Entries from May 2018 ↓

• Spider Earrings with Gemstone Abdomen

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• The People Fell Down The Hill Chasing The Cheese Again
• The Science Behind Frixion Erasable Pens | Nippon.com
• Rescuing drowning children: How to know when someone is in trouble in the water.
• Why Did Birds Survive the Dinosaur Mass Extinction?
• The Thing Inside Your Cells That Might Determine How Long You Live – The New York Times
• She Found Comfort in a Brooklyn Diner, Then Lost Everything – The New York Times
• Poland offers US up to $2B for permanent military base – POLITICO
• Wyoming’s Yellowstone Region Brings Back Controversial Grizzly Bear Hunts
• How WIRED Lost $100,000 in Bitcoin | WIRED

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• Radiolab Valentine: Carl Sagan and Ann Druyan by Radiolab – Listen to music
• Twitter
  RT @RawCassini: ‘SATURN’ @ 2012-05-27 08:54 w/ ISSWA using MT2 & CL2, range 2,181,381 km. NASA/JPL-Caltech/SSI…
• Twitter
  RT @geminiimatt: "In the world we live in, data is destiny. For Black people, who have been disproportionately harmed by data-driven…
• An Open Letter to Facebook from the Data for Black Lives Movement
• Bitcoin backlash as ‘miners’ suck up electricity, stress power grids in Central Washington | The Seattle Times
• Coffee can help people have a more favorable view of their colleagues, according to new research

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• Rocketbook Everlast | Smart Notebook | Cloud Notebook– Rocketbook Australia
• F.B.I.’s Urgent Request: Reboot Your Router to Stop Russia-Linked Malware – The New York Times
• The Last Jedi: our spoiler-free review – The Verge
• Everything coming to Netflix, Amazon Prime, and HBO Now in June – The Verge
• Batteries – Maximizing Performance – Apple
• iPhone Battery and Performance – Apple Support
• Durable Briefcases & Computer Bags | Filson
• Why Anne of Green Gables Is Big in Japan | HuffPost
• U.S.C. President Agrees to Step Down Over Scandal Involving Gynecologist – The New York Times
• Review: the Google News app is a news junkie’s dream come true
• Forking hell! Is The Good Place the ultimate TV show for our times? | Television & radio | The Guardian

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• Forking hell! Is The Good Place the ultimate TV show for our times? | Television & radio | The Guardian
• How One Company Scammed Silicon Valley. And How It Got Caught. – The New York Times
  Theranos
• Gender Letter: Harvey Weinstein ‘Perp Walked’ Into the Future of #MeToo – The New York Times
• Neglect & Abuse of Unaccompanied Children by U.S. Customs and Border Protection – ACLU of San Diego and Imperial Counties
• Childhood neglect erodes the brain | Science | AAAS
• HHS Official Says Agency Lost Track of Nearly 1,500 Unaccompanied Minors | Trafficked in America | FRONTLINE | PBS | Official Site
• american tune lyrics – Google Search
• YouTube

  llen Toussaint – American Tune (Live on Austin City Limits)

• YouTube

  Simon & Garfunkel – American Tune (from The Concert in Central Park)

• Twitter
  RT @haymarketbooks:
• Alitas | Agencies & Ministries | Catholic Community Services of Southern AZ

  You can donate to Casa Alitas in Tucson, which provides care, short-term shelter and help to reunite with family members in the U.S. https://www.ccs-soaz.org/agencies-ministries/detail/alitas-aid-for-migrant-women-and-children

• From Aggressive Overtures to Sexual Assault: Harvey Weinstein’s Accusers Tell Their Stories | The New Yorker

