video synthesis

Toys “R” Us riles critics with “first-ever” AI-generated commercial using Sora

AI, Air Head, Biz & IT, Joe Russo, machine learning, Mike Drucker, Native Foreign, Patrick Cederberg, shy kids, Toys, Toys"R"Us, video synthesis / Ryan Harris / June 26, 2024

Enlarge / A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys R Us

On Monday, Toys “R” Us announced that it had partnered with an ad agency called Native Foreign to create what it calls “the first-ever brand film using OpenAI’s new text-to-video tool, Sora.” OpenAI debuted Sora in February, but the video synthesis tool has not yet become available to the public. The brand film tells the story of Toys “R” Us founder Charles Lazarus using AI-generated video clips.

“We are thrilled to partner with Native Foreign to push the boundaries of Sora, a groundbreaking new technology from OpenAI that’s gaining global attention,” wrote Toys “R” Us on its website. “Sora can create up to one-minute-long videos featuring realistic scenes and multiple characters, all generated from text instruction. Imagine the excitement of creating a young Charles Lazarus, the founder of Toys “R” Us, and envisioning his dreams for our iconic brand and beloved mascot Geoffrey the Giraffe in the early 1930s.”

The company says that The Origin of Toys “R” Us commercial was co-produced by Toys “R” Us Studios President Kim Miller Olko as executive producer and Native Foreign’s Nik Kleverov as director. “Charles Lazarus was a visionary ahead of his time, and we wanted to honor his legacy with a spot using the most cutting-edge technology available,” Miller Olko said in a statement.

In the video, we see a child version of Lazarus, presumably generated using Sora, falling asleep and having a dream that he is flying through a land of toys. Along the way, he meets Geoffery, the store’s mascot, who hands the child a small red car.

Many of the scenes retain obvious hallmarks of AI-generated imagery, such as unnatural movement, strange visual artifacts, and the irregular shape of eyeglasses. In February, a few Super Bowl commercials intentionally made fun of similar AI-generated video defects, which became famous online after fake AI-generated beer commercial and “Pepperoni Hug Spot” clips made using Runway’s Gen-2 model went viral in 2023.

A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys “R” Us
A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys “R” Us
A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys “R” Us
A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys R Us
A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys R Us
A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys “R” Us
A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys “R” Us
A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys “R” Us
A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys “R” Us
A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys “R” Us
A screen capture from the partially AI-generated Toys “R” Us brand film created using Sora.

Toys “R” Us

AI-generated artwork receives frequent criticism online due to the use of human-created artwork to train AI models that create the works, the perception that AI synthesis tools will replace (or are currently replacing) human creative jobs, and the potential environmental impact of AI models, which are seen as energy-wasteful by some critics. Also, some people just think the output quality looks bad.

On the social network X, comedy writer Mike Drucker wrapped up several of these criticisms into one post, writing, “Love this commercial is like, ‘Toys R Us started with the dream of a little boy who wanted to share his imagination with the world. And to show how, we fired our artists and dried Lake Superior using a server farm to generate what that would look like in Stephen King’s nightmares.'”

Other critical comments were more frank. Filmmaker Joe Russo posted: “TOYS ‘R US released an AI commercial and it fucking sucks.”

Toys “R” Us riles critics with “first-ever” AI-generated commercial using Sora Read More »

Runway’s latest AI video generator brings giant cotton candy monsters to life

AI, AI-generated video, Biz & IT, Deepfakes, filmmaking, films, Gen-2, Gen-3, Gen-3 Alpha, giant cotton-candy monster, Google, machine learning, Meta, openai, Runway, Sora, Special Effects, video synthesis / Ryan Harris / June 19, 2024

Enlarge / Screen capture of a Runway Gen-3 Alpha video generated with the prompt “A giant humanoid, made of fluffy blue cotton candy, stomping on the ground, and roaring to the sky, clear blue sky behind them.”

