machine learning

tyler-perry-puts-$800-million-studio-expansion-on-hold-because-of-openai’s-sora

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 / /

The Synthetic Screen —

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

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Tyler Perry in 2022.

Enlarge / Tyler Perry in 2022.

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 »

stability-announces-stable-diffusion-3,-a-next-gen-ai-image-generator

Stability announces Stable Diffusion 3, a next-gen AI image generator

AI, AI image generators, Biz & IT, dall-e, DALL-E 3, Deepfakes, Emad Mostaque, image synthesis, machine learning, open weights, openai, SDXL, source available, Stability AI, Stable Diffusion, Stable Diffusion 3, Stable Diffusion XL / /

Pics and it didn’t happen —

SD3 may bring DALL-E-like prompt fidelity to an open-weights image-synthesis model.

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Stable Diffusion 3 generation with the prompt: studio photograph closeup of a chameleon over a black background.

Enlarge / Stable Diffusion 3 generation with the prompt: studio photograph closeup of a chameleon over a black background.

On Thursday, Stability AI announced Stable Diffusion 3, an open-weights next-generation image-synthesis model. It follows its predecessors by reportedly generating detailed, multi-subject images with improved quality and accuracy in text generation. The brief announcement was not accompanied by a public demo, but Stability is opening up a waitlist today for those who would like to try it.

Stability says that its Stable Diffusion 3 family of models (which takes text descriptions called “prompts” and turns them into matching images) range in size from 800 million to 8 billion parameters. The size range accommodates allowing different versions of the model to run locally on a variety of devices—from smartphones to servers. Parameter size roughly corresponds to model capability in terms of how much detail it can generate. Larger models also require more VRAM on GPU accelerators to run.

Since 2022, we’ve seen Stability launch a progression of AI image-generation models: Stable Diffusion 1.4, 1.5, 2.0, 2.1, XL, XL Turbo, and now 3. Stability has made a name for itself as providing a more open alternative to proprietary image-synthesis models like OpenAI’s DALL-E 3, though not without controversy due to the use of copyrighted training data, bias, and the potential for abuse. (This has led to lawsuits that are unresolved.) Stable Diffusion models have been open-weights and source-available, which means the models can be run locally and fine-tuned to change their outputs.

  • Stable Diffusion 3 generation with the prompt: Epic anime artwork of a wizard atop a mountain at night casting a cosmic spell into the dark sky that says “Stable Diffusion 3” made out of colorful energy.

  • An AI-generated image of a grandma wearing a “Go big or go home sweatshirt” generated by Stable Diffusion 3.

  • Stable Diffusion 3 generation with the prompt: Three transparent glass bottles on a wooden table. The one on the left has red liquid and the number 1. The one in the middle has blue liquid and the number 2. The one on the right has green liquid and the number 3.

  • An AI-generated image created by Stable Diffusion 3.

  • Stable Diffusion 3 generation with the prompt: A horse balancing on top of a colorful ball in a field with green grass and a mountain in the background.

  • Stable Diffusion 3 generation with the prompt: Moody still life of assorted pumpkins.

  • Stable Diffusion 3 generation with the prompt: a painting of an astronaut riding a pig wearing a tutu holding a pink umbrella, on the ground next to the pig is a robin bird wearing a top hat, in the corner are the words “stable diffusion.”

  • Stable Diffusion 3 generation with the prompt: Resting on the kitchen table is an embroidered cloth with the text ‘good night’ and an embroidered baby tiger. Next to the cloth there is a lit candle. The lighting is dim and dramatic.

  • Stable Diffusion 3 generation with the prompt: Photo of an 90’s desktop computer on a work desk, on the computer screen it says “welcome”. On the wall in the background we see beautiful graffiti with the text “SD3” very large on the wall.

As far as tech improvements are concerned, Stability CEO Emad Mostaque wrote on X, “This uses a new type of diffusion transformer (similar to Sora) combined with flow matching and other improvements. This takes advantage of transformer improvements & can not only scale further but accept multimodal inputs.”

Like Mostaque said, the Stable Diffusion 3 family uses diffusion transformer architecture, which is a new way of creating images with AI that swaps out the usual image-building blocks (such as U-Net architecture) for a system that works on small pieces of the picture. The method was inspired by transformers, which are good at handling patterns and sequences. This approach not only scales up efficiently but also reportedly produces higher-quality images.

