Podcasts about computer power

Join the GOLDEN BENCH CLUB! All you have to do is leave us a 5-star review and comment on the Apple Podcast app (or any other app and email us a screen shot) and we will read your review on the podcast and welcome you to the Golden Bench Club. This super elite club is only for the best of the best. We spend a lot of time in our lab doing repetitive tasks that let's all agree, no one really enjoys doing. File organization, nesting, adding pins and supports... the list goes on. Kris Wouters has a long history in the 3D printing industry. After joining OQTON and working on automation strategies, Kris and the rest of the dental division started their own company to focus on the dental lab industry. They started OQCAM (https://oqcam.com/) to help labs streamline and simplify their digital workflow. Kris talks about his history, the history of the company, some great examples on how OQCAM can work in a lab, and how it's scalable to work with labs of all sizes. Introducing Ivotion Digital Dentures (https://www.ivoclar.com/en_us/products/digital-processes/ivotion) from Ivoclar (https://www.ivoclar.com/en_us) – Experience unparalleled precision and efficiency with Ivoclar‘s state-of-the-art digital denture workflow. Ivotion is available in their patent pending monolithic disc that combines denture base and tooth materials in one seamless puck. Or if you lab needs more flexibility, Ivotion is also available as stand-alone discs - Ivotion Base, Dent and Dent Multi all in 98mm width to fit your favorite milling machine. With Ivotion you can streamline your lab's processes, reduce production time, and enhance patient satisfaction. Elevate your lab's capabilities with Ivotion Digital Dentures – where innovation meets perfection. Discover the future of dentures today with Ivoclar." Thanks for your continued support of the podcast Ivoclar. Special Guest: Kris Wouters.

In which we are joined by Ezri of Swampside Chats, to continue our discussion of "Computer Power and Human Reason: From Judgement to Calculation" by Joseph Weizenbaum. In this episode we cover the third an fourth chapters of the book. Computer Power and Human Reason: From Judgment to Calculation (1976) by Joseph Weizenbaum displays the author's ambivalence towards computer technology and lays out the case that while artificial intelligence may be possible, we should never allow computers to make important decisions because computers will always lack human qualities such as compassion and wisdom. Weizenbaum makes the crucial distinction between deciding and choosing. Deciding is a computational activity, something that can ultimately be programmed. It is the capacity to choose that ultimately makes one a human being. Choice, however, is the product of judgment, not calculation. Comprehensive human judgment is able to include non-mathematical factors such as emotions. Judgment can compare apples and oranges, and can do so without quantifying each fruit type and then reductively quantifying each to factors necessary for mathematical comparison. If you like the show, consider supporting us on Patreon. Links: Computer Power and Human Reason on Wikipedia

In which we are joined by Ezri of Swampside Chats, to continue our discussion of "Computer Power and Human Reason: From Judgement to Calculation" by Joseph Weizenbaum. In this episode we cover the second chapter of the book. Computer Power and Human Reason: From Judgment to Calculation (1976) by Joseph Weizenbaum displays the author's ambivalence towards computer technology and lays out the case that while artificial intelligence may be possible, we should never allow computers to make important decisions because computers will always lack human qualities such as compassion and wisdom. Weizenbaum makes the crucial distinction between deciding and choosing. Deciding is a computational activity, something that can ultimately be programmed. It is the capacity to choose that ultimately makes one a human being. Choice, however, is the product of judgment, not calculation. Comprehensive human judgment is able to include non-mathematical factors such as emotions. Judgment can compare apples and oranges, and can do so without quantifying each fruit type and then reductively quantifying each to factors necessary for mathematical comparison. If you like the show, consider supporting us on Patreon. Links: Computer Power and Human Reason on Wikipedia Weizenbaum's Nightmares, on The Guardian Inside the Very Human Origin of the Term “Artificial Intelligence” General Intellect Unit on iTunes http://generalintellectunit.net Support the show on Patreon https://twitter.com/giunitpod General Intellect Unit on Facebook General Intellect Unit on archive.org Emancipation Network

In which we are joined by Ezri of Swampside Chats, to continue our discussion of "Computer Power and Human Reason: From Judgement to Calculation" by Joseph Weizenbaum. In this episode we cover the first chapter of the book. Computer Power and Human Reason: From Judgment to Calculation (1976) by Joseph Weizenbaum displays the author's ambivalence towards computer technology and lays out the case that while artificial intelligence may be possible, we should never allow computers to make important decisions because computers will always lack human qualities such as compassion and wisdom. Weizenbaum makes the crucial distinction between deciding and choosing. Deciding is a computational activity, something that can ultimately be programmed. It is the capacity to choose that ultimately makes one a human being. Choice, however, is the product of judgment, not calculation. Comprehensive human judgment is able to include non-mathematical factors such as emotions. Judgment can compare apples and oranges, and can do so without quantifying each fruit type and then reductively quantifying each to factors necessary for mathematical comparison. If you like the show, consider supporting us on Patreon. Links: Computer Power and Human Reason on Wikipedia Weizenbaum's Nightmares, on The Guardian Inside the Very Human Origin of the Term “Artificial Intelligence” General Intellect Unit on iTunes http://generalintellectunit.net Support the show on Patreon https://twitter.com/giunitpod General Intellect Unit on Facebook General Intellect Unit on archive.org Emancipation Network

In which we are joined by Ezri of Swampside Chats, to continue our discussion of "Computer Power and Human Reason: From Judgement to Calculation" by Joseph Weizenbaum. In this episode we cover the prefaces, introduction, and chapter one. Computer Power and Human Reason: From Judgment to Calculation (1976) by Joseph Weizenbaum displays the author's ambivalence towards computer technology and lays out the case that while artificial intelligence may be possible, we should never allow computers to make important decisions because computers will always lack human qualities such as compassion and wisdom. Weizenbaum makes the crucial distinction between deciding and choosing. Deciding is a computational activity, something that can ultimately be programmed. It is the capacity to choose that ultimately makes one a human being. Choice, however, is the product of judgment, not calculation. Comprehensive human judgment is able to include non-mathematical factors such as emotions. Judgment can compare apples and oranges, and can do so without quantifying each fruit type and then reductively quantifying each to factors necessary for mathematical comparison. If you like the show, consider supporting us on Patreon. Links: Computer Power and Human Reason on Wikipedia Weizenbaum's Nightmares, on The Guardian Inside the Very Human Origin of the Term “Artificial Intelligence” General Intellect Unit on iTunes http://generalintellectunit.net Support the show on Patreon https://twitter.com/giunitpod General Intellect Unit on Facebook General Intellect Unit on archive.org Emancipation Network

