Miscellaneous

[Airicist]

https://youtu.be/37Wu7HrlYrA

Philosophy and Artificial Intelligence

Uploaded on Nov 10, 2011


A discussion of Artificial Intelligence from the standpoint of caution.
My reason for discussing a recursive proof is the question of whether a computer can intuitively know the outcome of a recursion. Can a computer "get it" with known facts without having the exact fact necessary to generate an original principle programmed in directly?

[Airicist]

https://youtu.be/yDSnZEsa9nU

G+ Philosophy of Mind: Consciousness

Streamed live on Jan 7, 2013

[Airicist]

https://youtu.be/c3of7xYoMQM

John Vervaeke - Why don't we have AI yet?

Published on Feb 5, 2013


In this mind-opening talk entitled, "The bioeconomics of relevance realization and general intelligence" award-winning lecturer John Veraeke aims to explain why we do not have artificial intelligence (AI) yet by arguing for a new framework for understanding how people think, feel and interact with the world. Every cognitive scientist and artificial intelligence researcher should see this video.

Abstract:
Vervaeke, Lillicrap, and Richards (2012) have argued that the central problem facing cognitive science is explaining how cognitive agents selectively attend to relevant information while flexibly ignoring a vast amount of irrelevant information. They further argued that the processes of relevance realization are ultimately economic in nature. Relevance realization runs off the bioeconomic properties of information processing. Vervaeke and Ferraro (forthcoming) argued that relevance realization is the core process of general intelligence and that this is being implemented in the self-organized firing and wiring of the brain. In short, it is internal economics that makes us externally smart.

John Vervaeke's homepage is at http://johnvervaeke.com

For more information on the UTISM conference and for information on future ones, please go here: http://cogsci.ca

[Airicist]

https://youtu.be/QkrhQUaypBI

Brandom on AI & Pragmatism (with Pirmin Stekeler-Weithofer)

Published on Mar 25, 2013


Robert Brandom gives a talk titled "Artificial Intelligence and Analytic Pragmatism". Then Pirmin Stekeler-Weithofer comments on it. This is the third of six lectures from the 2005-2006 John Locke lectures. The series is called "Between Saying and Doing: Towards an Analytic Pragmatism".

[Airicist]

https://youtu.be/I43hq13MnYM

Computers That Think Like Humans

Published on May 14, 2014


Wish you were as smart as a computer? Well engineers wish they could build a computer as smart as YOU! Believe it or not, your brain has many advantages over a computer chip, and at a fraction of the wattage. In a world of brain-inspired machine intelligence, computers of the future will no longer require programming -- you'll just need to teach them!

If you had a robot with brain-inspired learning hardware, what would you teach it and what would you NOT teach it? Let us know in the comments below!

[Airicist]

https://vimeo.com/61892220

Three approaches to the mind
March 15, 2013


In this 50-minute talk, Dr. Edward Hundert presents a synthesis of ideas from philosophers, psychiatrists, and neuroscientists in an effort to find a common language through which these diverse views of the human mind can contribute insights one to the next. Drawing on thinkers from Plato, Kant, Freud, Hegel, and Hume to modern neuroscientists and researchers in artificial intelligence, Dr. Hundert compares the ways various fields interpret the “nature-nurture debate” around the question of how our basic concepts of the world find their way into our brains. He concludes by comparing all of these cognitive theories of knowledge with moral theories of justice, challenging us to appreciate just how interactive the relationship is – in the realms of both knowledge and values – between the human brain and the world we share.

A psychiatrist, ethicist and educator, Dr. Hundert is Director of the Center for Teaching and Learning, and Senior Lecturer in Medical Ethics, at Harvard Medical School. He is a member of the faculty of the Center for Law, Brain, and Behavior. Dr. Hundert holds degrees in mathematics and the history of science and medicine from Yale University, in philosophy, politics, and economics from Oxford University, and in medicine from Harvard Medical School. Many of the ideas in this lecture were first put forward in his books, Philosophy, Psychiatry, and Neuroscience: Three Approaches to the Mind (Oxford University Press) and Lessons from an Optical Illusion: On Nature and Nurture, Knowledge and Values (Harvard University Press).

[Airicist]

https://youtu.be/cW1zUh94uMY

Great Minds: Slavoj Zizek

Uploaded on Jul 3, 2011


Modern radical thinker Slavoj Zizek spoke on the 1st July as part of the 'Great Minds' series, and affirmed his status as a great mind of modern philosophy and social, cultural and political theory. Starbucks, social solidarity and self-commodification were among the varied and enlightening topics touched upon by Zizek, all grounded by his interpretation of ideology and its continuing importance.

One of Europe's foremost Marxist theorists, Zizek criticised modern leftist groups who, he argued, didn't really know how to cope with the upheaval of the 'sublime' moment (revelation that an assumed state of total happiness is actually nonexistent). The question of 'what happens next' has been asked since the dwindling exhaustion of modernism into postmodernism. Zizek asks us to put ideological pressure on modern life, confirming the presence of ideological symbolism even in blatant popular culture (such as two Oscar-winning films, The King's Speech and Black Swan [2010]).