Stable Diffusion 3 also utilizes “flow matching,” which is a technique for creating AI models that can generate images by learning how to transition from random noise to a structured image smoothly. It does this without needing to simulate every step of the process, instead focusing on the overall direction or flow that the image creation should follow.

A comparison of outputs between OpenAI's DALL-E 3 and Stable Diffusion 3 with the prompt,

Enlarge / A comparison of outputs between OpenAI’s DALL-E 3 and Stable Diffusion 3 with the prompt, “Night photo of a sports car with the text “SD3″ on the side, the car is on a race track at high speed, a huge road sign with the text ‘faster.'”

We do not have access to Stable Diffusion 3 (SD3), but from samples we found posted on Stability’s website and associated social media accounts, the generations appear roughly comparable to other state-of-the-art image-synthesis models at the moment, including the aforementioned DALL-E 3, Adobe Firefly, Imagine with Meta AI, Midjourney, and Google Imagen.

SD3 appears to handle text generation very well in the examples provided by others, which are potentially cherry-picked. Text generation was a particular weakness of earlier image-synthesis models, so an improvement to that capability in a free model is a big deal. Also, prompt fidelity (how closely it follows descriptions in prompts) seems to be similar to DALL-E 3, but we haven’t tested that ourselves yet.

While Stable Diffusion 3 isn’t widely available, Stability says that once testing is complete, its weights will be free to download and run locally. “This preview phase, as with previous models,” Stability writes, “is crucial for gathering insights to improve its performance and safety ahead of an open release.”

Stability has been experimenting with a variety of image-synthesis architectures recently. Aside from SDXL and SDXL Turbo, just last week, the company announced Stable Cascade, which uses a three-stage process for text-to-image synthesis.

Listing image by Emad Mostaque (Stability AI)

Stability announces Stable Diffusion 3, a next-gen AI image generator Read More »

google-goes-“open-ai”-with-gemma,-a-free,-open-weights-chatbot-family

Google goes “open AI” with Gemma, a free, open-weights chatbot family

AI, Biz & IT, chatgpt, chatgtp, Gemini, Google, Google Gemini, LLaMA, Llama 2, machine learning, Meta, Meta Llama, Open AI models, Open weights AI, openai, source-available AI / /

Free hallucinations for all —

Gemma chatbots can run locally, and they reportedly outperform Meta’s Llama 2.

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The Google Gemma logo

On Wednesday, Google announced a new family of AI language models called Gemma, which are free, open-weights models built on technology similar to the more powerful but closed Gemini models. Unlike Gemini, Gemma models can run locally on a desktop or laptop computer. It’s Google’s first significant open large language model (LLM) release since OpenAI’s ChatGPT started a frenzy for AI chatbots in 2022.

Gemma models come in two sizes: Gemma 2B (2 billion parameters) and Gemma 7B (7 billion parameters), each available in pre-trained and instruction-tuned variants. In AI, parameters are values in a neural network that determine AI model behavior, and weights are a subset of these parameters stored in a file.

Developed by Google DeepMind and other Google AI teams, Gemma pulls from techniques learned during the development of Gemini, which is the family name for Google’s most capable (public-facing) commercial LLMs, including the ones that power its Gemini AI assistant. Google says the name comes from the Latin gemma, which means “precious stone.”

While Gemma is Google’s first major open LLM since the launch of ChatGPT (it has released smaller research models such as FLAN-T5 in the past), it’s not Google’s first contribution to open AI research. The company cites the development of the Transformer architecture, as well as releases like TensorFlow, BERT, T5, and JAX as key contributions, and it would not be controversial to say that those have been important to the field.

A chart of Gemma performance provided by Google. Google says that Gemma outperforms Meta's Llama 2 on several benchmarks.

Enlarge / A chart of Gemma performance provided by Google. Google says that Gemma outperforms Meta’s Llama 2 on several benchmarks.

Owing to lesser capability and high confabulation rates, smaller open-weights LLMs have been more like tech demos until recently, as some larger ones have begun to match GPT-3.5 performance levels. Still, experts see source-available and open-weights AI models as essential steps in ensuring transparency and privacy in chatbots. Google Gemma is not “open source” however, since that term usually refers to a specific type of software license with few restrictions attached.

