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Google, Apple, and Discord Let Harmful AI 'Undress' Websites Use Their Sign-On Systems

WIRED

Major technology companies, including Google, Apple, and Discord, have been enabling people to quickly sign up to harmful "undress" websites, which use AI to remove clothes from real photos to make victims appear to be "nude" without their consent. More than a dozen of these deepfake websites have been using login buttons from the tech companies for months. A WIRED analysis found 16 of the biggest so-called undress and "nudify" websites using the sign-in infrastructure from Google, Apple, Discord, Twitter, Patreon, and Line. This approach allows people to easily create accounts on the deepfake websites--offering them a veneer of credibility--before they pay for credits and generate images. While bots and websites that create nonconsensual intimate images of women and girls have existed for years, the number has increased with the introduction of generative AI.



Baseten nabs $20M to make it easier to build machine learning-based applications – TechCrunch

#artificialintelligence

As the tech world inches a closer to the idea of artificial general intelligence, we're seeing another interesting theme emerging in the ongoing democratization of AI: a wave of startups building tech to make AI technologies more accessible overall by a wider range of users and organizations. Today, one of these, Baseten -- which is building tech to make it easier to incorporate machine learning into a business' operations, production and processes without a need for specialized engineering knowledge -- is announcing $20 million in funding and the official launch of its tools. These include a client API and a library of pre-trained models to deploy models built in TensorFlow, PyTorch or scikit-learn; the ability to build APIs to power your own applications; and the ability the create custom UIs for your applications based on drag-and-drop components. The company has been operating in a closed, private beta for about a year and has amassed an interesting group of customers so far, including both Stanford and the University of Sydney, Cockroach Labs and Patreon, among others, who use it to, for example, help organizations with automated abuse detection (through content moderation) and fraud prevention. The $20 million is being discussed publicly for the first time now to coincide with the commercial launch, and it's in two tranches, with equally notable names among those backers.


Data Scientist

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Do you believe that creators should have the ability to get paid for the value they give to their fans? We do, which is why we're building Patreon, a platform that powers membership services for creators with established followings. Patreon strives to provide creators with insight, education, and tools that make it possible to retain creative control while running their creative business, so creators can focus on creating and energizing their fanbases. We have payed out over $500 million directly to creators on our platform this year alone, and our user base has doubled. In order to support this level of growth, we are looking for a Data Scientist to join our team.


Senior Data Scientist, Creator-Facing Teams

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We do, which is why we're building Patreon, a platform that powers membership services for creators with established followings. Patreon strives to provide creators with insight, education, and tools that make it possible to retain creative control while running their creative business, so creators can focus on creating and energizing their fanbases. Our user base has doubled in the last year alone, and we have paid over $2 billion directly to creators on our platform. In order to support this level of growth, Patreon is looking for a Senior Data Scientist to join our team. At Patreon, you'll join a high-performing and highly-empathetic team of people who proudly work on fulfilling our mission of funding the creative class.


Two Minute Papers: New AI: Photos Go In, Reality Comes Out! 🌁

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Check out Lambda here and sign up for their GPU Cloud: https://lambdalabs.com/papers The paper "ADOP: Approximate Differentiable One-Pixel Point Rendering" is available here: https://arxiv.org/abs/2110.06635


Two Minute Papers: Why Should We Trust An AI?

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We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Andrew Melnychuk, Brian Gilman, Christian Ahlin, Christoph Jadanowski, Dennis Abts, Emmanuel, Eric Haddad, Esa Turkulainen, Evan Breznyik, Frank Goertzen, Malek Cellier, Marten Rauschenberg, Michael Albrecht, Michael Jensen, Nader Shakerin, Raul Araújo da Silva, Robin Graham, Shawn Azman, Steef, Steve Messina, Sunil Kim, Torsten Reil. One-time payment links are available below.


Two Minute Papers: DeepMind's AI Learns Object Sounds

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The paper "Objects that Sound" is available here: https://arxiv.org/abs/1712.06651 One-time payment links are available below.


Two Minute Papers: Neural Image Stitching And Morphing

#artificialintelligence

The paper "Neural Best-Buddies: Sparse Cross-Domain Correspondence" is available here: https://arxiv.org/abs/1805.04140 Pick up cool perks on our Patreon page: http