On Sunday, Runway announced a new AI video synthesis model called Gen-3 Alpha that’s still under development, but it appears to create video of similar quality to OpenAI’s Sora, which debuted earlier this year (and has also not yet been released). It can generate novel, high-definition video from text prompts that range from realistic humans to surrealistic monsters stomping the countryside.

Unlike Runway’s previous best model from June 2023, which could only create two-second-long clips, Gen-3 Alpha can reportedly create 10-second-long video segments of people, places, and things that have a consistency and coherency that easily surpasses Gen-2. If 10 seconds sounds short compared to Sora’s full minute of video, consider that the company is working with a shoestring budget of compute compared to more lavishly funded OpenAI—and actually has a history of shipping video generation capability to commercial users.

Gen-3 Alpha does not generate audio to accompany the video clips, and it’s highly likely that temporally coherent generations (those that keep a character consistent over time) are dependent on similar high-quality training material. But Runway’s improvement in visual fidelity over the past year is difficult to ignore.

AI video heats up

It’s been a busy couple of weeks for AI video synthesis in the AI research community, including the launch of the Chinese model Kling, created by Beijing-based Kuaishou Technology (sometimes called “Kwai”). Kling can generate two minutes of 1080p HD video at 30 frames per second with a level of detail and coherency that reportedly matches Sora.

Gen-3 Alpha prompt: “Subtle reflections of a woman on the window of a train moving at hyper-speed in a Japanese city.”

Not long after Kling debuted, people on social media began creating surreal AI videos using Luma AI’s Luma Dream Machine. These videos were novel and weird but generally lacked coherency; we tested out Dream Machine and were not impressed by anything we saw.

Meanwhile, one of the original text-to-video pioneers, New York City-based Runway—founded in 2018—recently found itself the butt of memes that showed its Gen-2 tech falling out of favor compared to newer video synthesis models. That may have spurred the announcement of Gen-3 Alpha.

Gen-3 Alpha prompt: “An astronaut running through an alley in Rio de Janeiro.”

Generating realistic humans has always been tricky for video synthesis models, so Runway specifically shows off Gen-3 Alpha’s ability to create what its developers call “expressive” human characters with a range of actions, gestures, and emotions. However, the company’s provided examples weren’t particularly expressive—mostly people just slowly staring and blinking—but they do look realistic.

Provided human examples include generated videos of a woman on a train, an astronaut running through a street, a man with his face lit by the glow of a TV set, a woman driving a car, and a woman running, among others.

Gen-3 Alpha prompt: “A close-up shot of a young woman driving a car, looking thoughtful, blurred green forest visible through the rainy car window.”

The generated demo videos also include more surreal video synthesis examples, including a giant creature walking in a rundown city, a man made of rocks walking in a forest, and the giant cotton candy monster seen below, which is probably the best video on the entire page.

Gen-3 Alpha prompt: “A giant humanoid, made of fluffy blue cotton candy, stomping on the ground, and roaring to the sky, clear blue sky behind them.”

Gen-3 will power various Runway AI editing tools (one of the company’s most notable claims to fame), including Multi Motion Brush, Advanced Camera Controls, and Director Mode. It can create videos from text or image prompts.

Runway says that Gen-3 Alpha is the first in a series of models trained on a new infrastructure designed for large-scale multimodal training, taking a step toward the development of what it calls “General World Models,” which are hypothetical AI systems that build internal representations of environments and use them to simulate future events within those environments.

Runway’s latest AI video generator brings giant cotton candy monsters to life Read More »

Microsoft’s VASA-1 can deepfake a person with one photo and one audio track

AI, AI ethics, AI safety, Biz & IT, Deepfakes, image synthesis, machine learning, microsoft, VASA-1, video synthesis / Blake Jones / April 21, 2024

pics and it didn’t happen —

YouTube videos of 6K celebrities helped train AI model to animate photos in real time.

Benj Edwards – Apr 19, 2024 1: 07 pm UTC

Enlarge / A sample image from Microsoft for “VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time.”

On Tuesday, Microsoft Research Asia unveiled VASA-1, an AI model that can create a synchronized animated video of a person talking or singing from a single photo and an existing audio track. In the future, it could power virtual avatars that render locally and don’t require video feeds—or allow anyone with similar tools to take a photo of a person found online and make them appear to say whatever they want.

