Mind Matters Natural and Artificial Intelligence News and Analysis

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Network connected across planet Earth ,  view from space. Concept of smart wireless communication technology . Some elements of this image furnished by NASA

Google Cloud’s Ankur Jain To Speak at COSM 2022

One of his key initiatives is bringing internet connectivity to less well-served parts of the globe.

Ankur Jain, VP Engineering for Google Cloud for Telecom, Distributed Cloud, and Immersive Stream, will be speaking at COSM 2022, November 9–11 in Bellevue, Washington. Go here to get the Early Adopter rate before September 15 (tomorrow). At work, he has focused on cross-Google programs like cloud computing, mobile communications, 5G, and privacy issues. One of his key initiatives is bringing internet connectivity to less well-served parts of the globe. He noted in 2017, “As people increasingly access the Internet through their mobile devices, mobile operators are now designing their next-generation networks based on many of the same principles that we’ve adopted to power our own networking infrastructure.” In his current position, he leads Google Cloud’s Telco, Distributed Cloud Edge,…

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black metal spiral staircase in grayscale photography

How AI Neural Networks Show That the Mind Is Not the Brain

A series of simple diagrams shows that, while AI learns faster than the human brain, the human mind tackles problems that stump AI

Recently, I’ve been arguing (here and here, for example) that we can use artificial neural networks (ANNs) to prove that the mind is not the brain. To recap, here is the logic of my argument: Premise A: neural networks can learn better than the brainPremise B: the human mind can learn better than a neural networkConclusion: the human mind can learn better than the brain, therefore it is not the brain This means if we can conclusively show the human mind can learn better than a neural network, then the mind is not the brain. For Premise A, I’ve argued that the differentiable neural network is a superior learning model compared to the brain neuron’s “all or nothing principle”. The…

Machine learning , artificial intelligence , ai, deep learning blockchain neural network concept. Brain made with shining wireframe above multiple blockchain cpu on circuit board 3d render.

Artificial neural networks can show that the mind isn’t the brain

Because artificial neural networks are a better version of the brain, whatever neural networks cannot do, the brain cannot do.

What is the human mind? AI pioneer Marvin Minsky (1927–2016) said in 1987 that essentially “Minds are what brains do.” That is, the mind is the result of electrical waves cycling through the brain, as neurons spike and synapses transmit signals. But is that true? Can we test this idea? We can indeed, using artificial neural networks. One of the most popular approaches to artificial intelligence is artificial neural networks. These networks, inspired by an early model of how neurons fire (the McCulloch–Pitts model), consist of nodes, where each node is similar to a neuron. A node receives signals and then sends them to its linked nodes based on an activation function. There are, of course, differences between neural networks…

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Chatbot assistant, Ai Artificial Intelligence

Prof: How We Know Google’s Chatbot LaMDA Is Not a “Self”

Carissa Véliz, an Oxford philosophy prof who studies AI, explains where Google engineer Blake Lemoine is getting things mixed up

Say what you want about Blake “LaMDA is a person!” Lemoine. He has forced many people to help us clarify what AI — and in particular, a large language program — is and is not. For that, we should thank him. First, LaMDA is not conscious, sentient, not a self. And second, it’s not even a new idea, just a much bigger and more sophisticated version of a 1960s idea. Oxford philosophy prof Carissa Véliz, author of Privacy Is Power (2021) reminds us of philosopher Thomas Nagel’s seminal question, What is it like to be a bat? Nagel meant that, if an entity is be conscious or sentient, there must be something that it “is like” to be that entity.…

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Change Chance

The Salem Hypothesis: Why Engineers View the Universe as Designed

Not because we're terrorists or black-and-white thinkers, as claimed. A simple computer program shows the limits of creating information by chance

In the fun-filled world of internet debate between creationists and evolutionists, we encounter the Salem Hypothesis: Creationists tend to be engineers. Many explanations have been offered for this phenomenon (apparently named after Talk Origins contributor Bruce Salem): engineers are closet terrorists creationists are trying to protect their fragile beliefs a desire to exert authority engineers like simple black and white answers There’s a reason internet forums are not known for flattering character analysis! Anyhow, the true reason for the Salem Hypothesis is summed up in this graph. Read on to find out why. Engineers are more likely to be creationists because they are familiar with what it takes to design complex things for specific tasks. Which is exactly what we…

