1. Do androids dream of electric beats? How AI is changing music for good
The first testing sessions for SampleRNN – an artificially intelligent software developed by computer scientist duo CJ Carr and Zach Zukowski, AKA Dadabots – sounded more like a screamo gig than a machine-learning experiment. “When it produced its first output,” Carr tells me over email, “I was expecting to hear silence or noise because of an error we made, or else some semblance of singing.
Artificial intelligence is already used in music by streaming services such as Spotify, which scan what we listen to so they can better recommend what we might enjoy next. Read More
2. [1810.08669] Ockham’s Razor in Memetic Computing: Three Stage Optimal Memetic Exploration
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3. [1810.08680] Lightweight Convolutional Approaches to Reading Comprehension on SQuAD
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4. [1810.09084] A general learning system based on neuron bursting and tonic firing
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5. [1810.09302] BioSentVec: creating sentence embeddings for biomedical texts
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6. Fluid Annotation: An Exploratory Machine Learning–Powered Interface for Faster Image Annotation
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7. These are the skills that your kids will need for the future (Hint: It’s not coding)
The jobs of the future will involve humans collaborating with other humans to design work for machines, and value will shift from cognitive to social skills. Today, curriculums have shifted to focus on a more global and digital world, like cultural history, basic computer skills, and writing code.
Yet the challenges that our kids will face will be much different from those we faced growing up and many of the things a typical student learns in school today will no longer be relevant by the time he or she graduates college. Read More
8. Import AI: 117: Surveillance search engines; harvesting real-world road data with hovering drones; and improving language with unsupervised pre-training
Chinese researchers pursue state-of-the-art lip-reading with massive dataset:…What do I spy with my camera eyes. Now I can figure out what you are saying…Researchers with the Chinese Academic of Sciences and Huazhong University of Science and Technology have created a new dataset and benchmark for “lip-reading in the wild” for Mandarin. Dataset details: The lipreading dataset contains 745,187 distinct samples from more than 2,000 speakers, grouped into 1,000 classes, where each class corresponds to the syllable of a Mandarin word composed of one or several Chinese characters. Read More
9. How Artificial Intelligence Enhances the Home Buying Experience
In this special guest feature, Roy Dekel, CEO and Co-Founder of SetSchedule, discusses how AI is transforming the residential real estate industry by enhancing the home buying experience. This new technology can help make the human connections that make the home buying process less painful and more fulfilling. From finding the right agent among the thousands who serve your area to sifting through hundreds of properties on dozens of different websites and arranging plus attending showings. Read More
10. Forecasting financial series using clustering methods and support vector regression
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11. Christie’s, Trying to Be Relevant, Puts AI Art on the Block
With their eyes trained on a gilded frame containing a smeared, half-formed image of a distinguished gentleman, a small group of potential bidders gathered Friday night over cocktails at Christie’s New York and heard the pitch: here was the first portrait generated by an algorithm to come up for auction. The portrait, produced by artificial intelligence, hung on the wall opposite an Andy Warhol print and just to the right of a bronze work by Roy Lichtenstein. The work — estimated at $7,000-$10,000 — was a collaboration by the members of Obvious, a French trio composed of a student of machine learning and two business school graduates, none of whom have a background in art. Read More
12. Learning Complex Goals with Iterated Amplification
We’re proposing an AI safety technique called iterated amplification that lets us specify complicated behaviors and goals that are beyond human scale, by demonstrating how to decompose a task into simpler sub-tasks, rather than by providing labeled data or a reward function.
If we want to train an ML system to perform a task, we need a training signal — a way to evaluate how well it is doing in order to help it learn. If we don’t have a training signal we can’t learn the task, and if we have the wrong training signal, we can get unintended and sometimes dangerous behavior. Read More
13. Autonomous farm produces food with robot workers
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14. Applying Customer Feedback: How NLP & Deep Learning Improve Uber’s Maps
By Chun-Chen Kuo, Livia Yanez, & Jeffrey Yun
High quality map data powers many aspects of the Uber trip experience.
NLP and ML algorithms
The requirement for detecting errors in a map data type can be modeled as a classification problem in machine learning, in which a classification model will predict the probability that a ticket is related to errors in the map data type based on its learning from training data. For free-form text, a naive approach would be to use a pre-defined vocabulary to encode by word frequency. Read More
15. Jobs for humans in the robot age
Maybe you didn’t grow up dreaming of being an “augmented reality journey builder” or “master of edge computing” — or a “cyber calamity forecaster. ” But someone will.
The big picture: Jobs of the future will be heavy on the use of algorithms, automation and AI; customer experience; environment; fitness and wellness; health care; legal and financial services; transport; and work culture. Read More
16. US self-driving school bus test halted
French-based transport firm Transdev has been ordered to stop an “unlawful” test of a driverless school bus in Florida by US regulators.
