Tag: what
What is Google’s Bard AI? Here’s everything you need to know
What Can’t You Say on YouTube? Its Content Creators Aren’t Sure
Whatever it was, it was enough to get the interview demonetized, meaning no ads could be placed against it, and my host received no revenue from it.
“It does start to drive you mad,” says Andrew Gold, whose channel, On the Edge, was the place where I committed my unknowable offense. Like many full-time YouTubers, he relies on the Google-owned site’s AdSense program, which gives him a cut of revenues from the advertisements inserted before and during his interviews. When launching a new episode, Gold explained to me, “you get a green dollar sign when it’s monetizable, and it goes yellow if it’s not.” Creators can contest these rulings, but that takes time — and most videos receive the majority of their views in the first hours after launch. So it’s better to avoid the yellow dollar sign in the first place. If you want to make money off of YouTube, you need to watch what you say….
YouTube operates a three-strike policy for infractions: The first strike is a warning; the second prevents creators from making new posts for a week; and the third (if received within 90 days of the second) gets the channel banned…. Although many types of content may never run afoul of the guidelines…political discussions are subject to the whims of algorithms. Absent enough human moderators to deal with the estimated 500 hours of videos uploaded every minute, YouTube uses artificial intelligence to enforce its guidelines. Bots scan auto-generated transcripts and flag individual words and phrases as problematic, hence the problem with saying heroin. Even though “educational” references to drug use are allowed, the word might snag the AI trip wire, forcing a creator to request a time-consuming review….
[T]alk with everyday creators, and they are more than willing to work inside the rules, which they acknowledge are designed to make YouTube safer and more accurate. They just want to know what those rules are, and to see them applied consistently. As it stands, Gold compared his experience of being impersonally notified of unspecified infractions to working for HAL9000, the computer overlord from 2001: A Space Odyssey. [“They don’t tell me if it’s Nazis, heroin, or anything,” Gold says later. “You’re just left wondering what it was.”]
The article notes that YouTube’s algorithm seems to flag people who are debunking misinformation as misinformation. (One study found that purveyors of controversial content simply stop worrying about YouTube demonetizing their videos, using them to direct viewers instead to their “affiliate” links offering commissions, or to their content on other still-monetized platforms.)
In just the last three months of 2022, YouTube made almost $8 billion in advertising revenue, the article concludes. “There’s a very good reason journalism is not as profitable as that: Imagine if YouTube edited its content as diligently as a legacy newspaper or television channel — even quite a sloppy one. Its great river of videos would slow to a trickle.”
Read more of this story at Slashdot.
What Is KaiOS, and Can It Replace iPhone and Android?
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There are two big names in mobile operating systems—Google’s Android and Apple’s iOS. These two dominate the market, but they’re not alone. KaiOS is an alternative mobile OS that has some intriguing benefits. Maybe it’s right for you.
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What business logic is and where it should live
Samsung Galaxy Z Flip 5: Everything we know and what we want to see
What Is Tesla Dog Mode, and How Does It Work?
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You’ve almost certainly heard of Tesla’s “self-driving” feature by now, but what about its pet mode? A little while back, the car company introduced a feature that claims to let your pet travel with you on a hot day.
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If I’d invested £1,000 in Moderna shares 2 years ago, here’s what I’d have now!
Dr James Fox explores whether Moderna shares would have been a good investment two years ago, and takes a closer look at the firm’s pipeline.
The post If I’d invested £1,000 in Moderna shares 2 years ago, here’s what I’d have now! appeared first on The Motley Fool UK.
What happens when you repurpose H. R. Giger art to make a game? You get Dark Seed
Researchers Claim Their AI Algorithm Can Recreate What People See Using Brain Scans
A recent study, scheduled to be presented at an upcoming computer vision conference, demonstrates that AI can read brain scans and re-create largely realistic versions of images a person has seen….
Many labs have used AI to read brain scans and re-create images a subject has recently seen, such as human faces and photos of landscapes. The new study marks the first time an AI algorithm called Stable Diffusion, developed by a German group and publicly released in 2022, has been used to do this…. For the new study, a group in Japan added additional training to the standard Stable Diffusion system, linking additional text descriptions about thousands of photos to brain patterns elicited when those photos were observed by participants in brain scan studies. Unlike previous efforts using AI algorithms to decipher brain scans, which had to be trained on large data sets, Stable Diffusion was able to get more out of less training for each participant by incorporating photo captions into the algorithm….
The AI algorithm makes use of information gathered from different regions of the brain involved in image perception, such as the occipital and temporal lobes, according to Yu Takagi, a systems neuroscientist at Osaka University who worked on the experiment. The system interpreted information from functional magnetic resonance imaging (fMRI) brain scans, which detect changes in blood flow to active regions of the brain. When people look at a photo, the temporal lobes predominantly register information about the contents of the image (people, objects, or scenery), whereas the occipital lobe predominantly registers information about layout and perspective, such as the scale and position of the contents. All of this information is recorded by the fMRI as it captures peaks in brain activity, and these patterns can then be reconverted into an imitation image using AI. In the new study, the researchers added additional training to the Stable Diffusion algorithm using an online data set provided by the University of Minnesota, which consisted of brain scans from four participants as they each viewed a set of 10,000 photos.
If a study participant showed the same brain pattern, the algorithm sent words from that photo’s caption to Stable Diffusion’s text-to-image generator.
Iris Groen, a neuroscientist at the University of Amsterdam who was not involved with the work, told Science that “The accuracy of this new method is impressive.”
Read more of this story at Slashdot.