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ants building a bridge

Do Ants Think? Yes, They Do — But They Think Like Computers

Computer programmers have adapted some ant problem-solving methods to software programs (but without the need for complex chemical scents)

Navigation expert Eric Cassell, author of Animal Algorithms: Evolution and the Mysterious Origin of Ingenious Instincts (2021), offers some insights in the book into how ants organize themselves using what amount to algorithms, without any central command: Ants are remarkably consistent in their lifestyle: All of the roughly 11,000 species of ants live in groups, large or small. There are no known solitary ants. Living in groups, they have developed a social lifestyle that includes “agriculture, territorial wars, slavery, division of labor, castes, consensus building, cities, and a symbolic language.” (p. 85) How is this managed by ants with very small brains (200,000 to 250,000 neurons) and very limited individuality? For comparison, among mammals, the agouti has roughly 857 million…

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Cloud in woman hands on blue sky

Arm in the Cloud?: Lower Cost and Higher Performance

A quick tutorial on why Arm technology has 90% of the cell phone market

Central processing units (CPUs) are usually classified according to their architecture. Historically, desktop computers (especially non-Apple computers) were almost entirely based on Intel’s x86 32-bit architecture, with more recent ones supporting AMD’s 64-bit extensions for more modern computers. The x86 architecture has never ruled because it was a great architecture for the future, but merely because of compatibility — essentially, if you write software to one architecture, it won’t run on another one. The one company that pushed more aggressively for new architectures was Apple, which switched its Macintosh operating system through four major CPU architectures: Motorola 68k, PowerPC, Intel x86, and now Arm. Not only that, their earlier Apple II series ran yet another CPU architecture—the 6502. Because Apple…

New York, USA - 26 April 2021: Kubernetes company logo close-up on website page, Illustrative Editorial.
New York, USA - 26 April 2021: Kubernetes company logo close-up on website page, Illustrative Editorial

How Does A Kubernetes Cluster Work?

A general overview of the Kubernetes environment

Now that you have some concrete experience using Kubernetes, this article will present the basic theory of how a Kubernetes cluster works. We won’t talk about how to accomplish these things in the present article – the goal is to provide you with a broad understanding of the components of Kubernetes. Basic Kubernetes Components Kubernetes comes with a lot of different components, and it is hard to get them all shown on the same diagram. Therefore, I will just give a high-level picture of what a Kubernetes cluster looks like. The image below shows the basic setup, which we will cover in this article. You see here a separation between the internal Kubernetes network and the Internet. Note that this…

Laptop with cloud computing diagram

Getting Started with Kubernetes: A Cluster Setup Walkthrough

Setting up a Kubernetes cluster in Linode is incredibly simple

This series will give you an overview of Kubernetes, the popular open-source cloud computing platform developed by Google. Kubernetes allows for the development of cloud-based platforms using entirely open specifications, so you are never tied down to a specific vendor. Many cloud vendors, such as AWS, have proprietary ways of developing scalable web applications (such as their Lambda system). The problem is that this ties your application to their system, and, as we have seen with Parler, Amazon gives and Amazon takes away. Therefore, it is wise to not tie your infrastructure too tightly to a single vendor. Kubernetes allows you to build large-scale scalable applications in the cloud in a way that is transferable to a variety of vendors.…

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Server room or server computers.3d rendering.

Getting Started with Kubernetes: A Brief History of Cloud Hosting

A history lesson for a better understanding of why web infrastructure hosting is the way it is

Oftentimes it is hard to understand why something is the way it is unless you understand its history. To start with, I want to present a quick overview of the history of web infrastructure hosting to give you a better feel for what sorts of problems cloud native development solves. The Old Way Way back in the early days of the Internet, web applications were hosted on specific server machines. That is, when you wanted to host a web application, you had to purchase a physical machine, install Linux or some other operating system on it, and then pay an Internet Service Provider to put your machine on their network. This process was both time-consuming and expensive, often costing hundreds…

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Software computer programming code

First Steps to Serverless on AWS: A How-To Guide

A step-by-step tutorial on how to build and deploy a simple serverless web application on AWS

In a previous article, we talked about what serverless applications are and how they work. In this article, we will build and deploy a simple serverless web application on AWS (AWS is the cloud computing platform created by Amazon). For this application, I will assume that you have an AWS account already set up (if not, start here). While AWS has an enormous number of tools available for developers, we will focus on two: Lambda and API Gateway. Lambda is the general serverless function-invocation system on AWS. Essentially, everything that happens in AWS, whether it is a file upload, a video transcoding job, or an HTTP request, can be enabled to trigger a function defined in Lambda for further processing. Lambda functions…

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Serverless Computing: What Is It?

