Mind Matters News and Analysis on Natural and Artificial Intelligence

CategoryMachine Learning

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The true cost of “free” social media

It’s free but… are we? George Gilder points a way forward.
He thinks that expected massive increases in computing power will enable blockchain technologies that allow users to safely bypass the global data monopoly that Google and similar firms represent. Read More ›
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Senior Google scientist quits over Google’s censorship in China

He believes it “contravenes widely accepted principles of international law and human rights”
Some believe that any censorship system that a human being can develop can somehow be got around by another human being. China may provide a way of testing that.   Read More ›
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How Bitcoin Works: The social value of trust

The idea of employing such a game to guarantee validity in a trustless environment is nothing short of groundbreaking. It is an amazing accomplishment, and I am impressed by it more each time I think about it. However, it does have some drawbacks, which, I think, will ultimately lead to its demise.

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Twitter doesn’t just seem out of control

It actually is.
Social media may be changing the world more than we think. And we may need some social leadership in fighting back against Twitter mobs. It probably won’t emerge from within because bullies are usually cowards. Read More ›
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Google branches out into politics

Unfortunately, the only political model it would likely know is: One-party state

The unchallenged manipulation of search engine results during elections is a new phenomenon made possible by the domination of the internet by a few big players.

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How do robots “care”?

Emotional robots’ cameras and sensors respond to your facial expressions, tone of voice, and movements

Critics of the emotional robotics industry say that the view of emotions (assumed in the industry to be only six) is oversimplified and that the robots are likely to promote stereotypes.

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Can machines really learn?

A parable of a book that learned
Machine learning is a powerful and important tool that is likely to be of great value (and perhaps great risk) to man. Machines can be designed to change with time but it is man, and only man, who learns. Read More ›
George Montañez

What is learning anyway?

Machine learning specialist George Montañez reflects on the question in a video excerpt from the CNAI gala
Can we make approximations that are so close to ourselves that the fact that they are approximations no longer matters? Read More ›
Building a better future

“Artificial” Artificial Intelligence

What happens when AI needs a human I?
Artificial intelligence often fails at crucial points. It must then be supplemented by human intelligence. Many software systems that look to their users like pure advanced artificial intelligence hide a lot of human effort behind a technological mask. Read More ›
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Slaughterbots: How far is too far?

And how will we know if we have crossed a line?
A greater focus should be on restoring the foundations of our nation over building superweapons. And the key foundation is all human beings' right to life. Read More ›
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Karl Marx’s Eerie AI Prediction

He felt that capitalism would fall when machines replaced human labor
Because Marx held that the value of goods resided in the labor required to produce them, if goods were produced by automatons, without human labor, the economy would fall apart and capitalism would fail. Read More ›
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Imagining Life after Google

Reviewers of George Gilder's new book weigh in

If we have simply taken the big software, hardware, and social media companies who dominate our lives for granted, the reactions from the business world to Life after Google: The Fall of Big Data and the Rise of the Blockchain Economy should give us a lot to think about.

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Robogeddon!! Pause.

Wait. This just in: AI is NOT killing all our jobs
Jay Richards, author of The Human Advantage: The Future of American Work in an Age of Smart Machines,sees it as more of a retooling than a meltdown. But retooling does mean change, work, cost, and risk. Read More ›
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Ethics for an Information Society

Because machines can’t learn to solve their own ethical problems
AI (machine learning) was probably faster and cheaper but the whole point of the system was supposed to be justice which, whatever the explanation, proved too difficult to calculate… Read More ›
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Sometimes the ‘Bots Turn Out To Be Humans

That “lifelike” effect was easier to come by than some might think
Companies sometimes pretend to be using AI or machine learning when they are actually using human employees for various reasons. One reason is that they have promised potential investors more high tech than they can deliver. Sometimes, as we learned recently at The Guardian, it gets a bit sticky... Read More ›
Biometric facial recognition on smartphone. Unlock smartphone as it scans his face.

Will AI Liberate or Enslave Developing Countries?

Perhaps that depends on who gets there first with the technology
Karl D. Stephan: Zimbabwe, an African country well-known for its human-rights abuses, has received advanced Chinese AI technology from a startup company in exchange for letting the firm have access to the country’s facial-recognition database. So China is helping the government of Zimbabwe to keep tabs on its citizens as well. Read More ›
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Who Creates Information in a Market?

Do exchange-traded funds (ETFs)' algorithms make personally gathering information obsolete?

Algorithmic strategies can only be as good as the information that goes into them.  Ignoring how the information is created causes us to misunderstand the dynamics of value creation.  Algorithms can leverage information, they can’t create it.

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