“It paves the way for real-time engagements with lifelike avatars that emulate human conversational behaviors,” reads the abstract of the accompanying research paper titled, “VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time.” It’s the work of Sicheng Xu, Guojun Chen, Yu-Xiao Guo, Jiaolong Yang, Chong Li, Zhenyu Zang, Yizhong Zhang, Xin Tong, and Baining Guo.

The VASA framework (short for “Visual Affective Skills Animator”) uses machine learning to analyze a static image along with a speech audio clip. It is then able to generate a realistic video with precise facial expressions, head movements, and lip-syncing to the audio. It does not clone or simulate voices (like other Microsoft research) but relies on an existing audio input that could be specially recorded or spoken for a particular purpose.

Microsoft claims the model significantly outperforms previous speech animation methods in terms of realism, expressiveness, and efficiency. To our eyes, it does seem like an improvement over single-image animating models that have come before.

AI research efforts to animate a single photo of a person or character extend back at least a few years, but more recently, researchers have been working on automatically synchronizing a generated video to an audio track. In February, an AI model called EMO: Emote Portrait Alive from Alibaba’s Institute for Intelligent Computing research group made waves with a similar approach to VASA-1 that can automatically sync an animated photo to a provided audio track (they call it “Audio2Video”).

Trained on YouTube clips

Microsoft Researchers trained VASA-1 on the VoxCeleb2 dataset created in 2018 by three researchers from the University of Oxford. That dataset contains “over 1 million utterances for 6,112 celebrities,” according to the VoxCeleb2 website, extracted from videos uploaded to YouTube. VASA-1 can reportedly generate videos of 512×512 pixel resolution at up to 40 frames per second with minimal latency, which means it could potentially be used for realtime applications like video conferencing.

To show off the model, Microsoft created a VASA-1 research page featuring many sample videos of the tool in action, including people singing and speaking in sync with pre-recorded audio tracks. They show how the model can be controlled to express different moods or change its eye gaze. The examples also include some more fanciful generations, such as Mona Lisa rapping to an audio track of Anne Hathaway performing a “Paparazzi” song on Conan O’Brien.

The researchers say that, for privacy reasons, each example photo on their page was AI-generated by StyleGAN2 or DALL-E 3 (aside from the Mona Lisa). But it’s obvious that the technique could equally apply to photos of real people as well, although it’s likely that it will work better if a person appears similar to a celebrity present in the training dataset. Still, the researchers say that deepfaking real humans is not their intention.

“We are exploring visual affective skill generation for virtual, interactive charactors [sic], NOT impersonating any person in the real world. This is only a research demonstration and there’s no product or API release plan,” reads the site.

While the Microsoft researchers tout potential positive applications like enhancing educational equity, improving accessibility, and providing therapeutic companionship, the technology could also easily be misused. For example, it could allow people to fake video chats, make real people appear to say things they never actually said (especially when paired with a cloned voice track), or allow harassment from a single social media photo.

Right now, the generated video still looks imperfect in some ways, but it could be fairly convincing for some people if they did not know to expect an AI-generated animation. The researchers say they are aware of this, which is why they are not openly releasing the code that powers the model.

“We are opposed to any behavior to create misleading or harmful contents of real persons, and are interested in applying our technique for advancing forgery detection,” write the researchers. “Currently, the videos generated by this method still contain identifiable artifacts, and the numerical analysis shows that there’s still a gap to achieve the authenticity of real videos.”

VASA-1 is only a research demonstration, but Microsoft is far from the only group developing similar technology. If the recent history of generative AI is any guide, it’s potentially only a matter of time before similar technology becomes open source and freely available—and they will very likely continue to improve in realism over time.

Microsoft’s VASA-1 can deepfake a person with one photo and one audio track Read More »

Tyler Perry puts $800 million studio expansion on hold because of OpenAI’s Sora

AI, AI and jobs, AI ethics, AI safety, Biz & IT, generative ai, machine learning, openai, Sora, Tyler Perry, video synthesis / Ryan Harris / February 25, 2024

The Synthetic Screen —

Perry: Mind-blowing AI video-generation tools “will touch every corner of our industry.”