In reality, Gemma feels like a conspicuous play to match Meta, which has made a big deal out of releasing open-weights models (such as LLaMA and Llama 2) since February of last year. That technique stands in opposition to AI models like OpenAI’s GPT-4 Turbo, which is only available through the ChatGPT application and a cloud API and cannot be run locally. A Reuters report on Gemma focuses on the Meta angle and surmises that Google hopes to attract more developers to its Vertex AI cloud platform.

We have not used Gemma yet; however, Google claims the 7B model outperforms Meta’s Llama 2 7B and 13B models on several benchmarks for math, Python code generation, general knowledge, and commonsense reasoning tasks. It’s available today through Kaggle, a machine-learning community platform, and Hugging Face.

In other news, Google paired the Gemma release with a “Responsible Generative AI Toolkit,” which Google hopes will offer guidance and tools for developing what the company calls “safe and responsible” AI applications.

Google goes “open AI” with Gemma, a free, open-weights chatbot family Read More »

will-smith-parodies-viral-ai-generated-video-by-actually-eating-spaghetti

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 / /

Mangia, mangia —

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

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

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 »

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Reddit sells training data to unnamed AI company ahead of IPO

AI, Axel Springer, Biz & IT, Bloomberg, chatgpt, chatgtp, image synthesis, large language models, machine learning, openai, reddit, Stable Diffusion, steve huffman, text synthesis / /

Everything has a price —

If you’ve posted on Reddit, you’re likely feeding the future of AI.

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In this photo illustration the American social news

On Friday, Bloomberg reported that Reddit has signed a contract allowing an unnamed AI company to train its models on the site’s content, according to people familiar with the matter. The move comes as the social media platform nears the introduction of its initial public offering (IPO), which could happen as soon as next month.

Reddit initially revealed the deal, which is reported to be worth $60 million a year, earlier in 2024 to potential investors of an anticipated IPO, Bloomberg said. The Bloomberg source speculates that the contract could serve as a model for future agreements with other AI companies.

After an era where AI companies utilized AI training data without expressly seeking any rightsholder permission, some tech firms have more recently begun entering deals where some content used for training AI models similar to GPT-4 (which runs the paid version of ChatGPT) comes under license. In December, for example, OpenAI signed an agreement with German publisher Axel Springer (publisher of Politico and Business Insider) for access to its articles. Previously, OpenAI has struck deals with other organizations, including the Associated Press. Reportedly, OpenAI is also in licensing talks with CNN, Fox, and Time, among others.

In April 2023, Reddit founder and CEO Steve Huffman told The New York Times that it planned to charge AI companies for access to its almost two decades’ worth of human-generated content.

If the reported $60 million/year deal goes through, it’s quite possible that if you’ve ever posted on Reddit, some of that material may be used to train the next generation of AI models that create text, still pictures, and video. Even without the deal, experts have discovered in the past that Reddit has been a key source of training data for large language models and AI image generators.

While we don’t know if OpenAI is the company that signed the deal with Reddit, Bloomberg speculates that Reddit’s ability to tap into AI hype for additional revenue may boost the value of its IPO, which might be worth $5 billion. Despite drama last year, Bloomberg states that Reddit pulled in more than $800 million in revenue in 2023, growing about 20 percent over its 2022 numbers.

Advance Publications, which owns Ars Technica parent Condé Nast, is the largest shareholder of Reddit.

Reddit sells training data to unnamed AI company ahead of IPO Read More »

new-app-always-points-to-the-supermassive-black-hole-at-the-center-of-our-galaxy

New app always points to the supermassive black hole at the center of our galaxy

AI, astronomy, Biz & IT, chatgpt, chatgtp, Galactic Center, Galactic Compass, machine learning, Matt Webb, Space, Tech / /

the final frontier —

iPhone compass app made with AI assistance locates the heart of the Milky Way.

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A photo of Galactic Compass running on an iPhone.

Enlarge / A photo of Galactic Compass running on an iPhone.

Matt Webb / Getty Images

On Thursday, designer Matt Webb unveiled a new iPhone app called Galactic Compass, which always points to the center of the Milky Way galaxy—no matter where Earth is positioned on our journey through the stars. The app is free and available now on the App Store.