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• [1805.09501] AutoAugment: Learning Augmentation Policies from Data
  In this paper, we take a closer look at data augmentation for images, and describe a simple procedure called AutoAugment to search for improved data augmentation policies. Our key insight is to create a search space of data augmentation policies, evaluating the quality of a particular policy directly on the dataset of interest. In our implementation, we have designed a search space where a policy consists of many sub-policies, one of which is randomly chosen for each image in each mini-batch. A sub-policy consists of two operations, each operation being an image processing function such as translation, rotation, or shearing, and the probabilities and magnitudes with which the functions are applied. We use a search algorithm to find the best policy such that the neural network yields the highest validation accuracy on a target dataset. Our method achieves state-of-the-art accuracy on CIFAR-10, CIFAR-100, SVHN, and ImageNet (without additional data). On ImageNet, we attain a Top-1 accuracy of 83.54%. On CIFAR-10, we achieve an error rate of 1.48%, which is 0.65% better than the previous state-of-the-art. On reduced data settings, AutoAugment performs comparably to semi-supervised methods without using any unlabeled examples. Finally, policies learned from one dataset can be transferred to work well on other similar datasets. For example, the policy learned on ImageNet allows us to achieve state-of-the-art accuracy on the fine grained visual classification dataset Stanford Cars, without fine-tuning weights pre-trained on additional data.
• [1805.09692] Been There, Done That: Meta-Learning with Episodic Recall
  Meta-learning agents excel at rapidly learning new tasks from open-ended task distributions; yet, they forget what they learn about each task as soon as the next begins. When tasks reoccur – as they do in natural environments – metalearning agents must explore again instead of immediately exploiting previously discovered solutions. We propose a formalism for generating open-ended yet repetitious environments, then develop a meta-learning architecture for solving these environments. This architecture melds the standard LSTM working memory with a differentiable neural episodic memory. We explore the capabilities of agents with this episodic LSTM in five meta-learning environments with reoccurring tasks, ranging from bandits to navigation and stochastic sequential decision problems.
• ML beyond Curve Fitting: An Intro to Causal Inference and do-Calculus
• [1705.07538] Infrastructure for Usable Machine Learning: The Stanford DAWN Project
  Despite incredible recent advances in machine learning, building machine learning applications remains prohibitively time-consuming and expensive for all but the best-trained, best-funded engineering organizations. This expense comes not from a need for new and improved statistical models but instead from a lack of systems and tools for supporting end-to-end machine learning application development, from data preparation and labeling to productionization and monitoring. In this document, we outline opportunities for infrastructure supporting usable, end-to-end machine learning applications in the context of the nascent DAWN (Data Analytics for What’s Next) project at Stanford.
• Lawrence Hidden Valley Camp
• Review: Half a year later, the Google Pixel 2 XL has proven itself a worthy successor | 9to5Google
• NervanaSystems · GitHub
  Intel
• Intel AI Lab open-sources library for deep learning-driven NLP | VentureBeat
• Scientists discovered massive hidden canyons in Antarctica that could spell bad news for the rest of the planet – Quartz
• ICE Plans to Start Destroying Records of Immigrant Abuse, Including Sexual Assault and Deaths in Custody | American Civil Liberties Union
• Federal Agencies Lost Track of Nearly 1,500 Migrant Children Placed With Sponsors – The New York Times
• ROBIN’S BOOKS | Shoving Books Into Readers’ Hands Since 1958
• Here’s Amazon’s explanation for the Alexa eavesdropping scandal – Recode
• Pacific plastic dump far larger than feared: study

  The vast dump of plastic waste swirling in the Pacific ocean is now bigger than France, Germany and Spain combined: https://buff.ly/2FYy5hK

  #EndOceanPlastic #UseLess #WasteLess https://twitter.com/MikeHudema/status/999626580971458560/photo/1

• Behind the Scenes of Harvey Weinstein’s Impending Arrest | The New Yorker
• Roaring Forties Blue | Murray’s Cheese
• FBI repeatedly overstated encryption threat figures to Congress, public – The Washington Post
• Opinion | The Democrats’ Midterm Dilemma – The New York Times
• Instapaper says it will temporarily go offline in Europe due to GDPR | 9to5Mac

  GDPR requires that users opt-in to all commercial use of personal data.

