Facets contains two robust visualizations to aid in understanding and analyzing machine learning datasets. Get a sense of the shape of each feature of your dataset using Facets Overview, or explore individual observations using Facets Dive.
Science has outgrown the human mind and its limited capacities | Aeon Ideas
One promising strategy to overcome the current crisis is to integrate machines and artificial intelligence in the scientific process. Machines have greater memory and higher computational capacity than the human brain. Automation of the scientific process could greatly increase the rate of discovery. It could even begin another scientific revolution. That huge possibility hinges on an equally huge question: can scientific discovery really be automated?
The most detailed maps of the world will be for cars, not humans | Ars Technica
But a more scalable solution involves leveraging the embedded sensors in cars already using HD maps to navigate. “Today, many high-end vehicles not only have LTE connections but an array of advanced sensors on them; a forward-looking camera, forward and rear radar, and we’re working with numerous OEMs on getting that sensor data transmitted into our cloud,” said Sood. That’s going to mean millions of data points being constantly uploaded to the cloud, where Here’s servers will do the heavy lifting of making sense out of it all.
“We have machine learning algorithms and aggregation algorithms that sift through that data and try distilling changes from noise or aberrations in the world. Once we’ve detected those changes we update the map and then deploy that to the vehicle,” explained Sood.
Edgar Simo-Serra - Sketch Simplification
We present a novel technique to simplify sketch drawings based on learning a series of convolution operators.
Deep-Learning Machine Listens to Bach, Then Writes Its Own Music in the Same Style
The #machine-learning technique is straightforward. Hadjeres and Pachet begin by creating a data set to train their #neural_network. They begin with 352 chorales composed by #Bach and then transpose these to other keys that lie within a predefined vocal range, to give a data set of 2,503 chorales. They use 80 percent of these to train their neural network to recognize Bach harmonies and the rest to validate it.
98 personal data points that Facebook uses to target ads to you - The Washington Post
Maybe your mother’s birthday is coming up, and Facebook’s showing ads for her local florist.
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We need to talk about AI and access to publicly funded data-sets | TechCrunch
we’re all, as individuals, used to getting Google freebies in exchange for sharing some of our data. But the thing is, the data trade off here — with the publicly funded NHS — is a rather different beast. Because the people whose personal data is being pumped into Google-owned databanks are not being asked for their individual consent to the exchange.
Patient consent has not been sought in either of the current NHS collaborations. In the Moorfields project, where the data is being anonymized (or pseudonymized), NHS information governance rules allow for data to be shared for medical research purposes without obtaining patient consent (although NHS patients can opt out of supplying their data to all research projects) — so long as the relevant Health Research Authority clears the project. And DeepMind has applied to be cleared access in this case.