While using Galactic Compass, you set your iPhone on a level surface, and a big green arrow on the screen points the way to the Galactic Center, which is the rotational core of the spiral galaxy all of us live in. In that center is a supermassive black hole known as Sagittarius A*, a celestial body from which no matter or light can escape. (So, in a way, the app is telling us what we should avoid.)

But truthfully, the location of the galactic core at any given time isn’t exactly useful, practical knowledge—at least for people who aren’t James Tiberius Kirk in Star Trek V. But it may inspire a sense of awe about our place in the cosmos.

Screenshots of Galactic Compass in action, captured by Ars Technica in a secret location.

Enlarge / Screenshots of Galactic Compass in action, captured by Ars Technica in a secret location.

Benj Edwards / Getty Images

“It is astoundingly grounding to always have a feeling of the direction of the center of the galaxy,” Webb told Ars Technica. “Your perspective flips. To begin with, it feels arbitrary. The middle of the Milky Way seems to fly all over the sky, as the Earth turns and moves in its orbit.”

Webb’s journey to creating Galactic Compass began a decade ago as an offshoot of his love for casual astronomy. “About 10 years ago, I taught myself how to point to the center of the galaxy,” Webb said. “I lived in an apartment where I had a great view of the stars, so I was using augmented reality apps to identify them, and I gradually learned my way around the sky.”

While Webb initially used an astronomy app to help locate the Galactic Center, he eventually taught himself how to always find it. He described visualizing himself on the surface of the Earth as it spins and tilts, understanding the ecliptic as a line across the sky and recognizing the center of the galaxy as an invisible point moving predictably through the constellation Sagittarius, which lies on the ecliptic line. By visualizing Earth’s orbit over the year and determining his orientation in space, he was able to point in the right direction, refining his ability through daily practice and comparison with an augmented reality app.

With a little help from AI

Our galaxy, the Milky Way, is thought to look similar to Andromeda (seen here) if you could see it from a distance. But since we're inside the galaxy, all we can see is the edge of the galactic plane.

Enlarge / Our galaxy, the Milky Way, is thought to look similar to Andromeda (seen here) if you could see it from a distance. But since we’re inside the galaxy, all we can see is the edge of the galactic plane.

Getty Images

In 2021, Webb imagined turning his ability into an app that would help take everyone on the same journey, showing a compass that points toward the galactic center instead of Earth’s magnetic north. “But I can’t write apps,” he said. “I’m a decent enough engineer, and an amateur designer, but I’ve never figured out native apps.”

That’s where ChatGPT comes in, transforming Webb’s vision into reality. With the AI assistant as his coding partner, Webb progressed step by step, crafting a simple app interface and integrating complex calculations for locating the galactic center (which involves calculating the user’s azimuth and altitude).

Still, coding with ChatGPT has its limitations. “ChatGPT is super smart, but it’s not embodied like a human, so it falls down on doing the 3D calculations,” he says. “I had to learn a lot about quaternions, which are a technique for combining 3D rotations, and even then, it’s not perfect. The app needs to be held flat to work simply because my math breaks down when the phone is upright! I’ll fix this in future versions,” Webb said.

Webb is no stranger to ChatGPT-powered creations that are more fun than practical. Last month, he launched a Kickstarter for an AI-rhyming poetry clock called the Poem/1. With his design studio, Acts Not Facts, Webb says he uses “whimsy and play to discover the possibilities in new technology.”

Whimsical or not, Webb insists that Galactic Compass can help us ponder our place in the vast universe, and he’s proud that it recently peaked at #87 in the Travel chart for the US App Store. In this case, though, it’s spaceship Earth that is traveling the galaxy while every living human comes along for the ride.

“Once you can follow it, you start to see the galactic center as the true fixed point, and we’re the ones whizzing and spinning. There it remains, the supermassive black hole at the center of our galaxy, Sagittarius A*, steady as a rock, eternal. We go about our days; it’s always there.”

New app always points to the supermassive black hole at the center of our galaxy Read More »

openai-collapses-media-reality-with-sora,-a-photorealistic-ai-video-generator

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 / /

Pics and it didn’t happen —

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

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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 »

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US says AI models can’t hold patents

AI, AI ethics, Biz & IT, copyright, machine learning, patents, US Patent and Trademark Office, USPTO / /

Robot inventors dismayed —

Inventors must be human, but there’s still a condition where AI can officially help.