• minimaxir/textgenrnn: Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
  Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
• Meredith Lee on Twitter: "Calling all #opendata #waterwednesday #openscience #collaboration enthusiasts: join the #CAWaterDataChallenge now💧📈 https://t.co/MRIBxcV5Vp… https://t.co/4HzF3vN5ne"
• [1802.06765] Interpretable VAEs for nonlinear group factor analysis
  Deep generative models have recently yielded encouraging results in producing subjectively realistic samples of complex data. Far less attention has been paid to making these generative models interpretable. In many scenarios, ranging from scientific applications to finance, the observed variables have a natural grouping. It is often of interest to understand systems of interaction amongst these groups, and latent factor models (LFMs) are an attractive approach. However, traditional LFMs are limited by assuming a linear correlation structure. We present an output interpretable VAE (oi-VAE) for grouped data that models complex, nonlinear latent-to-observed relationships. We combine a structured VAE comprised of group-specific generators with a sparsity-inducing prior. We demonstrate that oi-VAE yields meaningful notions of interpretability in the analysis of motion capture and MEG data. We further show that in these situations, the regularization inherent to oi-VAE can actually lead to improved generalization and learned generative processes.

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• Error running Object Detection API on Google ML – Stack Overflow
• JetPens Fine Tip Gel Pen Sampler – Black – JetPens.com
• JetPens Beginner Fountain Pen Sampler – JetPens.com
• Zebra Zensations Fountain Pens – JetPens.com
• Platinum Preppy Fountain Pens – JetPens.com
• Twitter
  RT @dougmcgray: 58 people shot, 851 people injured, and it seems like we’ve already forgotten about it. @amandafortini tries to fig…
• What Happened in Vegas — The California Sunday Magazine
• Julia Louis-Dreyfus to receive the 2018 Mark Twain Prize for American Humor – The Washington Post
• Ira Glass’s Commencement Speech at the Columbia Journalism School Graduation – This American Life
• Twitter
  RT @summerbrennan: A favorite Roth quote:
• Donald Trump cannot block anyone on Twitter, court rules | US news | The Guardian

  A district court in New York has ruled that Donald Trump cannot block people on Twitter, because it violates their first amendment rights to participate in a “public forum”.

• Play with Kubernetes Classroom
• Introducing Play With Kubernetes – Docker Blog
• Why I’m Kind Of Tired Of The "Smartest Man In The Room"
• Python Programming Tutorials
• (5) Woman, Power & Modern Feminism – Chimamanda Ngozi Adichie & Professor Mary Beard – YouTube
• Twitter
  RT @mims: questions that answer themselves
• Blood Will Tell, Part I: Who Killed Mickey Bryan? – The New York Times
• Mueller investigation polling: most don’t know crimes have been found – Vox

  17 indictments and five guilty pleas so far.

• Google Cloud Platform Blog: Introducing GCP’s new interactive CLI
• Twitter
  RT @GCPcloud: Receive auto-prompts and in-line help for gcloud, gsutil, bq and kubectl commands as you type, using our new comman…
• The Oxygen of Amplification | Data & Society
• Twitter
  RT @janethaven: New @datasociety report by @wphillips49 analyzes interviews with 50+ journalists to show how hate groups use manipu…

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• [1805.08498] Implicit Reparameterization Gradients
  By providing a simple and efficient way of computing low-variance gradients of continuous random variables, the reparameterization trick has become the technique of choice for training a variety of latent variable models. However, it is not applicable to a number of important continuous distributions. We introduce an alternative approach to computing reparameterization gradients based on implicit differentiation and demonstrate its broader applicability by applying it to Gamma, Beta, Dirichlet, and von Mises distributions, which cannot be used with the classic reparameterization trick. Our experiments show that the proposed approach is faster and more accurate than the existing gradient estimators for these distributions.
• Twitter chooses Google Cloud: What it means for enterprise cloud adoption – TechRepublic
• Women’s Travel Pants – SCOTTeVEST
• Amazon Pushes Facial Recognition to Police. Critics See Surveillance Risk. – The New York Times
• Google Cloud Platform and Confluent partner to deliver a managed Apache Kafka service | Google Cloud Big Data and Machine Learning Blog  |  Google Cloud
• How to inspect a Tensorflow .tfrecord file? – Stack Overflow
• The statistical significance filter leads to overoptimistic expectations of replicability – Statistical Modeling, Causal Inference, and Social Science
  Treating a result as publishable just because the p-value is less than 0.05 leads to overoptimistic expectations of replicability. These overoptimistic expectations arise due to Type M(agnitude) error: when underpowered studies yield significant results, effect size estimates are guaranteed to be exaggerated and noisy. These effects get published, leading to an overconfident belief in replicability. We demonstrate the adverse consequences of this statistical significance filter by conducting six direct replication attempts (168 participants in total) of published results from a recent paper. We show that the published claims are so noisy that even non-significant results are fully compatible with them. We also demonstrate the contrast between such small-sample studies and a larger-sample study (100 participants); the latter generally yields less noisy estimates but also a smaller effect size, which looks less compelling but is more realistic. We make several suggestions for improving best practices in psycholinguistics and related areas.

