issue with transistors is that they now exist at the scale of a few nanometers in size—only a few silicon atoms thick. They can’t practically be made any smaller than they are now. If they get any smaller, the electrical current flowing through the transistor easily leaks out into other components nearby or deforms the transistor due to heat, rendering it useless. You need a minimum number of atoms to make the transistor work and we’ve functionally reached that limit. John Loeffler, “What is…

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The first model of the computational mechanism is an arithmometer.

Computers Are Getting Faster But Are They Getting Smarter? No.

Computers are Turing machines, limited to operations that can be completely understood in relation to their programming

Won’t quantum computers be smarter than regular ones? No. Still No. What about optical computing, computing with DNA, or some other exotic form of computation? Always No. A skeptical reader might ask, Why such a definitive answer? How do you deal with the spectacular performance of deep learning? What about AlphaGo Zero? What about Watson? What about the infamous Deep Blue? What about quantum supremacy? Don’t these examples all disprove your point? No. All forms of computation past, present, and future will be physical. And all physical phenomena can be modeled by a Turing machine (pictured). No matter how fast the computer runs, the computer will never be more powerful than a Turing machine. A Turing machine consists of five…

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Real Php code developing screen. Programing workflow abstract algorithm concept. Lines of Php code visible under magnifying lens.

How did Ray Solomonoff Kickstart Algorithmic Information Theory?

He started off the long pursuit of the shortest effective string of information that describes an object

In last week’s podcast,, “The Chaitin Interview II: Defining Randomness,” Walter Bradley Center director Robert J. Marks interviewed mathematician and computer scientist Gregory Chaitin on how best to describe true randomness but also on what he recalls of Ray Solomonoff (1926–2009), described in his obit as the “Founding Father of algorithmic information theory.” https://episodes.castos.com/mindmatters/Mind-Matters-125-Gregory-Chaitin.mp3 This portion begins at 10:30 min. A partial transcript, Show Notes, and Additional Resources follow. Gregory Chaitin (pictured): Ray Solomonoff was interested in prediction but I was more interested in looking at a given string of bits and asking, does it have structure or not, and the incompleteness results regarding this question. For example, most strings of bits have no structure, according to this definition. They…

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Infinite random numbers, original 3d rendering background, technology and science concepts

Chaitin’s Discovery of a Way of Describing True Randomness

He found that concepts from computer programming worked well because, if the data is not random, the program should be smaller than the data

In this week’s podcast, “The Chaitin Interview II: Defining Randomness,” Walter Bradley Center director Robert J. Marks interviewed mathematician and computer scientist Gregory Chaitin on randomness. It’s a subject on which Chaitin has thought deeply since his teenage years (!), when he published a journal paper on the subject. How do we measure randomness? Chaitin begins by reflecting on his 1969 paper: https://episodes.castos.com/mindmatters/Mind-Matters-125-Gregory-Chaitin.mp3 This portion begins at 1:12 min. A partial transcript, Show Notes, and Additional Resources follow. Gregory Chaitin: In particular, my paper looks at the size of computer programs in bits. More technically you ask, what is the size in bits of the smallest computer program you need to calculate a given digital object? That’s called the program…

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Program development concept. Young man working with computer

Why Software Cannot Just Evolve — a Demonstration

The claims for Avida — a software program that is supposed to “evolve” solutions via neo-Darwinian evolution — fail the most basic test

A Michigan State University publication headlined a media release declaring: “Evolution of learning is key to better artificial intelligence” (September 19, 2019). Reportedly, researchers used the computer simulation software, Avida, to show the “evolution of learning.” On that view, artificial intelligence arises via neo-Darwinian evolution. Really? The “Sound Bites” Were Exciting… The university’s team “composed of biologists and computer scientists used a digital evolution program that allowed them to observe tens of thousands of generations of evolution in just a few hours, a feat unachievable with living systems.” According to the release: • “The results are the first demonstration that shows the evolution of associative learning in an artificial organism without a brain.” • “While the environment was simulated, the…

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font, lead set, book printing

The Myth of “No Code” Software (Part III)

The complexities of human language present problems for natural language programming

Many visions of the future include humans programming through “natural language” — where humans merely state what they want and computers “figure out” how to write code that does what is requested. While there have been many demos that have led people to believe that this will be possible, the truth is, the idea has so many problems with it, it is hard to know where to begin. Let’s begin with the successes of natural language programming. Wolfram|Alpha is probably the best-known natural language programming system. You type in a command in natural English, and Wolfram|Alpha converts that command into native Mathematica code and runs it. In 2010, Stephen Wolfram announced that Wolfram|Alpha signified that natural language programming really was…

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Cardboard boxes with empty space on left side, logistics and delivery concept. 3D Rendering

The Myth of “No Code” Software (Part II)

Why (and where) no-code doesn't work

In my previous article, I noted that what programmers do is translate ambiguous specifications into very exact specifications, taking into account all of the specific subtleties that the implementation requires. However, I recognize that those not familiar with custom software may not recognize the problem. This article describes in additional detail the kinds of considerations that cause no-code solutions to be problematic. The essence of the problem is this: there are an infinite number of possible ways your business could possibly work, but only one way that it actually works. The work of the programmer is to make sure the software matches the specific way that your business works. Let’s take something simple like calculating shipping. It might be easy…

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Programming Work Time. Programmer Typing New Lines of HTML Code. Laptop and Hand Closeup. Working Time. Web Design Business Concept.

