Daily Archives: November 5, 2019
Questioning The Long-Term Importance Of Big Data In AI
No asset is more prized in today’s digital economy than data. It has become widespread to the point of cliche to refer to data as “the new oil.” As one recent Economist headline put it, data is “the world’s most valuable resource.”
Data is so highly valued today because of the essential role it plays in powering machine learning and artificial intelligence solutions. Training an AI system to function effectively—from Netflix’s recommendation engine to Google’s self-driving cars—requires massive troves of data.
The result has been an obsession with bigger and bigger data. He with the most data can build the best AI, according to the prevailing wisdom. Read More
Identifying Nuances in Fake News vs. Satire: Using Semantic and Linguistic Cues
The blurry line between nefarious fake news and protected-speech satire has been a notorious struggle for social media platforms. Further to the efforts of reducing exposure to misinformation on social media, purveyors of fake news have begun to masquerade as satire sites to avoid being demoted. In this work, we address the challenge of automatically classifying fake news versus satire. Previous work have studied whether fake news and satire can be distinguished based on language differences. Contrary to fake news, satire stories are usually humorous and carry some political or social message. We hypothesize that these nuances could be identified using semantic and linguistic cues. Consequently, we train a machine learning method using semantic representation, with a state-of-the-art contextual language model, and with linguistic features based on textual coherence metrics. Empirical evaluation attests to the merits of our approach compared to the language-based baseline and sheds light on the nuances between fake news and satire. As avenues for future work, we consider studying additional linguistic features related to the humor aspect, and enriching the data with current news events, to help identify a political or social message. Read More
The Eighty Five Percent Rule for optimal learning
Researchers and educators have long wrestled with the question of how best to teach their clients be they humans, non-human animals or machines. Here, we examine the role of a single variable, the difficulty of training, on the rate of learning. In many situations we find that there is a sweet spot in which training is neither too easy nor too hard, and where learning progresses most quickly. We derive conditions for this sweet spot for a broad class of learning algorithms in the context of binary classification tasks. For all of these stochastic gradient-descent based learning algorithms, we find that the optimal error rate for training is around 15.87% or, conversely, that the optimal training accuracy is about 85%. We demonstrate the efficacy of this ‘Eighty Five Percent Rule’ for artificial neural networks used in AI and biologically plausible neural networks thought to describe animal learning. Read More
How to Spy on Your Neighbors With a USB TV Tuner
A TV-tuning USB dongle and free software let you hear the radio signals emitted by computer screens, TVs, smartphones — even keyboards.
“Every device that you own is screaming its name into the infinite void,” said security researcher Melissa Elliott this past Saturday (Aug. 3) at the DEF CON hacker conference in Las Vegas. Read More
The Fantasy of Opting Out
Those who know about us have power over us. Obfuscation may be our best digital weapon.
Consider a day in the life of a fairly ordinary person in a large city in a stable, democratically governed country. She is not in prison or institutionalized, nor is she a dissident or an enemy of the state, yet she lives in a condition of permanent and total surveillance unprecedented in its precision and intimacy. Read More
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