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• How to Survive a Mountain Lion Attack
• Rudy Giuliani won deal for OxyContin maker to continue sales of drug behind opioid deaths | US news | The Guardian
• You want to be pregnant. You’re depressed. A tough choice lies ahead | Life and style | The Guardian
• Twitter
  RT @dankohn1: Call for Proposals for #KubeCon Shanghai (11/14-15) and Seattle (12/11-13) is now live! Apply for either or both fr…
• Call for Proposals (CFP) – KubeCon CloudNativeCon North America 2018
• fans & foes of today’s Supreme Court decision say it will make arbitration agreements w/class action waivers ~ubiquitous~ because it eliminates an employer’s biggest risk https://www.wired.com/story/supreme-court-rules-against-workers-in-arbitration-case
• Supreme Court Rules Against Workers In Arbitration Case | WIRED
• After decades of dwarfs and elves, writers of color redefine fantasy – CSMonitor.com
• Former Uber Engineer’s Lawsuit Claims Sexual Harassment – The New York Times
• The Line Between Big Tech and Defense Work | WIRED
• ‘The Business of War’: Google Employees Protest Work for the Pentagon – The New York Times
• Could the Fuji XT2 Be the Best Camera Ever Made? – John Raymond Mireles – Medium
• This app hacked the iPhone’s dual camera system, and you’ve never seen anything like it – BGR
• Myna Mahila Foundation – Myna Mahila
• Why Menstrual Equity Is Important For Women In The US
• Twitter
  RT @simongerman600: Schools tend to have a wall #map of their country hanging somewhere. If your school is in Chile you better have hig…
• Twitter
  RT @exploreml: Exciting stuff!
  @GCPcloud’s ML Engine now supports TPUs in beta:

  Here’s a tutorial:…

• Cloud ML Engine adds Cloud TPU support for training | Google Cloud Big Data and Machine Learning Blog  |  Google Cloud
  RT @exploreml: Exciting stuff!
  @GCPcloud’s ML Engine now supports TPUs in beta:

  Here’s a tutorial:…

• Twitter
  RT @StephenGParker: This is the most beautiful corn I have ever seen. It is a Native American variety called I believe ‘Glass Gem Corn’…
• Rare Disease Geneticist: A Profile of Uta Francke | The Scientist Magazine®
• Analyze your images in @ProjectJupyter with #ImageJ and interactively visualize with #itkwidgets thanks to a #hackathon supported by @UCBIDS @stefanvdwalt @cziscience @thefreemanlab @ctrueden @FijiSc https://github.com/InsightSoftwareConsortium/itk-jupyte

  Analyze your images in @ProjectJupyter with #ImageJ and interactively visualize with #itkwidgets thanks to a #hackathon supported by @UCBIDS @stefanvdwalt @cziscience @thefreemanlab @ctrueden @FijiSc https://github.com/InsightSoftwareConsortium/itk-jupyter-widgets/blob/master/examples/ImageJImgLib2.ipynb https://twitter.com/thewtex/status/998589676461191170/video/1