The Myth of “No Code” Software (Part I)

"No code" software has its place, but not as a replacement for programmers

For at least the past twenty-five years of software development, people have been claiming that, using this tool or that tool, we will be able to build software with “no code,” and that our tools will build code for us.  The claims have varied with whatever the current technology is. In the 1990s, the idea was that we could have a system which allowed building software entirely with drag-and-drop interfaces. Tools such as Visual Basic, Delphi, PowerBuilder, and even Microsoft Access made people think that this was an achievable dream. It turned out not to be deliverable on its promises. We’ll get more into the “why” later on. Today we have a new set of tools and a new set…

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Shot of Corridor in Working Data Center Full of Rack Servers and Supercomputers with Pink Neon Visualization Projection of Data Transmission Through High Speed Internet.

Would Super AI Cure Cancer — or Destroy the Earth?

Max Planck Institute computer scientists say that we not only don’t but can’t know

An international team of computer scientists associated with the Max Planck Institute concluded that, given the nature of computers, there is no way of determining what superintelligent AI would do: An international team of computer scientists used theoretical calculations to show that it would be fundamentally impossible to control a super-intelligent AI “A super-intelligent machine that controls the world sounds like science fiction. But there are already machines that perform certain important tasks independently without programmers fully understanding how they learned it. The question therefore arises whether this could at some point become uncontrollable and dangerous for humanity”, says study co-author Manuel Cebrian, Leader of the Digital Mobilization Group at the Center for Humans and Machines, Max Planck Institute for…

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Teddy bear and toys in a baby's room

Why Medical Device Companies Use Priorities Created by Toy Makers

The priorities followed by product developers arise from the ontology they use

The priorities of product development teams arise from the ontology, the beliefs about the nature of reality, they follow. One of the greatest values of defining that ontology is to identify blind spots and wrong assumptions. When the source of priorities is clear, improved, more adaptable options become possible. As Clayton Christensen (1952–2020, pictured) has said: To grow profit margins and revenue, he observes, such companies tend to develop products to satisfy the demands of their most sophisticated customers. As successful as this strategy may be, it means that those companies also tend to ignore opportunities to meet the needs of less sophisticated customers — who may eventually form much larger markets. A hierarchy of products starts with the components,…

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Mensch und Roboter in der Medizin der Zukunft, Beruf Arzt am Arbeitsplatz

Can Robots That Work With People Ever Be Safe?

Robot IQ offers five reasons why not

Cobots are robots designed to be friendly to people. But some doubt that friendship will work: It can be tempting to think of risk as an either/or situation — either your application is safe or it isn’t. In reality, risk is a sliding scale and you can never get rid of all risks completely. You can only know the true risk of a particular task by performing an adequate risk assessment. You need to do this whether the robot is collaborative or not. Truth: cobot safety can be changed to suit task performance The reality is that cobots have always been high-performance robots suitable for a range of industrial applications. Instead of being lesser robots, as some people mistakenly believe,…

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cropped shot of radio host speaking in microphone in broadcasitng studio

Radio Is Changing From Hardware to Software: New Policies Needed!

Perhaps surprisingly, theology may play a role in determining how radio will be used

As I noted in an article earlier this week, dynamic spectrum access networks (DySPAN), implementing policy-based radio, are defining the future of wireless. The new networks are based on ontologies. Ontology is the study of the essential nature of a subject. It identifies the objects or variables that are involved. It then identifies the relationships between them. An ontology identifies the variables and how they relate to one another. That knowledge is then used to develop solutions. The initial ontology focuses on the variables that may result in one radio service interfering with another. The subject is the transmission level. The purpose is to improve coexistence. The goal is to get transmitters to share the same spectrum with a minimum…

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Team of  programmers working on new project.They working late at night at the office.

Does Programming Depend More on Math or Language Skills?

Neither, actually, say researchers. It’s a more global network

Researchers have discovered that learning to code software uses not just math or language skills but rather a broader region of the brain called the “multiple demand network,” which is active when we are solving complex problems: “Understanding computer code seems to be its own thing. It’s not the same as language, and it’s not the same as math and logic,” says Anna Ivanova, an MIT graduate student and the lead author of the study. Anne Trafton, “To the brain, reading computer code is not the same as reading language” at MIT News Paper. (open access) (December 15, 2020) Neuroscientist Evelina Fedorenko, another of the study’s authors, says that there are two schools of thought regarding programming: One is, you…