Mind Matters News and Analysis on Natural and Artificial Intelligence

CategoryMachine Learning

ke-wen-623575-unsplash
Crosswalk with fake car and pedestrians

Does a Western Bias Affect Self-Driving Cars?

How a driver is expected to act varies by culture
Self-driving cars (autonomous vehicles) will need to adapt to different rules and we will, very likely, need to change those rules to make the vehicles work. Read More ›
Man with cardboard box on his head on grey background

The Machine Knows You Are Angry

Okay, it knows if your facial muscles are twisted in a certain way… does the difference matter?
Five accomplished scientists representing different camps reviewed over a thousand studies of machine emotion recognition. Essentially, there seems no clear science basis for the claims made. Read More ›
Chatbot conversation on smartphone screen app interface with artificial intelligence technology providing virtual assistant customer support and information, person hand holding mobile phone

You can build your own chatbot

New tools have made it comparatively easy

Natural Language Interfaces (the technical term for a chatbot) are becoming more and more popular. Many dial-in phone services have switched from numeric interfaces (“Dial 1 for sales, 2 for service, etc.”) to natural language interfaces (“Please say what you are calling about”). Where they have taken off though is with chatbots. Many online help systems at least start with chatbots, which collect basic information about a problem or situation and point to existing solutions before passing the contact off to a human expert. Additionally, the rise of the Generation Text, as well as the proliferation of chat-based groupware such as Slack, means that text-based natural language interfaces are one of the best ways of interacting with young people. Is Read More ›

Modern Red Haired Man Relaxing in Office

Lazy Engineers Treat AI as Magic!

When software engineers mostly use shared code, they save time but risk losing understanding

Building from scratch is different. Knowing when to use a tool and why and knowing the limitations of each tool separates the craftsperson from the novice.

Read More ›
markus-spiske-TaKB-4F58ek-unsplash

We Built the Power Big Social Media Have Over Us

Click by click, and the machines learned the patterns. Now we aren’t sure who is in charge

We’re stuck, working for free, training the Web giants’ ML systems to reap benefits for them while enduring (assuming we notice) the downsides.

Read More ›
daniel-monteiro-47VpDiZzzEQ-unsplash
Car top taxi sign

Even Uber didn’t believe in Uber’s self-driving taxis

We found that out after Google’s Waymo sued the company

Optimism is not driving the recent collaboration and corporate consolidation in the self-driving car industry. Rather, their retrenchment is protection against an uncertain future.

Read More ›
Helmeted police officers photographed from behind during a protest

Can AI Predict and Prevent Political Unrest?

The 1996 Democratic Convention tried neural networks but discovered a hidden flaw

The police union’s 1996 objection to fingering specific officers as violence risks without a detailed explanation pinpoints a weakness of neural networks even to this day. The neural network is basically a black box.

Read More ›
Ruins of Knossos Palace, Crete, GREECE

Could Machine Learning Decipher Lost Languages?

It gives us new search powers, based on perennial facts of language

An endless variety of word games derives from the fact that only certain combinations and orderings of words can be correct. Machine learning applies vast resources to cracking the code.

Read More ›
Animal clouds shape

How Business Intelligence Can Break the Data Deadlock

Companies today are awash in information. But which patterns are real? Which are cloud bunnies?

Contrary to the dogma of hypothesis testing, it is possible to do after-the-fact pattern analysis while limiting the probability of false positives.

Read More ›
Abstract Visualisation of data and technology in graph form. 3D Illustration
Abstract Visualization of data and technology in graph form. 3D Illustration

Machine Learning Tip: Set Boundaries for the Problems

We cannot take a giant pile of unorganized data, shove it into a machine, and expect useful results

Humans intrinsically understand causation and, therefore know which pieces of data likely have some correlation. Therefore, when we select data for computers to analyze, we are drastically reducing the size of the problem for computers.

Read More ›
george-pagan-iii-624417-unsplash
Just Did It hashtag

Winning Tag Lines Are Hard Enough To Write…

But AI really flops at that

AI tools help us do things better, faster, or more efficiently. But they lack the mind needed to know when “I’m loving’ it” is the winning slogan—and stop there. 

Read More ›
samuele-errico-piccarini-197299-unsplash
Photo from driver's seat with light trails ahead

The Real Future of Self-Driving Cars Is — Better Human Drivers!

Manufacturers are improving safety by incorporating warning systems developed for self-driving cars into conventional models

This human-plus-machine combination is proving more potent than the machine-only hype/promise.

Read More ›
tomas-robertson-1463833-unsplash

Successful Generalization Is a Key to Learning

In machine learning, the Solomonoff induction helps us decide how successful a generalization is

In the model of generalization set out in the paper, imperfect models can get better scores but they are discounted according to the amount of error they have.

Read More ›
Old calculator
Detail of an old office machine used for calculations

Machine Learning Dates Back To at Least 300 BC

The key to machine learning is not machines but mathematics

Machine learning is not a new technique, but is simply a modern extension of a tool that we have had in our toolbox since the days of the Babylonians. It continues to serve us well to help us extrapolate our data to estimate the value of unknown results and to help find the signal in noisy data.

Read More ›
chris-barbalis-186421-unsplash
Painted face, split in two

AI as the Artful Dodger

Watch what happens when I train a neural network on portraits of 56 famous scientists, starting the process with a right eye
New AI is much more sophisticated but the old and new AI share the property that the final result is nothing more than an interpolation of the training images used to train the AI. Read More ›
Detroit-Become-Human-Still
Android being constructed from Detroit: Become Human

A Closer Look at Detroit: Become Human, Part III

The second pillar of the AI religion is reductionism, the reduction of humanity to matter and energy

If the qualities that define being human (so that there is an obvious distinction between what is human and what is not) are not material by nature; then the premise of a compelling story about androids that become and surpass human beings as intelligent life falls flat.

Read More ›
meteorite explosion in the air on black bakcground
Missile explosion

Why we can’t just ban killer robots

Should we develop them for military use? The answer isn’t pretty. It is yes.

Autonomous AI weapons are potentially within the reach of terrorists, madmen, and hostile regimes like Iran and North Korea. As with nuclear warheads, we need autonomous AI to counteract possible enemy deployment while avoiding its use ourselves.

Read More ›
amanda-sandlin-10508-unsplash
Stripes on two lane highway

Can We Program Morality into a Self-Driving Car?

A software engineering professor tells us why that’s not a realistic goal

Any discussion of the morality of the self-driving car should touch on the fact that the industry as a whole thrives on hype that skirts honesty.

Read More ›
matthew-brodeur-436250-unsplash
Cryptic characters in neon, a password or curse word

Bitcoin: Is Lack of Trust the Biggest Security Threat?

It’s almost a parable: Everyone can see, no one can access, the millions trapped in the ether by a password known only to a dead man

Is this the future of currency? Seems like the Dark Ages to me. Bitcoin is a clever idea, but it is perhaps too clever for its own good.

Read More ›