In which we are joined by Ezri of Swampside Chats, to continue our discussion of "Computer Power and Human Reason: From Judgement to Calculation" by Joseph Weizenbaum. Computer Power and Human Reason: From Judgment to Calculation (1976) by Joseph Weizenbaum displays the author's ambivalence towards computer technology and lays out the case that while artificial intelligence may be possible, we should never allow computers to make important decisions because computers will always lack human qualities such as compassion and wisdom. Weizenbaum makes the crucial distinction between deciding and choosing. Deciding is a computational activity, something that can ultimately be programmed. It is the capacity to choose that ultimately makes one a human being. Choice, however, is the product of judgment, not calculation. Comprehensive human judgment is able to include non-mathematical factors such as emotions. Judgment can compare apples and oranges, and can do so without quantifying each fruit type and then reductively quantifying each to factors necessary for mathematical comparison. If you like the show, consider supporting us on Patreon. Links: Computer Power and Human Reason on Wikipedia Weizenbaum's Nightmares, on The Guardian Inside the Very Human Origin of the Term “Artificial Intelligence” General Intellect Unit on iTunes http://generalintellectunit.net Support the show on Patreon https://twitter.com/giunitpod General Intellect Unit on Facebook General Intellect Unit on archive.org Emancipation Network

In which we are joined by Ezri of Swampside Chats, to begin a series on "Computer Power and Human Reason: From Judgement to Calculation" by Joseph Weizenbaum. Computer Power and Human Reason: From Judgment to Calculation (1976) by Joseph Weizenbaum displays the author's ambivalence towards computer technology and lays out the case that while artificial intelligence may be possible, we should never allow computers to make important decisions because computers will always lack human qualities such as compassion and wisdom. Weizenbaum makes the crucial distinction between deciding and choosing. Deciding is a computational activity, something that can ultimately be programmed. It is the capacity to choose that ultimately makes one a human being. Choice, however, is the product of judgment, not calculation. Comprehensive human judgment is able to include non-mathematical factors such as emotions. Judgment can compare apples and oranges, and can do so without quantifying each fruit type and then reductively quantifying each to factors necessary for mathematical comparison. If you like the show, consider supporting us on Patreon. Links: Computer Power and Human Reason on Wikipedia Weizenbaum's Nightmares, on The Guardian Inside the Very Human Origin of the Term “Artificial Intelligence” General Intellect Unit on iTunes http://generalintellectunit.net Support the show on Patreon https://twitter.com/giunitpod General Intellect Unit on Facebook General Intellect Unit on archive.org Emancipation Network

Einstein teria dito que o budismo é a religião do futuro. Será mesmo que ele disse isso? E se disse, será que o budismo a que ele tinha acesso podia ser entendido além de um viés colonialista? Além disto, o que ele pensava realmente sobre ciência e religião é compatível mesmo com o budismo? O que o hype com a inteligência artificial tem a ver com tudo isso? Este podcast também está disponível em formato de vídeo em  https://tzal.org/ia-einstein-e-o-budismo/ ◦ Outros conteúdos sobre ciência e budismo https://tzal.org/budismo-e-ciencia/ ◦ Budismo e mistificação quântica (texto no Buda Virtual) https://www.budavirtual.com.br/budismo-e-mistificacao-quantica/ ◦ As premissas injustificadas da ciência (texto no Papo de Homem) https://papodehomem.com.br/as-premissas-injustificadas-da-ciencia-wtf-44/ ◦ A crença infundada numa realidade externa (texto no Buda Virtual) https://www.budavirtual.com.br/a-crenca-infundada-em-uma-realidade-externa-padma-dorje/ ◦ Outros conteúdos sobre materialismo https://tzal.org/materialismo/ ◦ Interpretações da mecânica quântica (artigo da wikipedia em inglês mencionado no texto) https://en.wikipedia.org/wiki/Interpretations_of_quantum_mechanics ◦ O livro de Joseph Weizenbaum, criador do ELIZA, um chatbot primitivo que imitava um terapeuta rogeriano, pode ser encontrado em inglês na amazon.com.br https://www.amazon.com.br/dp/0716704633&tag=tzal-20. Há também um artigo sobre o livro na wikipedia em inglês https://en.m.wikipedia.org/wiki/Computer_Power_and_Human_Reason. ◦ Dois livros de Donald S. Lopez Jr., que costuma tratar de questões de distorção e colonialismo no budismo, estes sendo em particular sobre as ideias colonialistas em torno de ciência e budismo: Buddhism & Science: A Guide for the Perplexed https://www.amazon.com.br/dp/0226493199&tag=tzal-20 e The Scientific Buddha: His Short and Happy Life https://www.amazon.com.br/dp/0300159129&tag=tzal-20. Para receber informações sobre a produção de Padma Dorje:  https://tzal.org/boletim-informativo/ Por favor ajude esse canal:  https://tzal.org/patronagem/ Lista completa de conteúdos no canal tendrel, com descrição:  https://tzal.org/tendrel-lista-completa-de-videos/ Centros de darma que recomendohttps://tzal.org/centros-de-darma-que-recomendo/ Para me ajudar comprando na amazonhttps://tzal.org/amazon Contribuições e perguntas podem ser feitas por email, que também funciona como chave PIX (conexoesauspiciosas@gmail.com)