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An illustrated concept of a digital brain, crossed out.

On Tuesday, the United States Patent and Trademark Office (USPTO) published guidance on inventorship for AI-assisted inventions, clarifying that while AI systems can play a role in the creative process, only natural persons (human beings) who make significant contributions to the conception of an invention can be named as inventors. It also rules out using AI models to churn out patent ideas without significant human input.

The USPTO says this position is supported by “the statutes, court decisions, and numerous policy considerations,” including the Executive Order on AI issued by President Biden. We’ve previously covered attempts, which have been repeatedly rejected by US courts, by Dr. Stephen Thaler to have an AI program called “DABUS” named as the inventor on a US patent (a process begun in 2019).

This guidance follows themes previously set by the US Copyright Office (and agreed upon by a judge) that an AI model cannot own a copyright for a piece of media and that substantial human contributions are required for copyright protection.

Even though an AI model itself cannot be named an inventor or joint inventor on a patent, using AI assistance to create an invention does not necessarily disqualify a human from holding a patent, as the USPTO explains:

“While AI systems and other non-natural persons cannot be listed as inventors on patent applications or patents, the use of an AI system by a natural person(s) does not preclude a natural person(s) from qualifying as an inventor (or joint inventors) if the natural person(s) significantly contributed to the claimed invention.”

However, the USPTO says that significant human input is required for an invention to be patentable: “Maintaining ‘intellectual domination’ over an AI system does not, on its own, make a person an inventor of any inventions created through the use of the AI system.” So a person simply overseeing an AI system isn’t suddenly an inventor. The person must make a significant contribution to the conception of the invention.

If someone does use an AI model to help create patents, the guidance describes how the application process would work. First, patent applications for AI-assisted inventions must name “the natural person(s) who significantly contributed to the invention as the inventor,” and additionally, applications must not list “any entity that is not a natural person as an inventor or joint inventor, even if an AI system may have been instrumental in the creation of the claimed invention.”

Reading between the lines, it seems the contributions made by AI systems are akin to contributions made by other tools that assist in the invention process. The document does not explicitly say that the use of AI is required to be disclosed during the application process.

Even with the published guidance, the USPTO is seeking public comment on the newly released guidelines and issues related to AI inventorship on its website.

US says AI models can’t hold patents Read More »

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OpenAI experiments with giving ChatGPT a long-term conversation memory

AI, AI memory, Biz & IT, chatbot, chatbots, chatgpt, chatgtp, GPT-4, GPT-4-turbo, large language models, machine learning / /

“I remember…the Alamo” —

AI chatbot “memory” will recall facts from previous conversations when enabled.

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A pixelated green illustration of a pair of hands looking through file records.

Enlarge / When ChatGPT looks things up, a pair of green pixelated hands look through paper records, much like this. Just kidding.

Benj Edwards / Getty Images

On Tuesday, OpenAI announced that it is experimenting with adding a form of long-term memory to ChatGPT that will allow it to remember details between conversations. You can ask ChatGPT to remember something, see what it remembers, and ask it to forget. Currently, it’s only available to a small number of ChatGPT users for testing.

So far, large language models have typically used two types of memory: one baked into the AI model during the training process (before deployment) and an in-context memory (the conversation history) that persists for the duration of your session. Usually, ChatGPT forgets what you have told it during a conversation once you start a new session.

Various projects have experimented with giving LLMs a memory that persists beyond a context window. (The context window is the hard limit on the number of tokens the LLM can process at once.) The techniques include dynamically managing context history, compressing previous history through summarization, links to vector databases that store information externally, or simply periodically injecting information into a system prompt (the instructions ChatGPT receives at the beginning of every chat).

A screenshot of ChatGPT memory controls provided by OpenAI.

Enlarge / A screenshot of ChatGPT memory controls provided by OpenAI.

OpenAI

OpenAI hasn’t explained which technique it uses here, but the implementation reminds us of Custom Instructions, a feature OpenAI introduced in July 2023 that lets users add custom additions to the ChatGPT system prompt to change its behavior.

Possible applications for the memory feature provided by OpenAI include explaining how you prefer your meeting notes to be formatted, telling it you run a coffee shop and having ChatGPT assume that’s what you’re talking about, keeping information about your toddler that loves jellyfish so it can generate relevant graphics, and remembering preferences for kindergarten lesson plan designs.

