Collaborating Authors


The 8 best '90s TV shows on Netflix you'll really, really want to watch


While fanny packs, the Spice Girls, and bowl cuts all made their mark in the '90s, they weren't the only things that helped define the decade. The TV shows of the era also left behind a legacy, and -- lucky for those of us who want to temporarily reverse time for a respite from today -- a handful of them are available for streaming right now. Netflix is the place to be if you want to hop back more than 20 years and journey into space, solve a mystery, or visit San Fransisco. Whether you're looking to rediscover an old favorite or figure out what classic to try for the first time, we've got you covered. The Halliwell sisters -- Prue, Piper, and Phoebe -- are just normal girls who live in San Francisco, except for one little thing: They're secretly witches.

GPT-3 Creative Fiction


What if I told a story here, how would that story start?" Thus, the summarization prompt: "My second grader asked me what this passage means: …" When a given prompt isn't working and GPT-3 keeps pivoting into other modes of completion, that may mean that one hasn't constrained it enough by imitating a correct output, and one needs to go further; writing the first few words or sentence of the target output may be necessary.

The 84 biggest flops, fails, and dead dreams of the decade in tech


The world never changes quite the way you expect. But at The Verge, we've had a front-row seat while technology has permeated every aspect of our lives over the past decade. Some of the resulting moments -- and gadgets -- arguably defined the decade and the world we live in now. But others we ate up with popcorn in hand, marveling at just how incredibly hard they flopped. This is the decade we learned that crowdfunded gadgets can be utter disasters, even if they don't outright steal your hard-earned cash. It's the decade of wearables, tablets, drones and burning batteries, and of ridiculous valuations for companies that were really good at hiding how little they actually had to offer. Here are 84 things that died hard, often hilariously, to bring us where we are today. Everyone was confused by Google's Nexus Q when it debuted in 2012, including The Verge -- which is probably why the bowling ball of a media streamer crashed and burned before it even came to market.

Conditional Self-Attention for Query-based Summarization Artificial Intelligence

Self-attention mechanisms have achieved great success on a variety of NLP tasks due to its flexibility of capturing dependency between arbitrary positions in a sequence. For problems such as query-based summarization (Qsumm) and knowledge graph reasoning where each input sequence is associated with an extra query, explicitly modeling such conditional contextual dependencies can lead to a more accurate solution, which however cannot be captured by existing self-attention mechanisms. In this paper, we propose \textit{conditional self-attention} (CSA), a neural network module designed for conditional dependency modeling. CSA works by adjusting the pairwise attention between input tokens in a self-attention module with the matching score of the inputs to the given query. Thereby, the contextual dependencies modeled by CSA will be highly relevant to the query. We further studied variants of CSA defined by different types of attention. Experiments on Debatepedia and HotpotQA benchmark datasets show CSA consistently outperforms vanilla Transformer and previous models for the Qsumm problem.

Is Siri spying on me? My iPad has shifted to Spanish ads after conversations in my home

USATODAY - Tech Top Stories

I watch most TV shows and movies on my iPad these days, and something strange happened recently. My iPad – or rather apps such as Hulu and Bravo linked via Apple TV on my iPad – started showing me commercials in Spanish. That was interesting, since I hadn't touched the language settings, watched any shows in Spanish, or done any kind of internet activity in another language. But even more curious, was what had changed when the new commercials popped up. We had just moved to a more Spanish-speaking area of Oakland, California.

Senior Software Engineer, Machine Learning Infrastructure


Netflix is driven by data and algorithms (along with tons of great TV shows and movies). If you are in the engineering, data, and / or machine learning fields, this is an amazing place to be.About usWe're a small team of engineers who envision, develop, and manage the systems and workflows that enable a diverse group of users at Netflix to apply machine learning to a wide range of business problems. To make this possible, we need to address questions like these:* What's the best way to take a prototype in R or Python and move it into ongoing production use at scale?* How can we help data scientists reproduce their research and be more collaborative?* How do we build flexible pipelines that can rapidly evolve to handle new technologies and modeling approaches?* How can we make various types of data, such as natural language, video assets, and tabular data easily available for machine learning pipelines?We don't think these questions are just technical challenges - they are also a product challenge: How can we provide the most delightful and empowering user experience for the users of our platform.