Benj Edwards – Feb 23, 2024 4: 42 pm UTC

In an interview with The Hollywood Reporter published Thursday, filmmaker Tyler Perry spoke about his concerns related to the impact of AI video synthesis on entertainment industry jobs. In particular, he revealed that he has suspended a planned $800 million expansion of his production studio after seeing what OpenAI’s recently announced AI video generator Sora can do.

“I have been watching AI very closely,” Perry said in the interview. “I was in the middle of, and have been planning for the last four years… an $800 million expansion at the studio, which would’ve increased the backlot a tremendous size—we were adding 12 more soundstages. All of that is currently and indefinitely on hold because of Sora and what I’m seeing. I had gotten word over the last year or so that this was coming, but I had no idea until I saw recently the demonstrations of what it’s able to do. It’s shocking to me.”

OpenAI, the company behind ChatGPT, revealed a preview of Sora’s capabilities last week. Sora is a text-to-video synthesis model, and it uses a neural network—previously trained on video examples—that can take written descriptions of a scene and turn them into high-definition video clips up to 60 seconds long. Sora caused shock in the tech world because it appeared to surpass other AI video generators in capability dramatically. It seems that a similar shock also rippled into adjacent professional fields. “Being told that it can do all of these things is one thing, but actually seeing the capabilities, it was mind-blowing,” Perry said in the interview.

Tyler Perry Studios, which the actor and producer acquired in 2015, is a 330-acre lot located in Atlanta and is one of the largest film production facilities in the United States. Perry, who is perhaps best known for his series of Madea films, says that technology like Sora worries him because it could make the need for building sets or traveling to locations obsolete. He cites examples of virtual shooting in the snow of Colorado or on the Moon just by using a text prompt. “This AI can generate it like nothing.” The technology may represent a radical reduction in costs necessary to create a film, and that will likely put entertainment industry jobs in jeopardy.

“It makes me worry so much about all of the people in the business,” he told The Hollywood Reporter. “Because as I was looking at it, I immediately started thinking of everyone in the industry who would be affected by this, including actors and grip and electric and transportation and sound and editors, and looking at this, I’m thinking this will touch every corner of our industry.”

You can read the full interview at The Hollywood Reporter, which did an excellent job of covering Perry’s thoughts on a technology that may end up fundamentally disrupting Hollywood. To his mind, AI tech poses an existential risk to the entertainment industry that it can’t ignore: “There’s got to be some sort of regulations in order to protect us. If not, I just don’t see how we survive.”

Perry also looks beyond Hollywood and says that it’s not just filmmaking that needs to be on alert, and he calls for government action to help retain human employment in the age of AI. “If you look at it across the world, how it’s changing so quickly, I’m hoping that there’s a whole government approach to help everyone be able to sustain.”

Tyler Perry puts $800 million studio expansion on hold because of OpenAI’s Sora Read More »

Will Smith parodies viral AI-generated video by actually eating spaghetti

AI, AI-generated video, Biz & IT, chatgpt, chatgtp, culture, Deepfakes, fake video, machine learning, openai, OpenAI Sora, Sora, video synthesis, will smith / Mike M. / February 21, 2024

Mangia, mangia —

Actor pokes fun at 2023 AI video by eating spaghetti messily and claiming it’s AI-generated.

Benj Edwards – Feb 20, 2024 2: 50 pm UTC

Enlarge / The real Will Smith eating spaghetti, parodying an AI-generated video from 2023.

On Monday, Will Smith posted a video on his official Instagram feed that parodied an AI-generated video of the actor eating spaghetti that went viral last year. With the recent announcement of OpenAI’s Sora video synthesis model, many people have noted the dramatic jump in AI-video quality over the past year compared to the infamous spaghetti video. Smith’s new video plays on that comparison by showing the actual actor eating spaghetti in a comical fashion and claiming that it is AI-generated.