Carlota Perez is a researcher who has studied hype cycles for much of her career. She's affiliated with the University College London, the University of Sussex, The Tallinn University of Technology in Astonia and has worked with some influential organizations around technology and innovation. As a neo-Schumpeterian, she sees technology as a cornerstone of innovation. Her book Technological Revolutions and Financial Capital is a must-read for anyone who works in an industry that includes any of those four words, including revolutionaries.  Connecticut-based Gartner Research was founded by GideonGartner in 1979. He emigrated to the United States from Tel Aviv at three years old in 1938 and graduated in the 1956 class from MIT, where he got his Master's at the Sloan School of Management. He went on to work at the software company System Development Corporation (SDC), the US military defense industry, and IBM over the next 13 years before starting his first company. After that failed, he moved into analysis work and quickly became known as a top mind in the technology industry analysts. He often bucked the trends to pick winners and made banks, funds, and investors lots of money. He was able to parlay that into founding the Gartner Group in 1979.  Gartner hired senior people in different industry segments to aid in competitive intelligence, industry research, and of course, to help Wall Street. They wrote reports on industries, dove deeply into new technologies, and got to understand what we now call hype cycles in the ensuing decades. They now boast a few billion dollars in revenue per year and serve well over 10,000 customers in more than 100 countries.  Gartner has developed a number of tools to make it easier to take in the types of analysis they create. One is a Magic Quadrant, reports that identify leaders in categories of companies by a vision (or a completeness of vision to be more specific) and the ability to execute, which includes things like go-to-market activities, support, etc. They lump companies into a standard four-box as Leaders, Challengers, Visionaries, and Niche Players. There's certainly an observer effect and those they put in the top right of their four box often enjoy added growth as companies want to be with the most visionary and best when picking a tool. Another of Gartner's graphical design patterns to display technology advances is what they call the “hype cycle”. The hype cycle simplifies research from career academics like Perez into five phases.  * The first is the technology trigger, which is when a breakthrough is found and PoCs, or proof-of-concepts begin to emerge in the world that get press interested in the new technology. Sometimes the new technology isn't even usable, but shows promise.  * The second is the Peak of Inflated Expectations, when the press picks up the story and companies are born, capital invested, and a large number of projects around the new techology fail. * The third is the Trough of Disillusionment, where interest falls off after those failures. Some companies suceeded and can show real productivity, and they continue to get investment. * The fourth is the Slope of Enlightenment, where the go-to-market activities of the surviving companies (or even a new generation) begin to have real productivity gains. Every company or IT department now runs a pilot and expectations are lower, but now achievable. * The fifth is the Plateau of Productivity, when those pilots become deployments and purchase orders. The mainstream industries embrace the new technology and case studies prove the promised productivity increases. Provided there's enough market, companies now find success. There are issues with the hype cycle. Not all technologies will follow the cycle. The Gartner approach focuses on financials and productivity rather than true adoption. It involves a lot of guesswork around subjective, synthetical, and often unsystematic research. There's also the ever-resent observer effect. However, more often than not, the hype is seperated from the tech that can give organizations (and sometimes all of humanity) real productivity gains. Further, the term cycle denotes a series of events when it should in fact be cyclical as out of the end of the fifth phase a new cycle is born, or even a set of cycles if industries grow enough to diverge. ChatGPT is all over the news feeds these days, igniting yet another cycle in the cycles of AI hype that have been prevalent since the 1950s. The concept of computer intelligence dates back to the 1942 with Alan Turing and Isaac Asimov with “Runaround” where the three laws of robotics initially emerged from. By 1952 computers could play themselves in checkers and by 1955, Arthur Samuel had written a heuristic learning algorthm he called “temporal-difference learning” to play Chess. Academics around the world worked on similar projects and by 1956 John McCarthy introduced the term “artificial intelligence” when he gathered some of the top minds in the field together for the McCarthy workshop. They tinkered and a generation of researchers began to join them. By 1964, Joseph Weizenbaum's "ELIZA" debuted. ELIZA was a computer program that used early forms of natural language processing to run what they called a “DOCTOR” script that acted as a psychotherapist.  ELIZA was one of a few technologies that triggered the media to pick up AI in the second stage of the hype cycle. Others came into the industry and expectations soared, now predictably followed by dilsillusionment. Weizenbaum wrote a book called Computer Power and Human Reason: From Judgment to Calculation in 1976, in response to the critiques and some of the early successes were able to then go to wider markets as the fourth phase of the hype cycle began. ELIZA was seen by people who worked on similar software, including some games, for Apple, Atari, and Commodore.  Still, in the aftermath of ELIZA, the machine translation movement in AI had failed in the eyes of those who funded the attempts because going further required more than some fancy case statements. Another similar movement called connectionism, or mostly node-based artificial neural networks is widely seen as the impetus to deep learning. David Hunter Hubel and Torsten Nils Wiesel focused on the idea of convultional neural networks in human vision, which culminated in a 1968 paper called  "Receptive fields and functional architecture of monkey striate cortex.” That built on the original deep learning paper from Frank Rosenblatt of Cornell University called "Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms" in 1962 and work done behind the iron curtain by Alexey Ivakhnenko on learning algorithms in 1967. After early successes, though, connectionism - which when paired with machine learning would be called deep learning when Rina Dechter coined the term in 1986, went through a similar trough of disillusionment that kicked off in 1970. Funding for these projects shot up after the early successes and petered out ofter there wasn't much to show for them. Some had so much promise that former presidents can be seen in old photographs going through the models with the statiticians who were moving into computing. But organizations like DARPA would pull back funding, as seen with their speech recognition projects with Cargegie Mellon University in the early 1970s.  