NEW AI IMAGING TECHNIQUE RECONSTRUCTS PHOTOS WITH REALISTIC RESULTS
To prepare to train their neural network, the team first generated 55,116 masks of random streaks and holes of arbitrary shapes and sizes for training. They also generated nearly 25,000 for testing. These were further categorized into six categories based on sizes relative to the input image, in order to improve reconstruction accuracy. Source: nvidia.com
MIT RESEARCHERS HAVE DEVELOPED A ‘SYSTEM FOR DREAM CONTROL’
There is a borderland between waking life and the uncharted wilderness of sleep that we all traverse each night, but we rarely stop to marvel at the strangeness of this liminal world. If we do, we find that it is full of hallucinations both wonderful and terrifying, a mental goulash of reality and fantasy. Source: vice.com
BASIC INCOME IS ALREADY TRANSFORMING LIFE AND WORK IN A POSTINDUSTRIAL CANADIAN CITY
Something is happening in the postindustrial pocket of Hamilton, Ontario, a 45-minute drive from Toronto’s gleaming skyscrapers. In its squat downtown, where payday loan services with names like Money Mart and Cash 4 U compete across the street from each other and a beware of dog sign hangs from a church gate, a potentially transformational future is on trial.
Read moreTHE 20 YEAR OLD ENTREPRENEUR IS A LIE
Forget what you’ve heard about 22-year-old wunderkinds, sitting in the corner offices of their wildly popular Silicon Valley startups — if you want to find the most successful entrepreneurs, you have to go back a few decades. Source: mit.edu
ACCELERATING DEEP NEUROEVOLUTION: TRAIN ATARI IN HOURS ON A SINGLE PERSONAL COMPUTER
We recently published an article announcing five papers on deep neuroevolution, including the discovery that genetic algorithms can solve deep reinforcement learning problems as well as popular alternatives, such as deep Q-learning and policy gradients. That work follows on Salimans et al. 2017, which showed the same for evolution strategies (ES), another neuroevolution algorithm. We further described how ES can be improved by adding exploration in the form of a pressure for agents to be novel, and how ES relates to gradient descent.
Read moreNETFLIX FLAMESCOPE
We’re excited to release FlameScope: a new performance visualization tool for analyzing variance, perturbations, single-threaded execution, application startup, and other time-based issues. It has been created by the Netflix cloud performance engineering team and just released as open source, and we welcome help from others to develop the project further. (If it especially interests you, you might be interested in joining Netflix to work on it and other projects.)
Read moreDATA SCIENCE AND THE ART OF PRODUCING ENTERTAINMENT AT NETFLIX
Netflix has released hundreds of Originals and plans to spend $8 billion over the next year on content. Creators of these stories pour their hearts and souls into turning ideas into joy for our viewers. The sublime art of doing this well is hard to describe, but it necessitates a careful orchestration of creative, business and technical decisions. Here we will focus on the latter two—business & technical decisions like planning budgets, finding locations, building sets, and scheduling guest actors that enable the creative act of connecting with viewers.
Read moreWHY IS THE HUMAN BRAIN SO EFFICIENT? MASSIVE PARALLELISM
Which has more problem-solving power—the brain or the computer? Given the rapid advances in computer technology in the past decades, you might think that the computer has the edge. Indeed, computers have been built and programmed to defeat human masters in complex games, such as chess in the 1990s and recently Go, as well as encyclopedic knowledge contests, such as the TV show Jeopardy!
Read moreFLUREE DB – A SCALABLE BLOCKCHAIN DATABASE
Develop blockchain applications with a powerful graph database. FlureeDB’s blockchain database allows developers to build decentralized applications on blockchain technology. Support for GraphQL, JavaScript, and React built in. Source: flur.ee
THE 315-YEAR-OLD SCIENCE EXPERIMENT
The most arrogant astronomer in Switzerland in the mid-20th century was a solar physicist named Max Waldmeier. Colleagues were so relieved when he retired in 1980 that they nearly retired the initiative he led as director of the Zurich Observatory. Waldmeier was in charge of a practice that dated back to Galileo and remains one of the longest continuous scientific practice in history: counting sunspots. Source: nautil.us