Captioned “This is getting out of hand!”, the Instagram video uses a split screen layout to show the original AI-generated spaghetti video created by a Reddit user named “chaindrop” in March 2023 on the top, labeled with the subtitle “AI Video 1 year ago.” Below that, in a box titled “AI Video Now,” the real Smith shows 11 video segments of himself actually eating spaghetti by slurping it up while shaking his head, pouring it into his mouth with his fingers, and even nibbling on a friend’s hair. 2006’s Snap Yo Fingers by Lil Jon plays in the background.

In the Instagram comments section, some people expressed confusion about the new (non-AI) video, saying, “I’m still in doubt if second video was also made by AI or not.” In a reply, someone else wrote, “Boomers are gonna loose [sic] this one. Second one is clearly him making a joke but I wouldn’t doubt it in a couple months time it will get like that.”

We have not yet seen a model with the capability of Sora attempt to create a new Will-Smith-eating-spaghetti AI video, but the result would likely be far better than what we saw last year, even if it contained obvious glitches. Given how things are progressing, we wouldn’t be surprised if by 2025, video synthesis AI models can replicate the parody video created by Smith himself.

It’s worth noting for history’s sake that despite the comparison, the video of Will Smith eating spaghetti did not represent the state of the art in text-to-video synthesis at the time of its creation in March 2023 (that title would likely apply to Runway’s Gen-2, which was then in closed testing). However, the spaghetti video was reasonably advanced for open weights models at the time, having used the ModelScope AI model. More capable video synthesis models had already been released at that time, but due to the humorous cultural reference, it’s arguably more fun to compare today’s AI video synthesis to Will Smith grotesquely eating spaghetti than to teddy bears washing dishes.

Will Smith parodies viral AI-generated video by actually eating spaghetti Read More »

OpenAI collapses media reality with Sora, a photorealistic AI video generator

AI, Ai video, Ai video generator, Biz & IT, chatgpt, chatgtp, cultural singularity, dall-e, DALL-E 3, deepfake, Deepfakes, image synthesis, machine learning, openai, OpenAI Sora, Sora, Stable Diffusion, video generator, video synthesis, will smith / Ryan Harris / February 17, 2024

Pics and it didn’t happen —

Hello, cultural singularity—soon, every video you see online could be completely fake.

Benj Edwards – Feb 16, 2024 5: 23 pm UTC

Snapshots from three videos generated using OpenAI's Sora. — Enlarge / Snapshots from three videos generated using OpenAI’s Sora.

On Thursday, OpenAI announced Sora, a text-to-video AI model that can generate 60-second-long photorealistic HD video from written descriptions. While it’s only a research preview that we have not tested, it reportedly creates synthetic video (but not audio yet) at a fidelity and consistency greater than any text-to-video model available at the moment. It’s also freaking people out.

“It was nice knowing you all. Please tell your grandchildren about my videos and the lengths we went to to actually record them,” wrote Wall Street Journal tech reporter Joanna Stern on X.

“This could be the ‘holy shit’ moment of AI,” wrote Tom Warren of The Verge.

“Every single one of these videos is AI-generated, and if this doesn’t concern you at least a little bit, nothing will,” tweeted YouTube tech journalist Marques Brownlee.

For future reference—since this type of panic will some day appear ridiculous—there’s a generation of people who grew up believing that photorealistic video must be created by cameras. When video was faked (say, for Hollywood films), it took a lot of time, money, and effort to do so, and the results weren’t perfect. That gave people a baseline level of comfort that what they were seeing remotely was likely to be true, or at least representative of some kind of underlying truth. Even when the kid jumped over the lava, there was at least a kid and a room.

The prompt that generated the video above: “A movie trailer featuring the adventures of the 30 year old space man wearing a red wool knitted motorcycle helmet, blue sky, salt desert, cinematic style, shot on 35mm film, vivid colors.“

Technology like Sora pulls the rug out from under that kind of media frame of reference. Very soon, every photorealistic video you see online could be 100 percent false in every way. Moreover, every historical video you see could also be false. How we confront that as a society and work around it while maintaining trust in remote communications is far beyond the scope of this article, but I tried my hand at offering some solutions back in 2020, when all of the tech we’re seeing now seemed like a distant fantasy to most people.