These hype cycles weren't just seen in the United States. The British applied mathemetician James Lighthill wrote a report for the British Science Research Council, which was published in 1973. The paper was called “Artificial Intelligence: A General Survey” and analyzed the progress made based on the amount of money spent on artificial intelligence programs. He found none of the research had resulted in any “major impact” in fields that the academics had undertaken. Much of the work had been done at the University of Edinbourgh and funding was drastically cut, based on his findings, for AI research around the UK. Turing, Von Neumann, McCarthy, and others had either intentially or not, set an expectation that became a check the academic research community just couldn't cash. For example, the New York Times claimed Rosenblatt's perceptron would let the US Navy build computers that could “walk, talk, see, write, reproduce itself, and be conscious of its existence” in the 1950s - a goal not likely to be achieved in the near future even seventy years later. Funding was cut in the US, the UK, and even in the USSR, or Union of the Soviet Socialist Republic. Yet many persisted. Languages like Lisp had become common in the late 1970s, after engineers like Richard Greenblatt helped to make McCarthy's ideas for computer languages a reality. The MIT AI Lab developed a Lisp Machine Project and as AI work was picked up at other schools like Stanford began to look for ways to buy commercially built computers ideal to be Lisp Machines. After the post-war spending, the idea that AI could become a more commercial endeavor was attractive to many. But after plenty of hype, the Lisp machine market never materialized. The next hype cycle had begun in 1983 when the US Department of Defense pumped a billion dollars into AI, but that spending was cancelled in 1987, just after the collapse of the Lisp machine market. Another AI winter was about to begin. Another trend that began in the 1950s but picked up steam in the 1980s was expert systems. These attempt to emulate the ways that humans make decisions. Some of this work came out of the Stanford Heuristic Programming Project, pioneered by Edward Feigenbaum. Some commercial companies took the mantle and after running into barriers with CPUs, by the 1980s those got fast enough. There were inflated expectations after great papers like Richard Karp's “Reducibility among Combinatorial Problems” out of UC Berkeley in 1972. Countries like Japan dumped hundreds of millions of dollars (or yen) into projects like “Fifth Generation Computer Systems” in 1982, a 10 year project to build up massively parallel computing systems. IBM spent around the same amount on their own projects. However, while these types of projects helped to improve computing, they didn't live up to the expectations and by the early 1990s funding was cut following commercial failures. By the mid-2000s, some of the researchers in AI began to use new terms, after generations of artificial intelligence projects led to subsequent AI winters. Yet research continued on, with varying degrees of funding. Organizations like DARPA began to use challenges rather than funding large projects in some cases. Over time, successes were found yet again. Google Translate, Google Image Search, IBM's Watson, AWS options for AI/ML, home voice assistants, and various machine learning projects in the open source world led to the start of yet another AI spring in the early 2010s. New chips have built-in machine learning cores and programming languages have frameworks and new technologies like Jupyter notebooks to help organize and train data sets. By 2006, academic works and open source projects had hit a turning point, this time quietly. The Association of Computer Linguistics was founded in 1962, initially as the Association for Machine Translation and Computational Linguistics (AMTCL). As with the ACM, they have a number of special interest groups that include natural language learning, machine translation, typology, natural language generation, and the list goes on. The 2006 proceedings on the Workshop of Statistical Machine Translation began a series of dozens of workshops attended by hundreds of papers and presenters. The academic work was then able to be consumed by all, inlcuding contributions to achieve English-to-German and Frnech tasks from 2014. Deep learning models spread and become more accessible - democratic if you will. RNNs, CNNs, DNNs, GANs.  Training data sets was still one of the most human intensive and slow aspects of machine learning. GANs, or Generative Adversarial Networks were one of those machine learning frameworks, initially designed by Ian Goodfellow and others in 2014. GANs use zero-sum game techniques from game theory to generate new data sets - a genrative model. This allowed for more unsupervised training of data. Now it was possible to get further, faster with AI.  This brings us into the current hype cycle. ChatGPT was launched in November of 2022 by OpenAI. OpenAI was founded as a non-profit in 2015 by Sam Altman (former cofounder of location-based social network app Loopt and former president of Y Combinator) and a cast of veritable all-stars in the startup world that included:  * Reid Hoffman, former Paypal COO, LinkedIn founder and venture capitalist. * Peter Thiel, former cofounder of Paypal and Palantir, as well as one of the top investors in Silicon Valley. * Jessica Livingston, founding partner at Y Combinator. * Greg Brockman, an AI researcher who had worked on projects at MIT and Harvard OpenAI spent the next few years as a non-profit and worked on GPT, or Generative Pre-trained Transformer autoregression models. GPT uses deep learning models to process human text and produce text that's more human than previous models. Not only is it capable of natural language processing but the generative pre-training of models has allowed it to take a lot of unlabeled text so people don't have to hand label weights, thus automated fine tuning of results. OpenAI dumped millions into public betas by 2016 and were ready to build products to take to market by 2019. That's when they switched from a non-profit to a for-profit. Microsoft pumped $1 billion into the company and they released DALL-E to produce generative images, which helped lead to a new generation of applications that could produce artwork on the fly. Then they released ChatGPT towards the end of 2022, which led to more media coverage and prognostication of world-changing technological breakthrough than most other hype cycles for any industry in recent memory. This, with GPT-4 to be released later in 2023. ChatGPT is most interesting through the lens of the hype cycle. There have been plenty of peaks and plateaus and valleys in artificial intelligence over the last 7+ decades. Most have been hyped up in the hallowed halls of academia and defense research. ChatGPT has hit mainstream media. The AI winter following each seems to be based on the reach of audience and depth of expectations. Science fiction continues to conflate expectations. Early prototypes that make it seem as though science fiction will be in our hands in a matter of weeks lead media to conjecture. The reckoning could be substantial. Meanwhile, projects like TinyML - with smaller potential impacts for each use but wider use cases, could become the real benefit to humanity beyond research, when it comes to everyday productivity gains. The moral of this story is as old as time. Control expectations. Undersell and overdeliver. That doesn't lead to massive valuations pumped up by hype cycles. Many CEOs and CFOs know that a jump in profits doesn't always mean the increase will continue. Some intentially slow expectations in their quarterly reports and calls with analysts. Those are the smart ones.