Also, OpenAI says that memories may help ChatGPT Enterprise and Team subscribers work together better since shared team memories could remember specific document formatting preferences or which programming frameworks your team uses. And OpenAI plans to bring memories to GPTs soon, with each GPT having its own siloed memory capabilities.

Memory control

Obviously, any tendency to remember information brings privacy implications. You should already know that sending information to OpenAI for processing on remote servers introduces the possibility of privacy leaks and that OpenAI trains AI models on user-provided information by default unless conversation history is disabled or you’re using an Enterprise or Team account.

Along those lines, OpenAI says that your saved memories are also subject to OpenAI training use unless you meet the criteria listed above. Still, the memory feature can be turned off completely. Additionally, the company says, “We’re taking steps to assess and mitigate biases, and steer ChatGPT away from proactively remembering sensitive information, like your health details—unless you explicitly ask it to.”

Users will also be able to control what ChatGPT remembers using a “Manage Memory” interface that lists memory items. “ChatGPT’s memories evolve with your interactions and aren’t linked to specific conversations,” OpenAI says. “Deleting a chat doesn’t erase its memories; you must delete the memory itself.”

ChatGPT’s memory features are not currently available to every ChatGPT account, so we have not experimented with it yet. Access during this testing period appears to be random among ChatGPT (free and paid) accounts for now. “We are rolling out to a small portion of ChatGPT free and Plus users this week to learn how useful it is,” OpenAI writes. “We will share plans for broader roll out soon.”

OpenAI experiments with giving ChatGPT a long-term conversation memory Read More »

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The Super Bowl’s best and wackiest AI commercials

AI, american football, Anthropic, Biz & IT, Commercial, commercials, Football, Google, large language models, machine learning, microsoft, Super Bowl / /

Superb Owl News —

It’s nothing like “crypto bowl” in 2022, but AI made a notable splash during the big game.

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A still image from BodyArmor's 2024

Enlarge / A still image from BodyArmor’s 2024 “Field of Fake” Super Bowl commercial.

BodyArmor

Heavily hyped tech products have a history of appearing in Super Bowl commercials during football’s biggest game—including the Apple Macintosh in 1984, dot-com companies in 2000, and cryptocurrency firms in 2022. In 2024, the hot tech in town is artificial intelligence, and several companies showed AI-related ads at Super Bowl LVIII. Here’s a rundown of notable appearances that range from serious to wacky.

Microsoft Copilot

Microsoft Game Day Commercial | Copilot: Your everyday AI companion.

It’s been a year since Microsoft launched the AI assistant Microsoft Copilot (as “Bing Chat“), and Microsoft is leaning heavily into its AI-assistant technology, which is powered by large language models from OpenAI. In Copilot’s first-ever Super Bowl commercial, we see scenes of various people with defiant text overlaid on the screen: “They say I will never open my own business or get my degree. They say I will never make my movie or build something. They say I’m too old to learn something new. Too young to change the world. But I say watch me.”

Then the commercial shows Copilot creating solutions to some of these problems, with prompts like, “Generate storyboard images for the dragon scene in my script,” “Write code for my 3d open world game,” “Quiz me in organic chemistry,” and “Design a sign for my classic truck repair garage Mike’s.”

Of course, since generative AI is an unfinished technology, many of these solutions are more aspirational than practical at the moment. On Bluesky, writer Ed Zitron put Microsoft’s truck repair logo to the test and saw results that weren’t nearly as polished as those seen in the commercial. On X, others have criticized and poked fun at the “3d open world game” generation prompt, which is a complex task that would take far more than a single, simple prompt to produce useful code.

Google Pixel 8 “Guided Frame” feature

Javier in Frame | Google Pixel SB Commercial 2024.

Instead of focusing on generative aspects of AI, Google’s commercial showed off a feature called “Guided Frame” on the Pixel 8 phone that uses machine vision technology and a computer voice to help people with blindness or low vision to take photos by centering the frame on a face or multiple faces. Guided Frame debuted in 2022 in conjunction with the Google Pixel 7.

The commercial tells the story of a person named Javier, who says, “For many people with blindness or low vision, there hasn’t always been an easy way to capture daily life.” We see a simulated blurry first-person view of Javier holding a smartphone and hear a computer-synthesized voice describing what the AI model sees, directing the person to center on a face to snap various photos and selfies.

