Tag: ML

  • AI vs Human made

    AI vs Human made

    Das Beispiel ist vielleicht nicht gleich das prominenteste, aber das erste, das ich in meiner Timeline (Buzzfeed) hatte. Der vietnamesische Künstler Minh Anh Nguyen Hoang, der sich selbst Ben Moran nennt, ist Gegenstand einer Debatte um AI und Generative Art bei Reddit geworden. Der Künstler produziert Buchcover, berichtet der Buzzfeed Artikel, bereits mehrmals für Selkie…

  • AI Wrote Better Phishing Emails

    WIRED schreibt, dass es Forschern gelungen ist, mit Hilfe von GPT3, dem Generative Pre-trained Transformer 3 ML Netzwerk, Phishing Mails zu erzeugen, die deutlich wirksamer sind als von Menschen geschriebene Mails. Endlich ein Einsatzbereich für AI, der sich auch ohne VC Geld lohnt. Source: AI Wrote Better Phishing Emails Than Humans in a Recent Test…

  • Protect your images from abuse by KI

    From the “Daily Dystopia Department”: Protect your images from abuse by KI. Headlines that’d be absolutely unthinkable only a decade ago don’t seem to be shocking in the year of the pandemic, 2021.

  • Introducing TensorFlow Recommenders

    TensorFlow, the open-source machine-learning library, introduced a library to make recommendations easier. Recommendations are a crucial component for e-Commerce but also other web-services. Good recommendations help build a better user experience and drive customer engagement. The more time consumers spend on a site, the quicker customers find what they are looking for, the better their…

  • Magic Email

    It’s not like email has been a perfect solution ever, to start with. In fact, email has been broken for most of its existence. Imagine all the rules and filters you need to stay on top of your inbox. When Internet became popular, soon spam became popular. Email lists were usable only before eternal September…

  • Internet Powertoy

    Internet of the day. Enjoy the rest of your day. You are welcome. https://pointerpointer.com

  • Machine Learning Confronts the Elephant in the Room 

    Machine Learning helps identifying the elephant in the room. Literally. A visual prank exposes an Achilles’ heel of computer vision systems: Unlike humans, they can’t do a double take. Source: Machine Learning Confronts the Elephant in the Room | Quanta Magazine