Nicholas P. Sullivan is my guest on Episode 158 of Inside Ideas with Marc Buckley. Nicholas is a writer and editor focusing on the impact of business and technology on international development. The Blue Revolution is his fourth book. It follows Money, Real Quick: Kenya's Disruptive Mobile Money Innovation; You Can Hear Me Now: How Microloans and Cell Phones Are Connecting the World's Poor to the Global Economy; and Computer Power for Your Small Business. He has been codirector of The Fletcher School's Leadership Program for Financial Inclusion (Tufts University), a consultant to central banks in developing countries, and a visiting scholar at MIT's Legatum Center for International Development. In the publishing world, he was publisher of Innovations: Technology/Governance/Globalization (MIT Press); editor-in-chief of Inc.com; and editor-in-chief of Home Office Computing. Sullivan is currently a Senior Fellow at The Fletcher School's Council on Emerging Market Enterprises and a Senior Research Fellow at its Maritime Studies Program. Sullivan has twice been a Rockefeller Foundation Bellagio Center Resident Fellow. A graduate of Harvard University and The Fletcher School of Law and Diplomacy, he lives in Dartmouth, Massachusetts. https://islandpress.org/books/blue-revolution

Home 'n' Pod First episode of this series where I explore various different tasks and how much power they consume or need to run https://markriley.org/how-much-computer-power-do-you-actually-need-part-1/

In this week's episode of Through The TechVine Live Radio Program, Diana, Sean, and Marco welcome Philip Wylie (The Hacker Maker)as a guest on the show — together they talk about: How Are Hackers Made? | Contextualizing Technology And Art | Why Computer Power Is Never Enough | What Could Cybersecurity Learn From Plants? | Vinyl Records & Video Cassette - Remembering BlockBuster | Through The TechVine Radio Program Episode TwentyWe have officially decided to keep Through The TechVine a live recording but Radio Style. We like that mood — what do you think?Apart from that, everything else is the usual Tech and Science Topics conversations, some good laughs, and a lot of WHAT IF?! 

Tonya Hall talks to Dr. Greg Bowman, director at Folding@home, about the groundbreaking scientific research carried out with the help of thousands of PCs around the world. Learn more about your ad choices. Visit megaphone.fm/adchoices

