Metcalfe’s Law of IT growth begins with the fact that one fax machine — for example — is useless. Two help a bit but millions of them made a difference.
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Mead never saw technology research as a left-brained thing; for him, he says, it is a matter of love. It only sounds simple afterward.
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The “strange loop” of life — a loop with no apparent beginning in non-life — was, Robert Rosen concluded, beyond the reach of computing.
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Developers don’t just write software; they must understand the whole picture of how it will be used both now and down the road.
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Programming practice has gone through several evolutions in its lifespan. The first phase might be considered the “exploratory” phase, where there were no rules but a lot of imagination. People wrote code that was simultaneously amazing and terrible—amazing at what people got their slow computers to do, but terrible in that no one but the author would ever be able to maintain the programs. The lessons learned from the exploratory phase led to what is known as “structured” programming. The goal of structured programming was to be able to write programs that someone else had a chance of reading and understanding. Structured programming favored having really well-documented inputs and outputs to every function, very clear entry and exit points to each function, and Read More ›
Academic publisher Taylor & Francis asks in TechXplore, “Should robots be given a conscience?” (June 11, 2023). I spoil no surprise by revealing that we are meant to think that that is both doable and desirable. T & F is publishing Eve Poole’s Robot Souls later this year. Poole is a British writer and academic, and author of Capitalism’s Toxic Assumptions, Buying God, and Leadersmithing. Her thesis is that, in our quest for the most functional software, we left out the “junk,” which includes our “emotions, free will and a sense of purpose”: Our junk code consists of human emotions, our propensity for mistakes, our inclination to tell stories, our uncanny sixth sense, our capacity to cope with uncertainty, an Read More ›
ChatGPT is a direct descendent of GPT-3, and is a fancy form of a fancy machine learning algorithm called a neural network. For an overview of all of ChatGPT’s neural network complexity, here is a fun article. However, all that is beside the point. The important thing about a neural network: It can only generate what is in its training data. Therefore, ChatGPT can only produce what is in its training data. ChatGPT’s training data does not include the conversation you or I are having with ChatGPT. Therefore, if something novel occurs in the conversation, ChatGPT cannot reproduce it. That is, if ChatGPT is a neural network. Conversely, if ChatGPT reproduces novel text from the conversation, then ipso facto ChatGPT is not a Read More ›
At Medium late last year, a programmer/researcher who writes under the name “Rebel Science,” assessed Deep Learning, a favorite of the self-driving car quest, as “useless” because it can’t generalize: The biggest problem with DL is its inherent inability to effectively generalize. Without generalization, edge cases are an insurmountable problem, something that the autonomous vehicle industry found out the hard way after wasting more than $100 billion by betting on DL. Rebel Science, “Deep Learning Is Not Just Inadequate for Solving AGI, It Is Useless” at Medium (Nov 2, 2022) Displaying for readers a picture of a bicycle, he continues, A deep neural network cannot perceive this bicycle unless it has been previously trained to recognize it. Generalization is the Read More ›
Santa Fe Institute professor of complexity Melanie Mitchell takes issue — in a gentle way — with those who warn about the dangers of superintelligent machines (AI alignment) destroying us all: In one scenario, for example, Oxford Future of Humanity Institute’s Nick Bostrom developed a scenario by which a super AI, told to make paper clips, might use up the world’s resources in doing so. Her comment: To many outside these specific communities, AI alignment looks something like a religion — one with revered leaders, unquestioned doctrine and devoted disciples fighting a potentially all-powerful enemy (unaligned superintelligent AI). Indeed, the computer scientist and blogger Scott Aaronson recently noted that there are now “Orthodox” and “Reform” branches of the AI alignment Read More ›
OpenAI, recently released a new AI program called ChatGPT. It left the internet gobsmacked, though some were skeptical, and concerned about its abilities. Particularly about ChatGPT writing students’ homework for them! [ChatGPT] also appears to be ominously good at answering the types of open-ended analytical questions that frequently appear on school assignments. (Many educators have predicted that ChatGPT, and tools like it, will spell the end of homework and take-home exams.) Kevin Roose, “The Brilliance and Weirdness of ChatGPT” at New York Times (December 5, 2022) The really amazing thing is ChatGPT’s humanlike responses. They gives an observer an unnerving suspicion that the AI is actually sentient. Maybe it is actually sentient. Wait, what? You heard me. The AI is Read More ›
Jonathan Bartlett, author of the well-received Calculus from the Ground Up (2018), has a new book out, Programming for Absolute Beginners: Using JavaScript. As he told Mind Matters News, the book is aimed at those who want to get started in programming, “whether that’s someone switching careers, an introductory college course, or a high school student.” Or just someone who needs to interact with programmers, perhaps in the workplace. Mind Matters News: You mention that, for those who want to learn programming today, the situation has changed, compared with earlier years. How has it changed? Jonathan Bartlett: I grew up around computers. I’ve been programming computers since the 1980s, and have been around the development scene for a long time. Read More ›
In an open-access paper last year at the Journal of Artificial Intelligence Research, a research group concluded that a computer superintelligence, if developed, could not be contained. It would be a HAL 9000 that couldn’t just be turned off. Science writer David Nield explains: The catch is that controlling a super-intelligence far beyond human comprehension would require a simulation of that super-intelligence which we can analyze (and control). But if we’re unable to comprehend it, it’s impossible to create such a simulation. Rules such as ‘cause no harm to humans’ can’t be set if we don’t understand the kind of scenarios that an AI is going to come up with, suggest the authors of the new paper. Once a computer Read More ›
In a previous article, I discussed the semiconductor industry and Taiwan’s supremacy in manufacturing microchips, the foundry portion of the semiconductor supply chain. Now let’s look at the U.S. perspective on the semiconductor industry and its relationship to Taiwan. In order to do that, we have to talk about the CHIPS+ Act Congress passed a bipartisan bill, the CHIPS and Science Act in July, after a year of negotiations in committee. President Biden signed the act into law on August 9 and the CHIPS Act Implementation Strategy was launched on September 6 through an executive order. CHIPS, or “Creating Helpful Incentives to Produce Semiconductors,” is a $250B initiative that incentivizes businesses to bring semiconductor manufacturing, research and innovation back to Read More ›
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, Read More ›
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 Read More ›
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 Read More ›
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. Read More ›
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 Read More ›
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 Read More ›
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 Read More ›