His manner was sometimes serious, sometimes comic and vaguely apocalyptic (he is a self confessed pessimist), which all together made for an engaging talk, dense in historical, anecdotal and political references. The combination of issues allowed the modern audience member to examine their own behaviour alongside Hegelian optimism, Freudian self-commodification and Marxist ideas of social roles, in a non 'academic' sense, referring to the purchasing of Starbucks coffee as a subconscious purchasing of social solidarity built into the price. An audience member asks 'isn't it the case that people know that what they're doing is buying a coffee that will then, in some sort of self-serving way, make them feel better about themselves?', thus showing that ideology is no longer a 'smokescreen' of sorts. Zizek answers by claiming that we follow things, knowing that they are ideologies, and this does not necessarily make them 'right' or true. This is where the notion of ideology seems to be headed; to a total self consciousness -- as with a Hegelian resolution of the 'Zeitgeist' (Zizek is actually close to the publishing of an 800 page book on Hegel).

In his relatively brief talk, Slavoj Zizek managed to expose our susceptibility to certain ideologies, thus proving their ever present role in modern society - not bad for a Friday night in West London, perhaps the capital of the British bourgeoisie.

[Airicist]

https://youtu.be/oY2C4YgXm7I

8 Intelligences: Are You a Jack of All Trades or a Master of One?

Published on Jan 13, 2016


What does it mean when someone calls you smart or intelligent? According to developmental psychologist Howard Gardner, it could mean one of eight things.

Read the full transcript here: "Intelligence Isn't Black and White. There Are Actually 8 Different Kinds. (https://bigthink.com/videos/howard-gardner-on-the-eight-intelligences)"

[Airicist]

https://youtu.be/bctMvKrB_y0

Why machines don't think like humans

Published on Mar 8, 2016


Artificial intelligence doesn't mimic the workings of the human brain: it reasons in a completely different way.

[Airicist]

Article "5 Big Predictions for Artificial Intelligence in 2017 (https://www.technologyreview.com/s/603216/5-big-predictions-for-artificial-intelligence-in-2017)"
Expect to see better language understanding and an AI boom in China, among other things.

by Will Knight
January 4, 2017

[Airicist]

https://youtu.be/2wgX30h8w3g

What is Artificial Intelligence?

Published on May 17, 2017


Computers that can recognize images, diagnose diseases and dominate every strategy game – the progress made in the field of artificial intelligence has been spectacular. But: »Artificial intelligence« (AI) – what is it exactly? And what impact will it have on work, society and companies? Everybody is discussing it. Anybody who wants to join the conversation has to understand what it is about. We make it easy: Artificial intelligence explained succinctly.

[Airicist]

"Living Together: Mind and Machine Intelligence (https://arxiv.org/pdf/1705.07996.pdf)"

by Neil D. Lawrence
May 22, 2017

[Airicist]

https://youtu.be/3Bns4HkAniA

Artificial Intelligence is the new science of human consciousness | Joscha Bach

Published on Jul 1, 2017


I think right now everybody is already perceiving that this is the decade of AI. And there is nothing like artificial intelligence that drives the digitization of the world. Historically artificial intelligence has always been the pioneer battallion of computer science.

When something was new and untested it was done in the field of AI, because it was seen as something that requires intelligence in some way, a new way of modeling things. Intelligence can be understood to a very large degree as the ability to model new systems, to model new problems.

And so it’s natural that even narrow AI is about making models of the world. For instance our current generation of deep-learning systems are already modeling things. They’re not modeling things quite in the same way with the same power as human minds can do it—They’re mostly classifiers, not simulators of complete worlds. But they’re slowly getting there, and by making these models we are, of course, digitizing things. We are making things accessible in data domains. We are making these models accessible to each other by computers and by AI systems.

And AI systems provide extensions to all our minds. Already now Google is something like my exo-cortex. It’s something that allows me to act as vast resources of information that get integrated in the way I think and extend my abilities. If I forget how to use a certain command in a programming language, it’s there at my fingertips, and I entirely rely on this like every other programmer on this planet. This is something that is incredibly powerful, and was not possible when we started out programming, when we had to store everything in our own brains.

I think consciousness is a very difficult concept to understand because we mostly know it by reference. We can point at it. But it’s very hard for us to understand what it actually is.

And I think at this point the best model that I’ve come up with—what we mean by consciousness—it is a model of a model of a model.
That is: our new cortex makes a model of our interactions with the environment. And part of our new cortex makes a model of that model, that is, it tries to find out how we interact with the environment so we can take this into account when we interaction with the environment. And then you have a model of this model of our model which means we have something that represents the features of that model, and we call this the Self.

And the self is integrated with something like an intentional protocol. So we have a model of the things that we attended to, the things that we became aware of: why we process things and why we interact with the environment. And this protocol, this memory of what we attended to is what we typically associate with consciousness. So in some sense we are not conscious in actuality in the here and now, because that’s not really possible for a process that needs to do many things over time in order to retrieve items from memory and process them and do something with them.