A survey of the idea that technology is creatures.    Subscribe at: paid.retraice.com    Details: we should call them something else; high-altitude fruit; Simon—the rules are the same; Grey Walter's tortoises; Butler—war to the death; Dyson—they're *not* imaginary; Wolfram's simple programs; Yudkowsky on fire alarms; I. J. Good—take science fiction seriously; `unquestionably'; Yudkowsky—smartish stuff; S. Russell and Norvig—operating on their own; two meanings of `the singularity'; a moral challenge; S. Russell—the user's mind; Dyson—worry less about intelligence; Smallberg—energy sources and replication; a digression on search; Dietterich—reproduction with autonomy; the work; Bostrom—deferred gratification; our civilization is evidence of capacity; skyscrapers seem taller than they are. Complete notes and video at: https://www.retraice.com/segments/re8   Air date: Wednesday, 28th Oct. 2020, 3 : 30 PM Pacific/US.   Chapters:  00:00 we should call them something else; 00:35 high-altitude fruit; 02:55 Simon—the rules are the same; 04:06 Grey Walter's tortoises; 08:19 Butler—war to the death; 11:16 Dyson—they're *not* imaginary; 14:02 Wolfram's simple programs; 15:49 Yudkowsky on fire alarms; 17:14 I. J. Good—take science fiction seriously; 18:36 `unquestionably'; 19:29 Yudkowsky—smartish stuff; 23:00 S. Russell and Norvig—operating on their own; 24:55 two meanings of `the singularity'; 25:41 a moral challenge; 26:52 S. Russell—the user's mind; 28:46 Dyson—worry less about intelligence; 30:24 Smallberg—energy sources and replication; 31:13 a digression on search; 34:02 Dietterich—reproduction with autonomy; 35:55 the work; 36:46 Bostrom—deferred gratification; 39:13 our civilization is evidence of capacity; 39:52 skyscrapers seem taller than they are.   References:      Bostrom, N. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford. First published in 2014. Citations are from the pbk. edition, 2016. ISBN: 978-0198739838. Searches: https://www.amazon.com/s?k=978-0198739838 https://www.google.com/search?q=isbn+978-0198739838 https://lccn.loc.gov/2015956648      Brockman, J. (Ed.) (2015). What to Think About Machines That Think: Today’s Leading Thinkers on the Age of Machine Intelligence. Harper Perennial. ISBN: 978-0062425652. Searches: https://www.amazon.com/s?k=978-0062425652 https://www.google.com/search?q=isbn+978-0062425652 https://lccn.loc.gov/2016303054      Brockman, J. (Ed.) (2019). Possible Minds: Twenty-Five Ways of Looking at AI. Penguin. ISBN: 978-0525557999. Searches: https://www.amazon.com/s?k=978-0525557999 https://www.google.com/search?q=isbn+978-0525557999 https://lccn.loc.gov/2018032888      Butler, S. (1863). Darwin among the machines. The Press (Canterbury, New Zealand). Reprinted in Butler et al. (1923).      Butler, S., Jones, H., & Bartholomew, A. (1923). The Shrewsbury Edition of the Works of Samuel Butler Vol. 1. J. Cape. No ISBN. https://books.google.com/books?id=B-LQAAAAMAAJ Retrieved 27th Oct. 2020.      de Garis, H. (2005). The Artilect War: Cosmists vs. Terrans: A Bitter Controversy Concerning Whether Humanity Should Build Godlike Massively Intelligent Machines. ETC Publications. ISBN: 0882801546. Searches: https://www.amazon.com/s?k=0882801546 https://www.google.com/search?q=isbn+0882801546      Dietterich, T. G. (2015). How to prevent an intelligence explosion. (pp. 380–383). In Brockman (2015).      Dyson, G. (2019). The third law. (pp. 31–40). In Brockman (2019).      Dyson, G. B. (1997). Darwin Among The Machines: The Evolution Of Global Intelligence. Basic Books. ISBN: 978-0465031627. Searches: https://www.amazon.com/s?k=978-0465031627 https://www.google.com/search?q=isbn+978-0465031627 https://lccn.loc.gov/2012943208      Good, I. J. (1965). Speculations concerning the first ultraintelligent machine. Advances in Computers, 6, 31–88. https://exhibits.stanford.edu/feigenbaum/catalog/gz727rg3869 Retrieved 27th Oct. 2020.      Harris, S. (2016). Can we build AI without losing control over it? — Sam Harris. TED. https://youtu.be/8nt3edWLgIg Retrieved 28th Oct. 2020.      Holland, O. (2003). Exploration and high adventure: the legacy of Grey Walter. Phil. Trans. R. Soc. Lond. A, 361, 2085–2121. https://www.researchgate.net/publication/9025611 Retrieved 22nd Nov. 2019. See also: https://www.youtube.com/results?search_query=grey+walter+tortoise+      Jackson, R. E., & Cormack, L. K. (2008). Evolved navigation theory and the environmental vertical illusion. Evolution and Human Behavior, 29, 299–304. https://liberalarts.utexas.edu/cps/_files/cormack-pdf/12Evolved_navigation_theory2009.pdf Retrieved 29th Oct. 2020.      Kurzweil, R. (2005). The Singularity Is Near: When Humans Transcend Biology. Penguin. ISBN: 978-0143037880. Searches: https://www.amazon.com/s?k=978-0143037880 https://www.google.com/search?q=isbn+978-0143037880 https://lccn.loc.gov/2004061231      Legg, S., & Hutter, M. (2007a). A collection of definitions of intelligence. Frontiers in Artificial Intelligence and Applications, 157, 17–24. June 2007. https://arxiv.org/abs/0706.3639 Retrieved ca. 10 Mar. 2019.      Legg, S., & Hutter, M. (2007b). Universal intelligence: A definition of machine intelligence. Minds & Machines, 17(4), 391–444. December 2007. https://arxiv.org/abs/0712.3329 Retrieved ca. 10 Mar. 2019.      Retraice (2020/09/07). Re1: Three Kinds of Intelligence. retraice.com. https://www.retraice.com/segments/re1 Retrieved 22nd Sep. 2020.      Retraice (2020/09/08). Re2: Tell the People, Tell Foes. retraice.com. https://www.retraice.com/segments/re2 Retrieved 22nd Sep. 2020.      Russell, S. (2019). Human Compatible: Artificial Intelligence and the Problem of Control. Viking. ISBN: 978-0525558613. Searches: https://www.amazon.com/s?k=978-0525558613 https://www.google.com/search?q=isbn+978-0525558613 https://lccn.loc.gov/2019029688      Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson, 4th ed. ISBN: 978-0134610993. Searches: https://www.amazon.com/s?k=978-0134610993 https://www.google.com/search?q=isbn+978-0134610993 https://lccn.loc.gov/2019047498      Simon, H. A. (1996). The Sciences of the Artificial. MIT, 3rd ed. ISBN: 0262691914. Searches: https://www.amazon.com/s?k=0262691914 https://www.google.com/search?q=isbn+0262691914 https://lccn.loc.gov/96012633 Previous editions available at: https://archive.org/search.php?query=The%20sciences%20of%20the%20artificial      Smallberg, G. (2015). No shared theory of mind. (pp. 297–299). In Brockman (2015).      Ulam, S. (1958). John von Neumann 1903-1957. Bull. Amer. Math. Soc., 64, 1–49. https://doi.org/10.1090/S0002-9904-1958-10189-5 Retrieved 29th Oct. 2020.      Weizenbaum, J. (1976). Computer Power and Human Reason: From Judgment to Calculation. W. H. Freeman and Company. ISBN: 0716704633. Also available at: https://archive.org/details/computerpowerhum0000weiz      Wolfram, S. (Ed.) (2002). A New Kind of Science. Wolfram Media, Inc. ISBN: 1579550088. Searches: https://www.amazon.com/s?k=1579550088 https://www.google.com/search?q=isbn+1579550088 https://lccn.loc.gov/2001046603      Yudkowsky, E. (2013). Intelligence explosion microeconomics. Machine Intelligence Research Institute. Technical report 2013-1. https://intelligence.org/files/IEM.pdf Retrieved ca. 9th Dec. 2018.      Yudkowsky, E. (2017). There’s no fire alarm for artificial general intelligence. Machine Intelligence Research Institute. 13th Oct. 2017. https://intelligence.org/2017/10/13/fire-alarm/ Retrieved 9th Dec. 2018.   Copyright: 2020 Retraice, Inc. https://retraice.com