In that piece, I called the moment that truth and fiction in media become indistinguishable the “cultural singularity.” It appears that OpenAI is on track to bring that prediction to pass a bit sooner than we expected.

Prompt: Reflections in the window of a train traveling through the Tokyo suburbs.

OpenAI has found that, like other AI models that use the transformer architecture, Sora scales with available compute. Given far more powerful computers behind the scenes, AI video fidelity could improve considerably over time. In other words, this is the “worst” AI-generated video is ever going to look. There’s no synchronized sound yet, but that might be solved in future models.

How (we think) they pulled it off

AI video synthesis has progressed by leaps and bounds over the past two years. We first covered text-to-video models in September 2022 with Meta’s Make-A-Video. A month later, Google showed off Imagen Video. And just 11 months ago, an AI-generated version of Will Smith eating spaghetti went viral. In May of last year, what was previously considered to be the front-runner in the text-to-video space, Runway Gen-2, helped craft a fake beer commercial full of twisted monstrosities, generated in two-second increments. In earlier video-generation models, people pop in and out of reality with ease, limbs flow together like pasta, and physics doesn’t seem to matter.

Sora (which means “sky” in Japanese) appears to be something altogether different. It’s high-resolution (1920×1080), can generate video with temporal consistency (maintaining the same subject over time) that lasts up to 60 seconds, and appears to follow text prompts with a great deal of fidelity. So, how did OpenAI pull it off?

OpenAI doesn’t usually share insider technical details with the press, so we’re left to speculate based on theories from experts and information given to the public.

OpenAI says that Sora is a diffusion model, much like DALL-E 3 and Stable Diffusion. It generates a video by starting off with noise and “gradually transforms it by removing the noise over many steps,” the company explains. It “recognizes” objects and concepts listed in the written prompt and pulls them out of the noise, so to speak, until a coherent series of video frames emerge.

Sora is capable of generating videos all at once from a text prompt, extending existing videos, or generating videos from still images. It achieves temporal consistency by giving the model “foresight” of many frames at once, as OpenAI calls it, solving the problem of ensuring a generated subject remains the same even if it falls out of view temporarily.

OpenAI represents video as collections of smaller groups of data called “patches,” which the company says are similar to tokens (fragments of a word) in GPT-4. “By unifying how we represent data, we can train diffusion transformers on a wider range of visual data than was possible before, spanning different durations, resolutions, and aspect ratios,” the company writes.

An important tool in OpenAI’s bag of tricks is that its use of AI models is compounding. Earlier models are helping to create more complex ones. Sora follows prompts well because, like DALL-E 3, it utilizes synthetic captions that describe scenes in the training data generated by another AI model like GPT-4V. And the company is not stopping here. “Sora serves as a foundation for models that can understand and simulate the real world,” OpenAI writes, “a capability we believe will be an important milestone for achieving AGI.”

One question on many people’s minds is what data OpenAI used to train Sora. OpenAI has not revealed its dataset, but based on what people are seeing in the results, it’s possible OpenAI is using synthetic video data generated in a video game engine in addition to sources of real video (say, scraped from YouTube or licensed from stock video libraries). Nvidia’s Dr. Jim Fan, who is a specialist in training AI with synthetic data, wrote on X, “I won’t be surprised if Sora is trained on lots of synthetic data using Unreal Engine 5. It has to be!” Until confirmed by OpenAI, however, that’s just speculation.

OpenAI collapses media reality with Sora, a photorealistic AI video generator Read More »

Google’s latest AI video generator can render cute animals in implausible situations

AI, Biz & IT, Google, image synthesis, Lumiere, machine learning, text-to-video, text2video, video synthesis / Mike M. / January 24, 2024

An elephant with a party hat—underwater —

Lumiere generates five-second videos that “portray realistic, diverse and coherent motion.”