A serverless system makes for a more convenient and efficient experience

A new trend in cloud programming these days is known as “serverless” programming. This term is a bit confusing, because it does not mean that your code isn’t running on a server. What it does mean is that you don’t have to manage the server(s). The Physical Server In the early days of the Internet, nearly all communication was directly between the “client” (the person using a web browser or other application) and the “server” (the physical device you were communicating with). Of course, there is a limit to the number of connections that a single physical machine can process. Early on, several mechanisms were developed that allowed companies to grow their services beyond what a single machine could handle,…

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Programming source code abstract background

NoSQL Databases are the Problem, Not the Solution

NoSQL means that you will be continually rewriting your code

It’s amazing how much we forget about our own history. Many people think that NoSQL databases are the “next big thing” in technology, and that we should write all of our core applications using them. However, NoSQL databases actually predate relational databases, and common relational databases were established to solve the problems that NoSQL brings. What are the advantages of NoSQL databases? There are essentially two — they are fast, fast, fast, and they can scale, scale, scale. This much is true. However, if you aren’t building the next Facebook, you probably don’t need that much speed and scale. The fact is, this much speed and scale comes at a cost, and, even in the 1970s, with the limited computers…

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Beautiful woman undecided which man to choose

New: AI Learns to Simulate Common Sense

It is a simulation because the AI can perform the task but does not “understand” what the concepts mean

Paul Allen, a co-founder of Microsoft, was concerned AI had no common sense. In early 2018, Allen said “AI still lacks what most 10-year-olds possess: ordinary common sense.” He continued, “If we want AI to approach human abilities and have the broadest possible impact in research, medicine and business, we need to fundamentally advance AI’s common sense abilities.” Billionaire Allen coughed up $125 million and founded the Allen Institute for Artificial Intelligence in Seattle. I believed that AI would never simulate common sense but always left the door open. Unlike understanding, creativity and sentience, common sense could possibly be computable. There was no indication that common sense was non-algorithmic. And now AI has simulated common sense. The classic test for…

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Programmer

The Pareto Tradeoff — Choosing the Best of a Mixed Lot

Navigating the knowns and the unknowns, computer engineers must choose between levels of cost and risk against a background with some uncertainty

In the first part of podcast Episode 161, “Bad news for artificial general intelligence”, Robert J. Marks and colleagues Justin Bui and Sam Haug from his research group at Baylor University looked at a fundamental reality of complex systems: Complexity adds but its problems multiply. More advanced AI would be faster but capable of bigger and more complex goofs. That leads to the world of knowns and unknowns and the Pareto tradeoffs that enable us to make decisions about artificial intelligence. So now Dr. Marks begins by asking about the late Donald Rumsfeld‘s notion of the knowns and unknowns: https://episodes.castos.com/mindmatters/34ccf6d5-16b1-4de8-8a69-9737d78ba4b4-Mind-Matters-Episode-161-Haug-and-Bui-Episode-3-rev1.mp3 This portion begins at 15:15 min. A partial transcript and notes, Show Notes, and Additional Resources follow. Sam Haug: This…

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High Angle View Of Railroad Tracks

Iron Law of Complexity: Complexity Adds But Its Problems Multiply

That’s why more complexity doesn’t mean more things will go right; without planning, it means the exact opposite. The math is scary

In “Bad news for artificial general intelligence” (podcast Episode 160), Justin Bui and Sam Haug from Robert J. Marks’s research group at Baylor University joined him for a look at how AI can go wrong — whether it’s an inconsequential hot weather story or imminent nuclear doom. Now, in Episode 161, they start by unpacking the significance of an ominous fact: When we increase complexity by adding things, we multiply the chances of things going wrong. Never mind getting an advanced machine to solve all our problems; it can’t solve its own: A partial transcript and notes, Show Notes, and Additional Resources follow. Robert J. Marks: I recently vetoed a family member’s suggestion that we put a lock on our…

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iot smart automotive Driverless car with artificial intelligence combine with deep learning technology. self driving car can situational awareness around the car, letting it navigate itself 360 degree

When AI Fails, the Results Are Sometimes Amusing. Sometimes Not.