On Dulles, evidence, trust, ‘is’ and ‘ought’, and capacities.   Subscribe at: paid.retraice.com    Details: Allen Dulles; The Craft of Intelligence; the gist of chpt. 15—‘Security in a Free Society’; four kinds of problems; problems of evidence; text; context; 'we'; evidence of thoughts; evidence of events; events and ideas; beliefs; problems of trust; deception and error; reputations; power (control) and incentives; control; incentives; problems of ‘is’ and ‘ought’; good guys and bad guys; openness; errors; need for ‘the bloodthirsty’; violence; kinds of war; psychological warfare—rumors; cyberwarfare—probing defenses; problems of our capacities; recap; next. Complete notes and video at: https://www.retraice.com/segments/re2   Dulles - Craft of Intelligence chpt. 15, ‘Security in a Free Society’, Part 1.   Air date: Tuesday, 8th Sep. 2020, 5pm Pacific/US.   0:00:00 Allen Dulles; 0:14:35 The Craft of Intelligence; 0:21:43 the gist of chpt. 15—‘Security in a Free Society’; 0:25:23 four kinds of problems; 0:25:54 problems of evidence; 0:25:59 text; 0:28:34 context; 0:31:35 'we'; 0:33:13 evidence of thoughts; 0:37:15 evidence of events; 0:40:05 events and ideas; 0:41:32 beliefs; 0:43:16 problems of trust; 0:43:55 deception and error; 0:44:45 reputations; 0:51:22 power (control) and incentives; 0:55:29 control; 1:02:37 incentives; 1:08:23 problems of ‘is’ and ‘ought’; 1:09:12 good guys and bad guys; 1:11:14 openness; 1:13:31 errors; 1:13:56 need for ‘the bloodthirsty’; 1:19:46 violence; 1:22:09 kinds of war; 1:22:24 psychological warfare—rumors; 1:24:18 cyberwarfare—probing defenses; 1:26:54 problems of our capacities; 1:29:44 recap; 1:31:05 next.   References:    Duflo, E., & Banerjee, A. (2019). Economic incentives don’t always do what we want them to. New York Times. 26th Oct. 2019 https://www.nytimes.com/2019/10/26/opinion/sunday/duflo-banerjee-economic-incentives.html Retrieved 8th Sep. 2020.   Dulles, A. (1960). Letter to Mr. Charles JV Murphy from Allen W. Dulles. cia.gov. 9th Jun. 1960 https://www.cia.gov/library/readingroom/docs/CIA-RDP80B01676R003600130033-5.pdf Retrieved 8th Sep. 2020.   Dulles, A. (2016). The Craft of Intelligence. Lyons Press / Rowman & Littlefield. First published 1963. This edition copyright Joan Buresch Talley, daughter of Dulles. ISBN: 978-1493018796. Different editions available at: https://archive.org/search.php?query=The%20Craft%20of%20Intelligence   Fischer, D. H. (1970). Historians Fallacies: Toward A Logic Of Historical Thought. Harper & Row. ISBN: 0061315451. Searches: https://www.amazon.com/s?k=0061315451 https://www.google.com/search?q=isbn+0061315451 https://lccn.loc.gov/69015583 Similar edition available at: https://archive.org/details/HistoriansFallaciesTowardALogicOfHistoricalThought/   Fitzgerald, F. S. (1936). The crack-up: A desolately frank document from one for whom the salt of life has lost its savor. Esquire. 1st Feb. 1936 https://classic.esquire.com/article/1936/2/1/the-crack-up Retrieved 8th Sep. 2020.   Gregory, R. L. (Ed.) (2004). The Oxford Companion to the Mind. Oxford University Press, 2nd ed. ISBN: 0198662246. Searches: https://www.amazon.com/s?k=0198662246 https://www.google.com/search?q=isbn+0198662246 https://lccn.loc.gov/2004275127   Grose, P. (1994). Gentleman Spy: The Life of Allen Dulles. Houghton Mifflin. ISBN: 0395516072. Also available at: https://archive.org/details/gentlemanspylife00gros   Hamblin, C. L. (1970). Fallacies. Vale. First published 1970. This Vale Press edition 2004. ISBN: 0916475247. Different edition available at: https://archive.org/details/fallacies0000hamb/page/12/mode/2up.   Horwich, P. (1982). Probability and Evidence. Cambridge. First published 1982; first paperback 2011; this Cambridge Philosophy Classics edition 2016. ISBN: 978-1316507018. Searches: https://www.amazon.com/s?k=978-1316507018 https://www.google.com/search?q=isbn+978-1316507018 https://lccn.loc.gov/2015049717   Kennedy, J. F. (1961). Remarks Upon Presenting The National Security Medal To Allen W. Dulles. jfklibrary.org. 28th Nov. 1961 https://www.jfklibrary.org/asset-viewer/archives/JFKWHA/1961/JFKWHA-058-003/JFKWHA-058-003 Retrieved 1st Sep. 2020.   Nell, V. (2004). Cruelty. Article in Gregory (2004).   O’Donnell, P. K. (2004). Operatives, Spies, and Saboteurs: The Unknown Story of the Men and Women of World War II’s OSS. Free Press / Simon & Schuster. ISBN: 074323572X. Also available at: https://archive.org/details/operativesspiess00odon   Retraice (2020/xx/xx). Re6: Interface. retraice.com. Pending publication.   Schneier, B. (2016). Someone is learning how to take down the internet. schneier.com. 13th Sep. 2016 https://www.schneier.com/essays/archives/2016/09/someone_is_learning_.html Retrieved 8th Sep. 2020. Also published at https://www.lawfareblog.com/someone-learning-how-take-down-internet   Talbot, D. (2015). The Devil’s Chessboard: Allen Dulles, the CIA, and the Rise of America’s Secret Government. Harper Perennial. ISBN: 978-0062276179. Searches: https://www.amazon.com/s?k=978-0062276179 https://www.google.com/search?q=isbn+978-0062276179 https://lccn.loc.gov/2015487367   Trento, J. J. (2001). The Secret History of the CIA. Forum / Prima. ISBN:0761525629 https://archive.org/details/secrethistoryofc0000tren/mode/2up Retrieved 8th Sep. 2020.   Weizenbaum, J. (1976). Computer Power and Human Reason: From Judgment to Calculation. W. H. Freeman and Company. ISBN: 0716704633. Also available at: https://archive.org/details/computerpowerhum0000weiz   Copyright: 2020 Retraice, Inc. https://retraice.com

That exponential pace of improvement is key to making quantum computers truly practical beyond today's research machines.

That exponential pace of improvement is key to making quantum computers truly practical beyond today's research machines.

