Group items tagged

"But researchers have approximately zero clues as to why it's so good at it, and it doesn't help that the AI essentially taught itself to make these predictions. According to one researcher involved in the project, "We can build these models, but we don't know how they work.""

"he outlines three sources of dysfunction - 'deliberate, malicious intent, such as state-sponsored hacking and attacks, criminal behaviour, and online harassment'; 'system design' which has created 'perverse incentives where user value is sacrificed, such as ad-based revenue models that commercially reward clickbait'; and the 'viral spread of misinformation'. he also calls attention to the 'unintended negative consequences' of the web, which he said had led to 'the outraged and polarised tone and quality of online discourse'."

"In the meantime, Pham is keen to see if robots can learn to build the chair using only an image of the assembled product as a guide. Will the technology ever help humans who struggle with the task? "I don't think it is in Ikea's business model to have robots assemble their chairs," he said. "In the next 10 to 20 years, people will still be sweating over flat-pack furniture.""

"So they trained a deep-learning neural net on tons of examples of deepfaked videos, and produced a model that's better than any previous automated technique at spotting hoaxery. (Their paper documenting the work is here.)"

"The triumph of open standards has manifestly demoralized Chiariglione, who grudgingly admits that a combination of rent-seeking by MPEG members and legal threats from patent trolls has spelled the end of the "business model" of creating standards for the purpose of allowing companies to charge royalties for everyday technological activities by injecting their patents into it."

"Now, work posted online shows how artificial intelligence (AI) can easily produce accurate emulators that can accelerate simulations across all of science by billions of times."

"Mobility-as-a-Service (MaaS) is a model for traffic without ownership. You pay a monthly fee for it, like with Spotify, tell the app where you are going and get instant access to taxis, Ubers, buses, and so on. Everything is available on-demand and ownership is no longer needed."

"In a paper titled "Towards Causal Representation Learning," researchers at the Max Planck Institute for Intelligent Systems, the Montreal Institute for Learning Algorithms (Mila), and Google Research discuss the challenges arising from the lack of causal representations in machine learning models and provide directions for creating artificial intelligence systems that can learn causal representations."

"SoundCloud announced on Tuesday it would become the first major streaming service to start directing subscribers' fees only to the artists they listen to, a move welcomed by musicians campaigning for fairer pay. Current practice for streaming services including Spotify, Deezer and Apple is to pool royalty payments and dish them out based on which artists have the most global plays. Many artists and unions have criticised this system, saying it disproportionately favours megastars and leaves y little for musicians further down the pecking order."

"Robinhood's free-trading revolution helped pave the way to the recent Reddit mayhem on Wall Street. The rise of Robinhood means that the ability to buy stocks, on a whim, is now at everyone's fingertips. Robinhood has opened investing up to the masses. Rival online brokerages were forced to mimic Robinhood's zero-commission business model, and some joined forces just to survive. "

"Some unemployment applicants have said that ID.me's facial recognition models fail to properly identify them (generally speaking, facial recognition technology is notoriously less accurate for women and people of color). And after their applications were put on hold because their identity couldn't be verified, many should-be beneficiaries have had to wait days or weeks to reach an ID.me "trusted referee" who could confirm what the technology couldn't."

"It's actually a big myth that search engines need to track your personal search history to make money or deliver quality search results. Almost all of the money search engines make (including Google) is based on the keywords you type in, without knowing anything about you, including your search history or the seemingly endless amounts of additional data points they have collected about registered and non-registered users alike. In fact, search advertisers buy search ads by bidding on keywords, not people….This keyword-based advertising is our primary business model. "

"The internet is primarily funded by the collection, analysis, and trade of data-the data economy. Much of that data is personal data-data about you. The trading of personal data as a business model is increasingly being exported to all institutions in society-the surveillance society, or surveillance capitalism."

"The models work by dividing maps into what Google calls "supersegments" "

"Researchers showed detectors can be defeated by inserting inputs called adversarial examples into every video frame. The adversarial examples are slightly manipulated inputs which cause artificial intelligence systems such as machine learning models to make a mistake. In addition, the team showed that the attack still works after videos are compressed."

"Most people who use AI-powered translation tools do so for commonplace, relatively unimportant tasks like understanding a single phrase or quote. Those basic services won't do for an enterprise offering technical documents in 15 languages - but Lengoo's custom machine translation models might just do the trick. And with a new $20 million B round, they may be able to build a considerable lead. The translation business is a big one, in the billions, and isn't going anywhere. It's simply too common a task to need to release a document, piece of software or live website in multiple languages - perhaps dozens."

"These experiments in computational creativity are enabled by the dramatic advances in deep learning over the past decade. Deep learning has several key advantages for creative pursuits. For starters, it's extremely flexible, and it's relatively easy to train deep-learning systems (which we call models) to take on a wide variety of tasks."

"What Hamilton and his colleagues found surprising was that this approach could also be applied to helping find problems with existing deep networks, related to the surge of "deepfakes" that have recently cropped up. They applied this data structure to find areas where probabilistic models, such as the generative adversarial networks (GANs) that are often used to create deepfakes, break down. They coined these problematic areas "blind spots," and note that they give us insight into how GANs can be biased. Such blind spots further show that GANs struggle to represent particular areas of a dataset, even if most of their fakes can fool a human. "

"The company has called for Australian policymakers to promote "copyright systems that enable appropriate and fair use of copyrighted content to enable the training of AI models in Australia on a broad and diverse range of data, while supporting workable opt-outs for entities that prefer their data not to be trained in using AI systems". The call for a fair use exception for AI systems is a view the company has expressed to the Australian government in the past, but the notion of an opt-out option for publishers is a new argument from Google."

"The platforms that control search were conceived in sin. Their business model auctions off our most precious and limited cognitive resource: attention. These platforms work overtime to hijack our attention by purveying information that arouses curiosity, outrage, or anger. The more our eyeballs remain glued to the screen, the more ads they can show us, and the greater profits accrue to their shareholders."