CategoryMachine Learning
The Machine Knows You Are Angry
Okay, it knows if your facial muscles are twisted in a certain way… does the difference matter?
You can build your own chatbot
New tools have made it comparatively easyNatural 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…
Lazy Engineers Treat AI as Magic!
When software engineers mostly use shared code, they save time but risk losing understandingBuilding 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.
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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 chargeWe’re stuck, working for free, training the Web giants’ ML systems to reap benefits for them while enduring (assuming we notice) the downsides.
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Even Uber didn’t believe in Uber’s self-driving taxis
We found that out after Google’s Waymo sued the companyOptimism is not driving the recent collaboration and corporate consolidation in the self-driving car industry. Rather, their retrenchment is protection against an uncertain future.
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Can AI Predict and Prevent Political Unrest?
The 1996 Democratic Convention tried neural networks but discovered a hidden flawThe 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.
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Could Machine Learning Decipher Lost Languages?
It gives us new search powers, based on perennial facts of languageAn 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.
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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.
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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 resultsHumans 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.
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Winning Tag Lines Are Hard Enough To Write…
But AI really flops at thatAI 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.
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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 modelsThis human-plus-machine combination is proving more potent than the machine-only hype/promise.
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Successful Generalization Is a Key to Learning
In machine learning, the Solomonoff induction helps us decide how successful a generalization isIn 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.
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Machine Learning Dates Back To at Least 300 BC
The key to machine learning is not machines but mathematicsMachine 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.
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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
Self-driving Cars Need Virtual Rails
The alternative is more needless fatalitiesA virtual rail is essentially a road that is built expressly for driverless cars.
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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 energyIf 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.
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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.
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Can We Program Morality into a Self-Driving Car?
A software engineering professor tells us why that’s not a realistic goalAny 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.
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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 manIs 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.
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