This week Kade takes you through many philosophical questions on whether we are living in a simulated reality or not. What if we are? How would we know? Who controls us? What if we aren't? All these questions are discussed this week, so please enjoy.Further Reading:https://builtin.com/hardware/simulation-theoryhttps://en.wikipedia.org/wiki/Simulation_hypothesishttps://www.vulture.com/2019/02/15-irrefutable-reasons-we-might-be-living-in-a-simulation.htmlVideos:https://www.youtube.com/watch?v=tlTKTTt47WEhttps://www.youtube.com/watch?v=J0KHiiTtt4whttps://www.youtube.com/watch?v=yGfTDcHJHSIhttps://www.youtube.com/watch?v=3d9i_0Ty7CgSupport the show (https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=R5Q2Z2RBKQUK6¤cy_code=USD&source=url)

Hello again from DEM BOYS at ARG Presents! This time out, it's another crazy trip to Japan for the SORD M5 computer! We touched on the SORD during the Thanks For Giving marathon, but this time it gets the FULL TREATMENT! Join Amigo Aaron and THE BRENT as we try POWER PAC and then we dive into WONDER HOLE! --- Support this podcast: https://anchor.fm/arg-presents/support

Hello again from DEM BOYS at ARG Presents! This time out, it's another crazy trip to Japan for the SORD M5 computer! We touched on the SORD during the Thanks For Giving marathon, but this time it gets the FULL TREATMENT! Join Amigo Aaron and THE BRENT as we try POWER PAC and then we dive into WONDER HOLE! --- Send in a voice message: https://anchor.fm/amigospodcast/message

Free VPN? Cloudflare’s bringing Warp VPN to their 1.1.1.1 app! Best PSU picks: is a 10 year warranty on a PC power supply legit??? Riding in Waymo’s self driving car is cool, powerstrips that automatically reboot your cable modem, digitizing tapes, and more in TekThing episode 223 with Patrick Norton and Shannon Morse! All the shownotes and links for episode 223.

In this Week’s show Justin and Andy deal with the Technology Gremlins with Andy sharing a story of Power and UPS systems. Andy finds very quickly he isn’t immune to the “Is it plugged in” question as the first line of questions in Tech Support. What happens when Power into the building is not delivered at the proper voltage? Justin shares info on the difference between US power and the system in Japan. Protecting your equipment with a UPS Smart System and Line Conditioner is smart with today’s electronics. Andy and Justin talk about the future of PC technology and how we have evolved from talking about PC and Laptops to the constant discussion of Smart Phones and tablets. Gaming and ESports continue to be a driving force for PC’s with popular gamers and streaming through Twitch and the Up and Coming Facebook Gaming streams. For the basic users, what is the solution for buying a new PC? Where can users get the best bang for the buck? The Question of Intel vs. AMD is also discussed. For users wanting to optimize their systems, start with a cleanup of the Desktop. Justin talks about Battle Royale with a discussion of Player Unknown Battlegrounds otherwise known as PUBG and Fortnite from Epic Games. What are the differences and features of these titles? Justin, who was originally a little less enthusiastic over Nintendo Switch, raves about the game play! Mobile games are also discussed by Andy. Digital Home Assistants are discussed with the differences between the Google Home Assistant and Amazon Alexa. New features to the devices are being added for an even better experience. Why is Radio pushing for the Amazon Alexa to be a partner in delivering audio? Wired publishes a great feature on its website for learning which device to get. The Website of the Week is an Online Game with the Characters from Super Mario floating around in a different type of game play! http://jellymar.io Connect with us on our Social Media sites. Facebook Techtalkers http://www.facebook.com/techtalkers Twitter @techtalkradio Instagram techtalkradio

Download: MP3 FileThis Saturday night the radio show gets our first guest in the studio for 2017: producer and DJ Otter, whose deep crates of bass music are a wonder to behold. With roots in the dirty south electro sounds and his eyes firmly fixed on futuristic sounds across breaks, drum'n'bass, trap and dub, we had some serious fun."Otter has been heavily involved in the Electronic Dance Music scene since 2001. Born and Raised in Atlanta, his musical influences range from the likes of Evol Intent, Tester, DJ Casper, Stanton Warriors, DJ Icey, DJ Fixx, Keith Mackenzie, Rick West, and Infiniti."Playlist:Guest DJ set from Otter:Otter - "Catalyst"Otter - "Close Encounters"Otter - "Scalawag"Otter - "Don't You Dare"London Elektricity - "Just One Second (Otter remix)"Otter - "Alpha Orion"Lecrae - "Say I Won't (Otter remix)"Better Kicks - "Dancefloor Destroyer (Otter remix)"Otter - "Take Yourself Away"Agent K - "Breaker"Lab3 & Ofay - "Smurf"DJ Icey & ill DJ Chris B - "Fam Litty"DeBeat - "Operator (this is an emergency)"A G Cook - "Had 1 Egyptian (Phat Kids edit)"Inxs - "Need You tonight (Alt-A Bootleg)"DJ Hero - "Baddest DJ"Lab3 & Ofay - "who's got the fix"Underworld - "Born Slippy (Breaking News remix)"Shade - "Fine Bass"DBK & Dmoney - "We Breakin (Colombo remix)"Kloe, Imprintz, J Scott G - "Return of the King (DJ Hero re-rub)"Prince - "Erotic City (Scotty Boy remix)"Agent K - "I See the Future"DJ Icey - "Searching"Infiniti & Keith Mackenzie - "Shadow"Dave London - "Genesis"DJ 33 & MC Freeflow - "Move To Night (Colombo Remix)"DJ Set - Logan 5:A1 People - "Do it Again"Jamie Jupitor - "Computer Power"Uberzone - "Synthetik"DJ Icey - "B. O. C. Bass"Exzact - "Alone 2006"Dynamik Bass System - "Robotmachine"Simon - "Two Crates"

Some diseases are so rare and unusual that doctors have never seen anything like it. An excruciating journey for both families and doctors, figuring out what’s wrong can take years, if an answer is ever found at all. Using a computer tool developed by Aaron Quinlan, Ph.D., he and his team recently uncovered the genetic causes behind nearly one dozen previously unsolved cases, all infants with severe seizures. Quinlan describes GEMINI, and how it is helping he and his colleagues at the USTAR Center for Genetic Discovery to understand rare disease genetics.

Kraftwerk - The Man MachineKid Frost - Terminator (Instrumental)Davy DMX - One For The Treble (Fresh)Strafe - Set It OffThe Extra T's - I Like It (Corn Flakes)G.L.O.B.E. & Whiz Kid - Play That Beat Mr. DJNewcleus - Jam On It (Instrumental)Hashim - We're Rocking The PlanetThe Jonzun Crew - Pack JamJamie Jupitor - Computer PowerDIRECT DOWNLOADPaul's Boutique #183 : O.G. Electro by Paul Kersey on Mixcloud