Daily Links 04/04/2017

Emotion Detection and Recognition from Text Using Deep Learning

The researchers used a data set of short English text messages labeled by Mechanical Turkers with five emotion classes anger, sadness, fear, happiness, and excitement. A multi-layered neural network was trained to classify text messages by emotion. The model was able to classify anger, sadness, and excitement well but didn’t do well at recognizing fear.

Adapting ideas from neuroscience for AI

We don’t really know why neurons spike. One theory is that they want to be noisy so as to regularize, because we have many more parameters than we have data points. The idea of dropout [a technique developed to help prevent overfitting] is that if you have noisy activations, you can afford to use a much bigger model. That might be why they spike, but we don’t know. Another reason why they might spike is so they can use the analog dimension of time, to code a real value at the time of the spike. This theory has been around for 50 years, but no one knows if it’s right. In certain subsystems, neurons definitely do that, like in judging the relative time of arrival of a signal to two ears so you can get the direction.

Five AI Startup Predictions for 2017

My favorite: “Full stack AI startups actually work”

When you focus on a vertical, you can find high level customer needs that we can meet better with AI, or new needs that can’t be met without AI. These are terrific business opportunities, but they require much more business savvy and subject matter expertise. The generally more technical crowd starting AI startups tend to have neither, and tend to not realize the need for or have the humility to bring in the business and subject matter expertise required to ‘move up the stack’ or ‘go full stack’ as I like to call it.

The Silicon Gourmet: training a neural network to generate cooking recipes

Pears Or To Garnestmeam

meats

¼ lb bones or fresh bread; optional
½ cup flour
1 teaspoon vinegar
¼ teaspoon lime juice
2  eggs

Brown salmon in oil. Add creamed meat and another deep mixture.

Discard filets. Discard head and turn into a nonstick spice. Pour 4 eggs onto clean a thin fat to sink halves.

Brush each with roast and refrigerate.  Lay tart in deep baking dish in chipec sweet body; cut oof with crosswise and onions.  Remove peas and place in a 4-dgg serving. Cover lightly with plastic wrap.  Chill in refrigerator until casseroles are tender and ridges done.  Serve immediately in sugar may be added 2 handles overginger or with boiling water until very cracker pudding is hot.

Yield: 4 servings

Also see In Which a Neural Network Learns to Tell Knock-Knock Jokes

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