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Rive text is live!! Animatable, variable, dynamic text for runtime, with full support for any language. There are a MONSTER amount of new things to play around with! 🚀 Create Text objects, styles, runs, and modifiers. 🚀 Support for any language. LTR, RTL, special characters/features, ligatures, etc. 🚀 Animate... variable fonts. 🚀 Google Fonts are provided by default, but you can upload custom fonts. 🚀 Runs are a way to segment a text field into different sections. You can target runs at runtime to change their content dynamically. See documentation here: 🚀 Apply different text styles to runs. 🚀 Convert text to paths (flatten). 🚀 Text modifiers are a powerful way to add layered animation to text, while maintaining its editability! 🚀 Use transform constraints to resize graphics to text objects. Coming soon: 🚧 Ability to export fonts out of band or via CDN. They are currently packaged in the .riv file.show more

Guido Rosso

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25,950 Aufrufe • vor 3 Jahren •via X (Twitter)

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ACN Labs

41,377 Aufrufe • vor 1 Jahr

This monkey is in an NIH laboratory run by experimenter Elisabeth Murray. Murray subjects sensitive, vulnerable monkeys to procedures in which she saws open her victims’ skulls and injects toxins to burn brain cells, or suctions out parts of their brain to induce permanent damage. After sewing them back up, she places them in a small cage and deliberately provokes them with their worst fears, spiders and snakes, just to see how they’ll react. Although artificial, some of these realistic-looking spiders and snakes can move or even jump. She keeps monkeys hungry and thirsty to force them to cooperate, restrains them for extended periods of time, and implants head posts directly into their skulls. Some monkeys have lived for decades in her lab, pulling out their own hair and suffering with chronic diarrhea from the constant stress of living in a metal box. After these cruel and pointless experiments, Murray kills the monkeys. Murray’s experiments are an atrocity against monkeys and embarrassment to science. Text FRIGHT to 73822 to urge the NIH to end these experiments! *Message and data rates may apply. U.S. only. Text STOP to end and HELP for info. Periodic messaging. Full terms are available at:

This monkey is in an NIH laboratory run by experimenter Elisabeth Murray. Murray subjects sensitive, vulnerable monkeys to procedures in which she saws open her victims’ skulls and injects toxins to burn brain cells, or suctions out parts of their brain to induce permanent damage. After sewing them back up, she places them in a small cage and deliberately provokes them with their worst fears, spiders and snakes, just to see how they’ll react. Although artificial, some of these realistic-looking spiders and snakes can move or even jump. She keeps monkeys hungry and thirsty to force them to cooperate, restrains them for extended periods of time, and implants head posts directly into their skulls. Some monkeys have lived for decades in her lab, pulling out their own hair and suffering with chronic diarrhea from the constant stress of living in a metal box. After these cruel and pointless experiments, Murray kills the monkeys. Murray’s experiments are an atrocity against monkeys and embarrassment to science. Text FRIGHT to 73822 to urge the NIH to end these experiments! *Message and data rates may apply. U.S. only. Text STOP to end and HELP for info. Periodic messaging. Full terms are available at:

PETA

32,855 Aufrufe • vor 3 Jahren

The Hidden Language of Diffusion Models paper page: tackle the challenge of understanding concept representations in text-to-image models by decomposing an input text prompt into a small set of interpretable elements. This is achieved by learning a pseudo-token that is a sparse weighted combination of tokens from the model's vocabulary, with the objective of reconstructing the images generated for the given concept. Applied over the state-of-the-art Stable Diffusion model, this decomposition reveals non-trivial and surprising structures in the representations of concepts. For example, we find that some concepts such as "a president" or "a composer" are dominated by specific instances (e.g., "Obama", "Biden") and their interpolations. Other concepts, such as "happiness" combine associated terms that can be concrete ("family", "laughter") or abstract ("friendship", "emotion"). In addition to peering into the inner workings of Stable Diffusion, our method also enables applications such as single-image decomposition to tokens, bias detection and mitigation, and semantic image manipulation

The Hidden Language of Diffusion Models paper page: tackle the challenge of understanding concept representations in text-to-image models by decomposing an input text prompt into a small set of interpretable elements. This is achieved by learning a pseudo-token that is a sparse weighted combination of tokens from the model's vocabulary, with the objective of reconstructing the images generated for the given concept. Applied over the state-of-the-art Stable Diffusion model, this decomposition reveals non-trivial and surprising structures in the representations of concepts. For example, we find that some concepts such as "a president" or "a composer" are dominated by specific instances (e.g., "Obama", "Biden") and their interpolations. Other concepts, such as "happiness" combine associated terms that can be concrete ("family", "laughter") or abstract ("friendship", "emotion"). In addition to peering into the inner workings of Stable Diffusion, our method also enables applications such as single-image decomposition to tokens, bias detection and mitigation, and semantic image manipulation

AK

41,746 Aufrufe • vor 3 Jahren

🎥 Comparing AI video models: Image to video • Gen-3 • Kling AI 1.5 • Hailuo MiniMax • Luma Dream Machine I used a Midjourney image in each model 4 times with no text prompt. This type of image is difficult for the AI to separate the subject in the front from the people behind her - they tend to move the group as if they are a single unit. But the results were interesting, as you can see! I chose my favorite results, below.

🎥 Comparing AI video models: Image to video • Gen-3 • Kling AI 1.5 • Hailuo MiniMax • Luma Dream Machine I used a Midjourney image in each model 4 times with no text prompt. This type of image is difficult for the AI to separate the subject in the front from the people behind her - they tend to move the group as if they are a single unit. But the results were interesting, as you can see! I chose my favorite results, below.

Heather Cooper

41,354 Aufrufe • vor 1 Jahr