Benj Edwards – Jan 24, 2024 10: 45 pm UTC

Enlarge / Still images of AI-generated video examples provided by Google for its Lumiere video synthesis model.

On Tuesday, Google announced Lumiere, an AI video generator that it calls “a space-time diffusion model for realistic video generation” in the accompanying preprint paper. But let’s not kid ourselves: It does a great job at creating videos of cute animals in ridiculous scenarios, such as using roller skates, driving a car, or playing a piano. Sure, it can do more, but it is perhaps the most advanced text-to-animal AI video generator yet demonstrated.

According to Google, Lumiere utilizes unique architecture to generate a video’s entire temporal duration in one go. Or, as the company put it, “We introduce a Space-Time U-Net architecture that generates the entire temporal duration of the video at once, through a single pass in the model. This is in contrast to existing video models which synthesize distant keyframes followed by temporal super-resolution—an approach that inherently makes global temporal consistency difficult to achieve.”

In layperson terms, Google’s tech is designed to handle both the space (where things are in the video) and time (how things move and change throughout the video) aspects simultaneously. So, instead of making a video by putting together many small parts or frames, it can create the entire video, from start to finish, in one smooth process.

The official promotional video accompanying the paper “Lumiere: A Space-Time Diffusion Model for Video Generation,” released by Google.

Lumiere can also do plenty of party tricks, which are laid out quite well with examples on Google’s demo page. For example, it can perform text-to-video generation (turning a written prompt into a video), convert still images into videos, generate videos in specific styles using a reference image, apply consistent video editing using text-based prompts, create cinemagraphs by animating specific regions of an image, and offer video inpainting capabilities (for example, it can change the type of dress a person is wearing).

In the Lumiere research paper, the Google researchers state that the AI model outputs five-second long 1024×1024 pixel videos, which they describe as “low-resolution.” Despite those limitations, the researchers performed a user study and claim that Lumiere’s outputs were preferred over existing AI video synthesis models.

As for training data, Google doesn’t say where it got the videos they fed into Lumiere, writing, “We train our T2V [text to video] model on a dataset containing 30M videos along with their text caption. [sic] The videos are 80 frames long at 16 fps (5 seconds). The base model is trained at 128×128.”

Enlarge / A block diagram showing components of the Lumiere AI model, provided by Google.

AI-generated video is still in a primitive state, but it’s been progressing in quality over the past two years. In October 2022, we covered Google’s first publicly unveiled image synthesis model, Imagen Video. It could generate short 1280×768 video clips from a written prompt at 24 frames per second, but the results weren’t always coherent. Before that, Meta debuted its AI video generator, Make-A-Video. In June of last year, Runway’s Gen2 video synthesis model enabled the creation of two-second video clips from text prompts, fueling the creation of surrealistic parody commercials. And in November, we covered Stable Video Diffusion, which can generate short clips from still images.

AI companies often demonstrate video generators with cute animals because generating coherent, non-deformed humans is currently difficult—especially since we, as humans (you are human, right?), are adept at noticing any flaws in human bodies or how they move. Just look at AI-generated Will Smith eating spaghetti.

Judging by Google’s examples (and not having used it ourselves), Lumiere appears to surpass these other AI video generation models. But since Google tends to keep its AI research models close to its chest, we’re not sure when, if ever, the public may have a chance to try it for themselves.

As always, whenever we see text-to-video synthesis models getting more capable, we can’t help but think of the future implications for our Internet-connected society, which is centered around sharing media artifacts—and the general presumption that “realistic” video typically represents real objects in real situations captured by a camera. Future video synthesis tools more capable than Lumiere will make deceptive deepfakes trivially easy to create.

To that end, in the “Societal Impact” section of the Lumiere paper, the researchers write, “Our primary goal in this work is to enable novice users to generate visual content in an creative and flexible way. [sic] However, there is a risk of misuse for creating fake or harmful content with our technology, and we believe that it is crucial to develop and apply tools for detecting biases and malicious use cases in order to ensure a safe and fair use.”