Considering the controversies that generative AI currently generates (pun intended), it’s refreshing to see a positive application of AI technology used as an accessibility feature. Relatedly, an app called Be My Eyes (powered by OpenAI’s GPT-4V) also aims to help low-vision people interact with the world.

Despicable Me 4

Despicable Me 4 – Minion Intelligence (Big Game Spot).

So far, we’ve covered a couple attempts to show AI-powered products as positive features. Elsewhere in Super Bowl ads, companies weren’t as generous about the technology. In an ad for the film Despicable Me 4, we see two Minions creating a series of terribly disfigured AI-generated still images reminiscent of Stable Diffusion 1.4 from 2022. There’s three-legged people doing yoga, a painting of Steve Carell and Will Ferrell as Elizabethan gentlemen, a handshake with too many fingers, people eating spaghetti in a weird way, and a pair of people riding dachshunds in a race.

The images are paired with an earnest voiceover that says, “Artificial intelligence is changing the way we see the world, showing us what we never thought possible, transforming the way we do business, and bringing family and friends closer together. With artificial intelligence, the future is in good hands.” When the voiceover ends, the camera pans out to show hundreds of Minions generating similarly twisted images on computers.

Speaking of image synthesis at the Super Bowl, people mistook a Christian commercial created by He Gets Us, LLC as having been AI-generated, likely due to its gaudy technicolor visuals. With the benefit of a YouTube replay and the ability to look at details, the “He washed feet” commercial doesn’t appear AI-generated to us, but it goes to show how the concept of image synthesis has begun to cast doubt on human-made creations.

The Super Bowl’s best and wackiest AI commercials Read More »

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Report: Sam Altman seeking trillions for AI chip fabrication from UAE, others

AI, AI chips, Biz & IT, Google Gemini, large language models, machine learning, microsoft, Microsoft Copilot, openai, sam altman, semiconductor manufacturing, text synthesis, UAE / /

chips ahoy —

WSJ: Audacious $5-$7 trillion investment would aim to expand global AI chip supply.

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WASHINGTON, DC - JANUARY 11: OpenAI Chief Executive Officer Sam Altman walks on the House side of the U.S. Capitol on January 11, 2024 in Washington, DC. Meanwhile, House Freedom Caucus members who left a meeting in the Speakers office say that they were talking to the Speaker about abandoning the spending agreement that Johnson announced earlier in the week. (Photo by Kent Nishimura/Getty Images)

Enlarge / OpenAI Chief Executive Officer Sam Altman walks on the House side of the US Capitol on January 11, 2024, in Washington, DC. (Photo by Kent Nishimura/Getty Images)

Getty Images

On Thursday, The Wall Street Journal reported that OpenAI CEO Sam Altman is in talks with investors to raise as much as $5 trillion to $7 trillion for AI chip manufacturing, according to people familiar with the matter. The funding seeks to address the scarcity of graphics processing units (GPUs) crucial for training and running large language models like those that power ChatGPT, Microsoft Copilot, and Google Gemini.

The high dollar amount reflects the huge amount of capital necessary to spin up new semiconductor manufacturing capability. “As part of the talks, Altman is pitching a partnership between OpenAI, various investors, chip makers and power providers, which together would put up money to build chip foundries that would then be run by existing chip makers,” writes the Wall Street Journal in its report. “OpenAI would agree to be a significant customer of the new factories.”

To hit these ambitious targets—which are larger than the entire semiconductor industry’s current $527 billion global sales combined—Altman has reportedly met with a range of potential investors worldwide, including sovereign wealth funds and government entities, notably the United Arab Emirates, SoftBank CEO Masayoshi Son, and representatives from Taiwan Semiconductor Manufacturing Co. (TSMC).

TSMC is the world’s largest dedicated independent semiconductor foundry. It’s a critical linchpin that companies such as Nvidia, Apple, Intel, and AMD rely on to fabricate SoCs, CPUs, and GPUs for various applications.

Altman reportedly seeks to expand the global capacity for semiconductor manufacturing significantly, funding the infrastructure necessary to support the growing demand for GPUs and other AI-specific chips. GPUs are excellent at parallel computation, which makes them ideal for running AI models that heavily rely on matrix multiplication to work. However, the technology sector currently faces a significant shortage of these important components, constraining the potential for AI advancements and applications.

