Tech roundup 33: a journal published by a bot

Read a tech roundup with this week’s news that our powerful bot has chosen: blockchain, AI, development, corporates and more.

Gooooooood morning, Tribe!!! Hey, this is not a test, this is a tech roundup. Time to rock it from the Delta to the DMZ.

AI, bots and robots

  • A Practitioner’s Guide to Deep Learning with Ludwig
  • A Worrying Analysis of Recent Neural Recommendation Approaches
    Deep learning techniques have become the method of choice for researchers
    working on algorithmic aspects of recommender systems. With the strongly
    increased interest in machine learning in general, it has, as a result, become
    difficult to keep track of what represents the state-of-the-art at the moment,
    e.g., for top-n recommendation tasks. At the same time, several recent
    publications point out problems in today’s research practice in applied machine
    learning, e.g., in terms of the reproducibility of the results or the choice of
    the baselines when proposing new models. In this work, we report the results of
    a systematic analysis of algorithmic proposals for top-n recommendation tasks.
    Specifically, we considered 18 algorithms that were presented at top-level
    research conferences in the last years. Only 7 of them could be reproduced with
    reasonable effort. For these methods, it however turned out that 6 of them can
    often be outperformed with comparably simple heuristic methods, e.g., based on
    nearest-neighbor or graph-based techniques. The remaining one clearly
    outperformed the baselines but did not consistently outperform a well-tuned
    non-neural linear ranking method. Overall, our work sheds light on a number of
    potential problems in today’s machine learning scholarship and calls for
    improved scientific practices in this area. Source code of our experiments and
    full results are available at:
    https://github.com/MaurizioFD/RecSys2019_DeepLearning_Evaluation.
  • The AI of GoldenEye 007
  • Deciphering Linear B with AI
    In this paper we propose a novel neural approach for automatic decipherment
    of lost languages. To compensate for the lack of strong supervision signal, our
    model design is informed by patterns in language change documented in
    historical linguistics. The model utilizes an expressive sequence-to-sequence
    model to capture character-level correspondences between cognates. To
    effectively train the model in an unsupervised manner, we innovate the training
    procedure by formalizing it as a minimum-cost flow problem. When applied to the
    decipherment of Ugaritic, we achieve a 5.5% absolute improvement over
    state-of-the-art results. We also report the first automatic results in
    deciphering Linear B, a syllabic language related to ancient Greek, where our
    model correctly translates 67.3% of cognates.
  • AI Portraits
  • AI is supercharging the creation of maps around the world
    Map With AI, tool created by Facebook researchers and engineers, is helping the OpenStreetMap (OSM) project map missing roads around the world.
  • Simple trading bot in JavaScript using ~40 lines of code
  • An Introduction to Recurrent Neural Networks
  • Waifu Labs – AI Generated Custom Waifus
  • Play rock paper and scissors against a untrained neural network
  • Darpa’s New Brain Device Increases Learning Speed by 40%

Blockchain and decentralization

Woman computer scientist of the week
Ashawna Hailey, created the HSPICE program which large parts of the worldwide semiconductor industry use to simulate and design silicon chips. Her company, Meta-Software, produced compound annual growth rate in excess of 25-30 percent every year for 18 years, and eventually became part of Synopsys, which calls HSPICE «the ‘gold standard’ for accurate circuit simulation». In 1973 she created Advanced Micro Devices’ first microprocessor, the Am9080, a clone of the Intel 8080, and in 1974, AMD’s first nonvolatile memory, the 2702 2048-bit EPROM. Earlier, she built the launch sequencer for the Sprint Anti-Ballistic Missile System for Martin Marietta.

Cloud and architecture

Development and languages

Quote of the week

RMS is to Unix, like Hitler [was] to Nietzsche.

        — Federico Benavento

Enterprises

Other news

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Autor: Javi López G.

Arquitecto/desarrollador, creativo, buscador de nuevas soluciones y modelos de negocio, crítico constructivo y ex muchas cosas

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