The regulator said the firm had not been authorised to transport schoolchildren in Florida, and said the test was “irresponsible” and “inappropriate”.
But the National Highway Traffic Safety Administration (NHTSA) said the test of the EZ10 Generation II driverless shuttle in the Babcock Ranch community in Florida was outside the scope of what the firm had been authorised to do. Read More
17. AI’s Potential to Diagnose and Treat Mental Illness
The United States faces a mental health epidemic. Nearly one in five American adults suffers from a form of mental illness. Digital solutions – many with artificial intelligence (AI) at their core – offer hope for reversing the decline in our mental wellness. Read More
18. Robotic Raven Gains Altitude
Inspired by the beauty and flying ability of birds, Leonardo da Vinci strived centuries ago to create a human-powered flapping-wing flying machine. But his designs, which da Vinci explored in his Codex on the Flight of Birds, were never developed in any practical way. James Clark School of Engineering have been moving ever closer to faithfully imitating bird flight with Robo Raven, the first bird-inspired unmanned aerial vehicle (UAV) that has successfully flown with independent wing control. Read More
19. “AI Clinician” Makes Treatment Plans for Patients With Sepsis
Most experiments with artificial intelligence in medicine thus far have worked on the diagnostic side. AI systems have used computer vision to examine images like X-rays or pathology slides, and they have combed through data in electronic medical records to spot subtle patterns that humans can miss.
“It’s not mimicking the perceptual ability of the doctor, where the doctor sees certain symptoms and says the patient is going into septic shock,” says Aldo Faisal, an associate professor of bioengineering and computing at Imperial College London and one of the paper’s authors. Read More
20. AI can’t replace doctors. But it can make them better.
Several years ago Vinod Khosla, the Silicon Valley investor, wrote a provocative article titled “Do We Need Doctors or Algorithms?” Khosla argued that doctors were no match for artificial intelligence. Doctors banter with patients, gather a few symptoms, hunt around the body for clues, and send the patient off with a prescription.
Consider what AI could do for asthma, the most common chronic medical disease in childhood. Read More
21. Introducing the NVIDIA Self-Driving Safety Report | NVIDIA Blog
Autonomous vehicles promise to reduce traffic accidents by replacing unpredictable human drivers with artificial intelligence.
To help answer that, NVIDIA has released the Self-Driving Safety Report. Our report details how compute performance translates to safety at all stages, from initial data collection to public road testing. Read More
22. Researchers discover security flaws in leading IoT operating system
Researchers from IT security firm Zimperium have discovered vulnerabilities within leading IoT operating system FreeRTOS that could allow attackers to crash IoT devices used in smart homes and life-critical applications. In November 2017, stewardship of the FreeRTOS kernel (and its components) was transferred to Amazon Web Services (AWS).
Karliner says these vulnerabilities ‘allow an attacker to crash the device, leak information from the device’s memory, and remotely execute code on it, thus completely compromising it’. Read More
23. Why China Can Do AI More Quickly and Effectively Than the US
When Enrico Fermi decided to leave Benito Mussolini’s Italy and emigrate to the United States, he changed the global balance of power. After arriving in the US, Fermi led the world’s first self-sustaining nuclear reaction at the University of Chicago and played an indispensable role in the Manhattan Project, which led to the end of World War II in the Pacific and laid the groundwork for a new world order and America’s prominent role. Chinese companies are equal to or ahead of their American counterparts in each of these areas. Read More
24. 3 Smart Things About Animal-Inspired Robotics
Though it has a brain, the lamprey—an eel-like beast—doesn’t need it to wiggle about the deep. Neurons along the creature’s spinal cord can act independently via signals called central pattern generators, or CPGs. A slithering machine inspired by the lamprey, the AmphiBot, has 10 body modules, each with its own onboard computer that mimics a CPG. Read More
25. The Case for Giving Robots an Identity
The first time Stephanie Dinkins met Bina48, in 2014, she worried the thing was dead. Dinkins caught the robot’s stare and knew she’d found her muse. Her subject, though possessed of human thoughts, seemed more interested in talking about being a robot. Read More
26. The AI Cold War That Could Doom Us All
In the spring of 2016, an artificial intelligence system called AlphaGo defeated a world champion Go player in a match at the Four Seasons hotel in Seoul. And the technology that had emerged victorious was even more foreign: a form of AI called machine learning, which uses large data sets to train a computer to recognize patterns and make its own strategic choices. ”In China, by contrast, 280 million people watched AlphaGo win. Read More
27. Scientists Help Robots ‘Evolve.’ Weirdness Ensues
Evolution is a trip. Some animals fly with feathered wings, others with membranes stretched between fingers. Some run on two legs, others four. Read More