Google’s latest AI video generator can render cute animals in implausible situations Read More »

A song of hype and fire: The 10 biggest AI stories of 2023

AI, AI ethics, AI hype, AI safety, Anthropic, audio synthesis, Bing Chat, Biz & IT, chatgpt, chatgtp, encylopedia, Features, greg brockman, image synthesis, large language models, machine learning, Meta, Meta AI, microsoft, MidJourney, openai, sam altman, Stable Diffusion, text synthesis, video synthesis, will smith, x-risk, Yann LeCun / Ryan Harris / December 18, 2023

An illustration of a robot accidentally setting off a mushroom cloud on a laptop computer. — Getty Images | Benj Edwards

“Here, There, and Everywhere” isn’t just a Beatles song. It’s also a phrase that recalls the spread of generative AI into the tech industry during 2023. Whether you think AI is just a fad or the dawn of a new tech revolution, it’s been impossible to deny that AI news has dominated the tech space for the past year.

We’ve seen a large cast of AI-related characters emerge that includes tech CEOs, machine learning researchers, and AI ethicists—as well as charlatans and doomsayers. From public feedback on the subject of AI, we’ve heard that it’s been difficult for non-technical people to know who to believe, what AI products (if any) to use, and whether we should fear for our lives or our jobs.

Meanwhile, in keeping with a much-lamented trend of 2022, machine learning research has not slowed down over the past year. On X, former Biden administration tech advisor Suresh Venkatasubramanian wrote, “How do people manage to keep track of ML papers? This is not a request for support in my current state of bewilderment—I’m genuinely asking what strategies seem to work to read (or “read”) what appear to be 100s of papers per day.”

To wrap up the year with a tidy bow, here’s a look back at the 10 biggest AI news stories of 2023. It was very hard to choose only 10 (in fact, we originally only intended to do seven), but since we’re not ChatGPT generating reams of text without limit, we have to stop somewhere.

Bing Chat “loses its mind”

In February, Microsoft unveiled Bing Chat, a chatbot built into its languishing Bing search engine website. Microsoft created the chatbot using a more raw form of OpenAI’s GPT-4 language model but didn’t tell everyone it was GPT-4 at first. Since Microsoft used a less conditioned version of GPT-4 than the one that would be released in March, the launch was rough. The chatbot assumed a temperamental personality that could easily turn on users and attack them, tell people it was in love with them, seemingly worry about its fate, and lose its cool when confronted with an article we wrote about revealing its system prompt.

Aside from the relatively raw nature of the AI model Microsoft was using, at fault was a system where very long conversations would push the conditioning system prompt outside of its context window (like a form of short-term memory), allowing all hell to break loose through jailbreaks that people documented on Reddit. At one point, Bing Chat called me “the culprit and the enemy” for revealing some of its weaknesses. Some people thought Bing Chat was sentient, despite AI experts’ assurances to the contrary. It was a disaster in the press, but Microsoft didn’t flinch, and it ultimately reigned in some of Bing Chat’s wild proclivities and opened the bot widely to the public. Today, Bing Chat is now known as Microsoft Copilot, and it’s baked into Windows.

US Copyright Office says no to AI copyright authors

Enlarge / An AI-generated image that won a prize at the Colorado State Fair in 2022, later denied US copyright registration.

Jason M. Allen

In February, the US Copyright Office issued a key ruling on AI-generated art, revoking the copyright previously granted to the AI-assisted comic book “Zarya of the Dawn” in September 2022. The decision, influenced by the revelation that the images were created using the AI-powered Midjourney image generator, stated that only the text and arrangement of images and text by Kashtanova were eligible for copyright protection. It was the first hint that AI-generated imagery without human-authored elements could not be copyrighted in the United States.

This stance was further cemented in August when a US federal judge ruled that art created solely by AI cannot be copyrighted. In September, the US Copyright Office rejected the registration for an AI-generated image that won a Colorado State Fair art contest in 2022. As it stands now, it appears that purely AI-generated art (without substantial human authorship) is in the public domain in the United States. This stance could be further clarified or changed in the future by judicial rulings or legislation.

A song of hype and fire: The 10 biggest AI stories of 2023 Read More »