Mind Matters Natural and Artificial Intelligence News and Analysis

TagRandomness

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Blockchain Network, Data Stream

Define Information Before You Talk About It: Egnor Interviews Marks

Has anyone ever given you some useless information? What does it even mean for information to be meaningful? This week, on Mind Matters News, guest host Dr. Michael Egnor interviews our own Robert J. Marks about information, as well as the creative limits of artificial intelligence, and why evolutionary algorithms aren’t the magic bullet they’re often presented to be. Show…

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Coins on a gray table

Why Is Randomness A Good Model, But Not A Good Explanation?

After all, random processes are used all the time to model things in science

The previous article I wrote about randomness proved quite controversial. After all, random processes are used all the time to model things in science. How can I say randomness is not a scientific explanation? Let me first make a distinction between a model and an explanation. A model shows us how some physical thing operates, but it does not explain the cause of the thing. An explanation, on the other hand, tries to explain the cause. But surely if we can effectively model something with randomness, then randomness must also be part of the causal explanation for the thing? Well, not so fast. Let’s look at how we model randomness with computers. Computers themselves are not random in the slightest.…

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a hand rolling dice

Randomness is Not a Scientific Explanation

We can never know if anything is truly random

It is common in the sciences to claim aspects of our universe are random: In evolution, mutations are random. In quantum physics, the wave collapse is random. In biology, much of the genome is random. In business theory, organizational ecologists state new ideas are random. There is a general idea that everything new has its origins in randomness. This is because within our current philosophy of science, the two fundamental causes in our universe boil down to randomness and necessity. Since necessity never creates anything new, then by process of elimination the source of newness must be randomness. Similar to how the ancient Greeks believed the universe originated from chaos. Here’s the irony of the view that whatever is unique…

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Choosing the High Road or Low Road

Freebits: An Interesting Argument From the Big Bang for Free Will

There are two types of uncertainty, we learn, only one of which could create free will

Caleb Scharf (pictured), author of The Ascent of Information (2021), offers an excerpt at Nautilus that introduces two new terms, the “dataome” and “freebits.” The dataome is all the ways human beings create information, from cave paintings to cloud servers. He asks, “Was all of this really inevitable? Did we ever have a choice in creating a dataome or doing any of the things we do, and does any self-aware entity in the universe have a choice either?” Relying on theoretical computer scientist Scott Aaronson’s 2013 essay, “The Ghost in the Quantum Turing Machine,” he asks us to consider that there are two types of uncertainty, only one of which could create choice. Typical “randomness” actually follows statistical laws, a…

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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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Close up cute little child girl spinning a coin to make decision. Heads or tails game.

The Chaitin Interview II: Defining Randomness

In the 1960s, mathematician and computer scientist Gregory Chaitin published a landmark paper in the field of algorithmic information theory in the Journal of the ACM – and he was only a teenager. Listen in as Robert J. Marks explores that paper with Chaitin, covering Chaitin’s definition of randomness and his philosophical interest in algorithmic information theory. Show Notes 00:27…

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Inside an old Silo

Robert J. Marks On AI Evolutionary Computing (Part III)

Can artificial intelligence algorithms prove Darwinian evolution? Why won’t some scientists admit the design inherent in evolutionary computing? Do random processes disprove intelligent design? Dr. Michael Egnor discusses evolutionary computing, the no free lunch theorem, and the role of purpose in chance with Dr. Robert J. Marks. Show Notes 00:41 | Introducing Dr. Robert J. Marks 01:10 | The role…

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burst set of random numbers glowing on a black background

How Spooky “Quantum Collapse” Can Give Us More Secure Encryption

If entangled photons linked to random numbers are transmitted, parties on either end can know, via high error rates, that they’ve been intercepted.

In a recent podcast, “Enrique Blair on quantum computing,” Walter Bradley Center director Robert J. Marks talks with fellow computer engineer Enrique Blair about why quantum mechanics is so strange but important to our future. They discussed “quantum communication” (generally, quantum encryption) and why safer quantum encryption might be easier to achieve than general quantum computing. https://episodes.castos.com/mindmatters/Mind-Matters-110-Enrique-Blair.mp3 The discussion of quantum communication begins at approximately 55:32. The Show Notes and transcript follow. Robert J. Marks: I know there’s lots of interesting quantum communication today. The NSF and the Department of Defense are throwing big bucks at it. What is it, just roughly? Enrique Blair: Quantum communication really is the use of quantum mechanics to share information in a secure manner.…

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Quantum Wave

Bingecast: Enrique Blair on Quantum Computing

What is quantum mechanics? What can quantum computers do that classical computers can’t? Has Google achieved quantum supremacy? Robert J. Marks discusses the weird world of quantum mechanics with Dr. Enrique Blair. Show Notes 00:54 | Introducing Dr. Enrique Blair, a professor of electrical and computer engineering at Baylor University 03:08 | The history of quantum mechanics 13:16 | Quantum…

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upset sick mature woman in kerchief looking at smiling reflection in mirror, cancer concept

Cancer Maps—An Expensive Source of Phantom Patterns?

Is the money the U.S. government spends on tracking cancer patterns a good investment? There’s a way we can tell

The U.S. government puts interactive maps on the internet that show the geographic incidence (all the way down to census blocks) of various types of cancer. Millions of dollars are spent each year maintaining these maps, but for what purpose? The problem with cancer maps is that they tempt the curious and fearful to scrutinize the brightly colored chunks, thinking that any patterns they discover must be meaningful. However, statistical patterns are sometimes meaningless. For example, I flipped a coin ten times and got these results: There is a cluster of 3 heads in a row and a cluster of 4 tails in a row: These clusters are not at all surprising. If a fair coin is flipped ten times,…

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Enrique Blair on the Future of Quantum Computing

Google has claimed quantum supremacy. What does that mean? What is the future of quantum computing? Robert J. Marks discusses quantum communication, supremacy, and computing with Dr. Enrique Blair. Show Notes 00:49 | Introducing Dr. Enrique Blair, a professor of electrical and computer engineering at Baylor University 01:14 | Problems with quantum computing 01:54 | What is quantum supremacy? 03:06…

Photo by Amanda Jones

Bridge: Why Shuffle the Deck Seven Times?

For years, competitive bridge players complained that computer shuffling of cards produced goofy results. Statisticians sided with the computers

Bridge is one of the few games where computer algorithms have not yet demolished the best human players but, despite claims to the contrary, algorithms do a much better job of random shuffling of the deck.

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Colorful toothpicks or pick-up sticks

How Can We Measure Meaningful Information?

Neither randomness nor order alone creates meaning. So how can we identify communications?
Dropping a handful of toothpicks on the table seems to produce a different sort of pattern than spelling out a word with toothpicks. Surprisingly, this intuitive distinction is harder to make in math and the sciences. Algorithmic specified complexity (ASC) enables us to distinguish them. Read More ›