• ARGENT | Smarter Workwear for Women
• Women’s SCOTTeVEST Clothing –
• Women’s Insulated Jacket – SCOTTeVEST
  The OTG (Off The Grid) Jacket for women features two front Rapid Access Panelsâ„¢ can hold a full size laptop without showing bumps or bulges. The OTG truly marries fashion with function and will be your new wardrobe staple that is ideal for cooler climates.
• Language Modeling with Ngrams
• [1803.11175] Universal Sentence Encoder
  We present models for encoding sentences into embedding vectors that specifically target transfer learning to other NLP tasks. The models are efficient and result in accurate performance on diverse transfer tasks. Two variants of the encoding models allow for trade-offs between accuracy and compute resources. For both variants, we investigate and report the relationship between model complexity, resource consumption, the availability of transfer task training data, and task performance. Comparisons are made with baselines that use word level transfer learning via pretrained word embeddings as well as baselines do not use any transfer learning. We find that transfer learning using sentence embeddings tends to outperform word level transfer. With transfer learning via sentence embeddings, we observe surprisingly good performance with minimal amounts of supervised training data for a transfer task. We obtain encouraging results on Word Embedding Association Tests (WEAT) targeted at detecting model bias. Our pre-trained sentence encoding models are made freely available for download and on TF Hub.
• [1804.07754] Learning Semantic Textual Similarity from Conversations
  We present a novel approach to learn representations for sentence-level semantic similarity using conversational data. Our method trains an unsupervised model to predict conversational input-response pairs. The resulting sentence embeddings perform well on the semantic textual similarity (STS) benchmark and SemEval 2017’s Community Question Answering (CQA) question similarity subtask. Performance is further improved by introducing multitask training combining the conversational input-response prediction task and a natural language inference task. Extensive experiments show the proposed model achieves the best performance among all neural models on the STS benchmark and is competitive with the state-of-the-art feature engineered and mixed systems in both tasks.
• Google AI Blog: Advances in Semantic Textual Similarity
  The recent rapid progress of neural network-based natural language understanding research, especially on learning semantic text representations, can enable truly novel products such as Smart Compose and Talk to Books. It can also help improve performance on a variety of natural language tasks which have limited amounts of training data, such as building strong text classifiers from as few as 100 labeled examples.

  Below, we discuss two papers reporting recent progress on semantic representation research at Google, as well as two new models available for download on TensorFlow Hub that we hope developers will use to build new and exciting applications.

• Twitter
  RT @ahmetb: GKE v1.10 is out with so many new features!

  $ gcloud container clusters upgrade \
  –master –cluster-version=1…

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• MPI Documents
• Germany Acts to Tame Facebook, Learning From Its Own History of Hate – The New York Times
• Camera rumors 2018: the biggest and best camera rumors around: Fujifilm rumors 2018 | TechRadar
• François Couperin – Les Barricades Mystérieuses
• Ian Evans — Oceans Deeply
• Pew Environment on Twitter: "Explorers just returned from the Gulf of Mexico with "unknown species, photos of unexplored environments and videos of never-before-seen wildlife behavior." News via @oceansdeeply: https://t.co/qv2EnQuS30… https://t.co/4gFfF
• FUJIFILM GFX & X Series Camera Lineup
• The First Fujifilm Lenses You Should Buy: Reviews by Wirecutter | A New York Times Company
• The Best Point-and-Shoot Camera: Reviews by Wirecutter | A New York Times Company
• Beyoncé – Crazy In Love / Freedom / Lift every voice and sing / Formatio…
• signs, easy to start, surprisingly difficult to… – distracted

  A classic. “Signs: Easy to start, surprisingly difficult to finish.” http://mendel.tumblr.com/post/69216872937/signs-easy-to-start-surprisingly-difficult-to

• Some endangered frogs may be leaping back from extinction – The Washington Post
• #WOMENSART on Twitter: "’The Skate Girls of Kabul’ photographic series by Jessica Fulford-Dobson featuring girls from the Afghan capital, who are not allowed to ride bikes, so are learning to skateboard instead as a way to bond and liberate themselves fro
• Meghan Markle and the Bicultural Blackness of the Royal Wedding
• Texas school had a shooting plan, armed officers and practice. And still 10 people died. – The Washington Post
• 10 Best URL Shortener Services For Your Domain | Customize Apps With Domains at iwantmyname
• What Happens Next Will Amaze You
• Fujifilm FUJINON XF 35mm f/2 R WR Standard Lens for Fujifilm X-Mount System Cameras Black 16481878 – Best Buy

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