10 most important tech trends of the decade


Apple CEO Steve Jobs unveils the iPad on January 27, 2010, in San Francisco. When I hustled out of CNET headquarters in San Francisco on May 26, 2010, and slipped into a rental car with two of my co-workers to head to a meeting across the Bay, one of them slipped me a copy of The Wall Street Journal and pointed to a headline that announced Apple had passed Microsoft to become the world's most valuable tech company. "What do you think of that?" she said. "Unreal," I responded, shaking my head. Just over a decade earlier, Apple had nearly been on its deathbed and needed a $150 million investment from Microsoft simply to stay alive.

Jeff Bezos' master plan


What the Amazon founder and CEO wants for his empire and himself, and what that means for the rest of us. Where in the pantheon of American commercial titans does Jeffrey Bezos belong? Andrew Carnegie's hearths forged the steel that became the skeleton of the railroad and the city. John D. Rockefeller refined 90 percent of American oil, which supplied the pre-electric nation with light. Bill Gates created a program that was considered a prerequisite for turning on a computer. At 55, Bezos has never dominated a major market as thoroughly as any of these forebears, and while he is presently the richest man on the planet, he has less wealth than Gates did at his zenith. Yet Rockefeller largely contented himself with oil wells, pump stations, and railcars; Gates's fortune depended on an operating system. The scope of the empire the founder and CEO of Amazon has built is wider. Indeed, it is without precedent in the long history of American capitalism. More product searches are conducted ...

Intercon World Keynote Dr. Ganapathi Pulipaka Receives a Top 50 Technology Leader Award for His Contributions to AI, Machine Learning, Mathematics, and Data Science


Dr. Ganapathi Pulipaka was a recipient of the Top 50 Technology Leader awards for recognition of his contribution to artificial intelligence, machine learning, and data science; for the past five years on Twitter as a machine learning and data science influencer; as a contributor to thought leadership and of project implementation articles on Medium, Data Driven Investor, LinkedIn, GitHub; as a best-selling author of two books on Amazon - "The Future of Data Science and Parallel Computing: A Road to Technological Singularity," published on June 29, 2018, and "Big Data Appliances for In-Memory Computing: A Real-World Research Guide for Corporations to Tame and Wrangle Their Data," published Dec. 8, 2015 - and other eBooks that have reached all-time high rankings from the world's largest book ratings authority (featured on Forbes), BookAuthority; and also for writing another 400 research papers as part of academic research programs for PostDoc and PhD. He is an American data scientist and AI luminary who has been featured in top-tier magazines and news and industry publications and was a speaker for multiple media distribution networks and some of the top media station affiliates, including ABC, FoxNews, NBC, Yahoo Finance, MarketWatch, The CW, VentureBeat, MirrorReview, CIOReview, SAP, Erie News Now, USA Today, Double T 97.3 Lubbock's Radio station, 100.7 KFM BFM San Diego, KITV, Telemundo Lubbock 46, AZCentral, Insights Success, NewsOk, Pittsburgh Post-Gazette, MarketWatch, and Ask.

A Look Back At How Google's AI Sees A Week Of Television News And The World Of AI Video Understanding


This past May I worked with the Internet Archive's Television News Archive to apply Google's suite of cloud AI APIs to analyze a week of television news coverage to examine how AI "sees" television and what insights we might gain into the world of non-consumptive deep learning-powered video understanding. Using Google's video, image, speech and natural language APIs as lenses, more than 600GB of machine annotations trace how deep learning algorithms today understand video. What lessons can we learn about the state of AI today and how it can be applied in creative ways to catalog and explore the vast world of video? Working with the Internet Archive's Television News Archive, a week of television news was selected covering CNN, MSNBC and Fox News and the morning and evening broadcasts of San Francisco affiliates KGO (ABC), KPIX (CBS), KNTV (NBC) and KQED (PBS) from April 15 to April 22, 2019, totaling 812 hours of television news. This week was selected due to it having two major stories, one national (the Mueller report release on April 18th) and one international (the Notre Dame fire on April 15th).