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Please explain Support Vector Machines (SVM) like I am a 5 year old. • r/MachineLearning
This is tough for five-year-olds, but I'll give it a shot for ten-year-olds. Like a lot of other machine learning algorithms, SVMs take some data to start with that's already classified (the training set), and tries to predict a set of unclassified data (the testing set). The data that we have often has a lot of different features, and so we can end up plotting each data item as a point in space, with the value of each feature being the value at a particular coordinate. Now (for two data features) what we want to do is find some line that splits the data between the two differently classified groups of data as well as we can. This will be the line such that the distances from the closest point in each of the two groups will be farthest away.
PETER HITCHENS tries out Amazon's 'personal assistant'
She sits patiently in millions of homes, an unremarkable cylinder commonly referred to as Alexa. But Amazon's new'virtual assistant' has been touted as nothing short of technological revolution. In response to spoken commands, she answers questions which previously required an internet search, can perform mundane domestic tasks such as turning on lights, and makes online purchases – through Amazon, obviously. Can it all be as innocent as it seems, particularly in an age rife with internet snooping? Some users have even reported'bone-chilling' cackles emanating from their speakers at random moments.
[D] Market prediction using NN • r/MachineLearning
Does anyone here have experience with using ML models to predict markets? I've found it very challenging so far, and I need help. This is how far I've gotten: Plots at the top, in light green background, are predictions using training data. Plots at the bottom, in light blue background, are predictions using testing data. Blue lines are historical prices of a stock/cryptocurrency. Red lines are predicted future 5 minute prices, made at time at which the blue line ends.
Non-artificial intelligence confers about ethical issues in AI
On April 9 and 10, the inaugural K&L Gates Conference on Ethics and Artificial Intelligence (AI) sought to bring to light some of the prevailing issues that surround artificial intelligence, including "effects on the workforce, social justice, fairness, privacy and many other sectors of society," as the conference …
UK Lawmakers Warn Against Tech Giants Dominating AI Industry
An influential body of U.K. lawmakers said regulators should stop major tech companies from dominating the field of artificial intelligence, and also … British antitrust regulators should be mindful that large datasets on which artificial intelligence depends on are not monopolized by a handful of large …