Mind Matters News and Analysis on Natural and Artificial Intelligence

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Google vs. IBM?: Quantum Supremacy Isn’t the Big Fix Anyway

If human thought is a halting oracle, then even quantum computing will not allow us to replicate human intelligence

Google’s quantum supremacy claim is certainly fascinating and controversial, but even if true, it ultimately only amounts to an incremental and even inconsequential improvement in the state of AI and ML, due to the still-unmet need for a halting oracle.

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Occam’s Razor Can Shave Away Data Snooping

The greater an object's information content, the lower its probability.

One technique to avoid data snooping is based on the intersection of information theory and probability: An object’s probability is related to its information content. The greater an object’s information content, the lower its probability. We measure a model’s information content as the logarithmic difference between the probability that the data occurred by chance and the number of bits required to store the model. The negative exponential of the difference is the model’s probability of occurring by chance. If the data cannot be compressed, then these two values are equal. Then the model has zero information and we cannot know if the data was generated by chance or not. For a dataset that is incompressible and uninformative, swirl some tea Read More ›

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Big Tech Tries to Fight Racist and Sexist Data

The trouble is, no machine can be better than its underlying training data. That’s baked in

The problem with machine learning-based AI in police work is not so much its inherent bias (none of us is bias-free) but the delegation to a machine of what should be a human decision.

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Machine Learning, Part 3: Don’t Snoop on Your Data

You risk using a feature for prediction that is common to the dataset, but not to the problem you are studying

As long as we can establish that our theories, hypotheses, and/or models are independent of the data, then we can trust that their predictive power will generalize beyond the data we have observed.

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Machine Learning, Part 2: Supervised Learning

Machine learning isn’t hard to understand; it’s just different. Let’s start with the most common type

The neat thing about machine learning is that the algorithm can extract general principles from the dataset that can then be applied to new problems. It is like the story that Newton observed an apple fall and then derived from it the general law of gravity that applies to the entire universe.

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Has AI been racist?

AI is, left to itself, inherently unthinking, which can result in insensitivity and bias

Just any available data swatched into systems may embody prejudices that only become evident in use.

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A Quick Guide to Augmented Reality

Now that Apple is integrating Augmented Reality Into iOS 13, here are some things you can do with it

While iOS 13 has some amazing features, it also has some significant limitations. The biggest one is that the tracking between the real world and the virtual world does not extend to GPS.

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