Robert J. Marks, Justin Bui, and Samuel Haug examine five instances where AI went wrong, sometimes on the world stage

Even if artificial general intelligence (AGI) could be achieved, a problem looms: The more complex a system is, the more can go wrong. If a computer could really match human thinking, a great deal could go wrong. In “When AI goes wrong” (podcast 160), Walter Bradley Center director Robert J. Marks is joined once again by members of his research group, Justin Bui and Samuel Haug, who is a PhD student in computer and electrical engineering. The topic is, what happens if AI starts behaving in bizarre and unpredictable ways? https://episodes.castos.com/mindmatters/f5d26d44-cb33-4736-bc75-f95bd8f3ae5f-Mind-Matters-Episode-160-Haug-and-Bui-Episode-2-rev1.mp3 A partial transcript and notes, Show Notes, and Additional Resources follow. Robert J. Marks: Okay. I want to start out with Paul Harvey’s The Rest of the Story. Either…

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Young african male programmer writing program code sitting at the workplace with three monitors in the office. Image focused on the screen

Have a Software Design Idea? Kaggle Could Help It Happen for Free

Okay, not exactly. You have to do the work. But maybe you don’t have to invent the software

In a recent Mind Matters podcast, “Artificial General Intelligence: the Modern Homunculus,” Walter Bradley Center director Robert J. Marks, a computer engineering prof, spoke with Justin Bui from his own research group at Baylor University in Texas about what’s happening — and isn’t happening — in artificial intelligence today. The big story turned out to be all the free software you can use to advance your own projects. This time out, Dr. Bui focuses on what open source (free) Kaggle software can do for you, including competitons. Call it science non-fiction, if you like… https://episodes.castos.com/mindmatters/d4505b4a-de80-40ae-a56c-2636563f3453-Mind-Matters-Episode-159-Justin-Bui-Episode-1-rev1.mp3 This portion begins at 12:58 min. A partial transcript and notes, Show Notes, and Additional Resources follow. Justin Bui: Kaggle is owned by Google; I…

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Bright light Developer programming and coding technology. Website design Safety of tahe social world Cyberspace concept.

Jonathan Bartlett: An Interview With the Author

"Learn to Program with Assembly" teaches programmers the language needed for a better understanding of their computer

“Learning assembly language is about learning how the processor itself thinks about your code. It is about gaining the mind of the machine.” Jonathan Bartlett, Learn to Program with Assembly: Foundational Learning for New Programmers, p. 1 Jonathan Bartlett is a man of many talents: an engineer, a software developer, a mathematician, a researcher and writer. He has been a faithful contributor here at Mind Matters News for many years, on topics ranging from programming and coding to math to education to technology. His books have become required reading at Princeton and DeVry Universities. Now, he has written a new book, Learn to Program with Assembly: Foundational Learning for New Programmers, and he sat down with Mind Matters to talk…

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Judge's gavel on table in office

Rittenhouse Trial: Are Attorneys and Judge Tech/Math-Challenged?

Does simple pinch and zoom change pixels? The devil, though, is in the details

In one of the many exchanges between lawyers and Judge Schroeder in the Kyle Rittenhouse trial, the degree to which pinching and zooming change cell phone images was addressed. Rittenhouse lawyer Mark Richards claimed it does. The district attorney Thomas Binger claimed there is no change. Richards first claimed that an image prepared by the prosecutor changed pixels using AI and logarithms. If AI is defined as any “gee whiz” technology, he was right. But pinch and zoom was invented in 2007 by Steve Jobs and uses nothing that can be considered modern AI. All nerds should laugh at the claim that “logarithms”  were used in the pinch and zoom.  Attorney Mark Richards obviously meant “algorithms”  To his credit, Richards confessed he knew…