Consciousness is actually a memory. It’s a construct that is reinvented in our brain several times a minute.

And when we think about being conscious of something it means that we have a model of that thing that makes it operable, that we can use.

You are not really aware of what the world is like. The world out there is some weird [viewed?] quantum graph. It’s something that we cannot possibly really understand —first of all because we as observers cannot really measure it. We don’t have access to the full vector of the universe.

What we get access to is a few bits that our senses can measure in the environment. And from these bits our brain tries to derive a function that allows us to predict the next observable bits.

So in some sense all these concepts that we have in our mind, all these experiences that we have—sounds, people, ideas and so on— are not features of the world out there. There are no sounds in the world out there, no colors and so on. These are all features of our mental representations. They’re used to predict the next set of bits that are going to hit our retina or our eardrums.

I think the main reason why AI was started was that it was a science to understand the mind. It was meant to take over where psychology stopped making progress. Sometime after Piaget, at this point in the 1950s psychology was in this thrall of behaviorism. That means that it only focused on observable behavior. And in some sense psychology has not fully recovered from this. Even now “thinking” is not really a term in psychology, and we don’t have good ways to study thoughts and mental processes. What we study is human behavior in psychology. And in neuroscience we mostly study brains, nervous systems.

[Airicist]

https://youtu.be/djkeV4gew4Q

Making computers smarter with Google's AI chief John Giannandrea | Disrupt SF 2017

Published on Sep 19, 2017


Google's John Giannandrea sits down with Frederic Lardinois to discuss the AI hype/worry cycle and the importance, limitations, and acceleration of machine learning.

[Airicist]

https://youtu.be/TWyS2z9xv9c

Our Skynet moment - Tim O'Reilly

Published on Sep 20, 2017


A world ruled by machines that are hostile to humanity is not a distant possibility. Complex systems evolve from much simpler forebears, and the design of the systems we are building today is already shaping the future of truly intelligent machines. We are in a defining period of the struggle for human freedom.

Tim O’Reilly draws on lessons from networked platforms such as Amazon, Google, Facebook, Airbnb, Uber, and Lyft to show how our economy and financial markets have also become increasingly managed by algorithms, making the case that income inequality, declining upward mobility, and job losses due to technology are not inevitable; they are the result of design choices we have made in the algorithms that manage our markets. Just as Google constantly updates its algorithms in pursuit of relevant search and ad results and as Facebook wrestles with how to rethink its algorithms for user engagement in response to fake news, we must rewrite the algorithms that shape our economy if we wish to create a more human-centered future.

[Airicist]

https://youtu.be/zjeBGkS4LAA

AI explained in 101 seconds

Published on Sep 25, 2017


Artificial intelligence is making our devices more than just utilities. From smartphones to healthcare to autonomous cars, our own Gary Brotman explains the potential of AI to make our lives easier and more exciting.

[Airicist]

https://youtu.be/OV7k0Nsa9F4

Ethnography for Artificial Intelligence

Published on Oct 6, 2017


An introduction to ethnography for Artificial Intelligence as well as conversational analysis and its relevance to AI.

[Airicist]

https://youtu.be/F_QZ2F-qrGM

Artificial intelligence: Making a human connection - Genevieve Bell (Intel Corporation)

Published on Sep 28, 2016


We have been talking about robots and artificial intelligence forever, or so it sometimes seems. Images of smart machinery have inhabited our thinking and our literary and cultural imaginations long before technology made such objects possible. It is tempting to keep separate the art and science of the robot and the artificial intelligence that underpins it. However, there are reasons to thread them back together. After all, the AI of our imagination is the AI we have built.

Genevieve Bell explores the meaning of “intelligence” within the context of machines and its cultural impact on humans and their relationships. Genevieve interrogates AI not just as a technical agenda but as a cultural category in order to understand the ways in which the story of AI is connected to the history of human culture.

[Airicist]

https://youtu.be/aCCotxqxFsk

Artificial Intelligence Debate - Yann LeCun vs. Gary Marcus - Does AI Need More Innate Machinery?

Published on Oct 20, 2017


Debate between Facebook's head of AI, Yann LeCun and Prof. Gary Marcus at New York University.

Gary Marcus begins at 10:06
Yann LeCun begins at 34:12

The debate was moderated by Prof. David Chalmers.

Recorded: Oct 5th, 2017

[Airicist]

https://youtu.be/jiXwXg2CUWM

AI explained

Published on Nov 14, 2017


Here we take a deep dive into the current state of AI

[Airicist]

https://youtu.be/NPEPx6VUgrg

Why artificial intelligence has no common sense

Published on Jul 9, 2018


We are surrounded by artificial intelligence. From the Google Home and Amazon Echo, to Facebook’s facial recognition and whatever it is Huawei’s doing. It’s easy to become desensitized to the term and misunderstand the current state of AI we live in. Verge video director Becca Farsace talks to some experts in the field of AI to better pinpoint what all this AI really means.