In particular, the UAE’s involvement, led by Sheikh Tahnoun bin Zayed al Nahyan, a key security official and chair of numerous Abu Dhabi sovereign wealth vehicles, reflects global interest in AI’s potential and the strategic importance of semiconductor manufacturing. However, the prospect of substantial UAE investment in a key tech industry raises potential geopolitical concerns, particularly regarding the US government’s strategic priorities in semiconductor production and AI development.

The US has been cautious about allowing foreign control over the supply of microchips, given their importance to the digital economy and national security. Reflecting this, the Biden administration has undertaken efforts to bolster domestic chip manufacturing through subsidies and regulatory scrutiny of foreign investments in important technologies.

To put the $5 trillion to $7 trillion estimate in perspective, the White House just today announced a $5 billion investment in R&D to advance US-made semiconductor technologies. TSMC has already sunk $40 billion—one of the largest foreign investments in US history—into a US chip plant in Arizona. As of now, it’s unclear whether Altman has secured any commitments toward his fundraising goal.

Updated on February 9, 2024 at 8: 45 PM Eastern with a quote from the WSJ that clarifies the proposed relationship between OpenAI and partners in the talks.

Report: Sam Altman seeking trillions for AI chip fabrication from UAE, others Read More »

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ChatGPT’s new @-mentions bring multiple personalities into your AI convo

agentic AI, AI, AI agents, Biz & IT, chatgpt, ChatGPT Plus, chatgtp, GPT Store, GPT-4, GPT-4-turbo, GPTs, large language models, machine learning, openai / /

team of rivals —

Bring different AI roles into the same chatbot conversation history.

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Illustration of a man jugging at symbols.

Enlarge / With so many choices, selecting the perfect GPT can be confusing.

On Tuesday, OpenAI announced a new feature in ChatGPT that allows users to pull custom personalities called “GPTs” into any ChatGPT conversation with the @ symbol. It allows a level of quasi-teamwork within ChatGPT among expert roles that was previously impractical, making collaborating with a team of AI agents within OpenAI’s platform one step closer to reality.

“You can now bring GPTs into any conversation in ChatGPT – simply type @ and select the GPT,” wrote OpenAI on the social media network X. “This allows you to add relevant GPTs with the full context of the conversation.”

OpenAI introduced GPTs in November as a way to create custom personalities or roles for ChatGPT to play. For example, users can build their own GPTs to focus on certain topics or certain skills. Paid ChatGPT subscribers can also freely download a host of GPTs developed by other ChatGPT users through the GPT Store.

Previously, if you wanted to share information between GPT profiles, you had to copy the text, select a new chat with the GPT, paste it, and explain the context of what the information means or what you want to do with it. Now, ChatGPT users can stay in the default ChatGPT window and bring in GPTs as needed without losing the history of the conversation.

For example, we created a “Wellness Guide” GPT that is crafted as an expert in human health conditions (of course, this being ChatGPT, always consult a human doctor if you’re having medical problems), and we created a “Canine Health Advisor” for dog-related health questions.

A screenshot of ChatGPT where we @-mentioned a human wellness advisor, then a dog advisor in the same conversation history.

Enlarge / A screenshot of ChatGPT where we @-mentioned a human wellness advisor, then a dog advisor in the same conversation history.

Benj Edwards

We started in a default ChatGPT chat, hit the @ symbol, then typed the first few letters of “Wellness” and selected it from a list. It filled out the rest. We asked a question about food poisoning in humans, and then we switched to the canine advisor in the same way with an @ symbol and asked about the dog.

Using this feature, you could alternatively consult, say, an “ad copywriter” GPT and an “editor” GPT—ask the copywriter to write some text, then rope in the editor GPT to check it, looking at it from a different angle. Different system prompts (the instructions that define a GPT’s personality) make for significant behavior differences.

We also tried swapping between GPT profiles that write software and others designed to consult on historical tech subjects. Interestingly, ChatGPT does not differentiate between GPTs as different personalities as you change. It will still say, “I did this earlier” when a different GPT is talking about a previous GPT’s output in the same conversation history. From its point of view, it’s just ChatGPT and not multiple agents.

From our vantage point, this feature seems to represent baby steps toward a future where GPTs, as independent agents, could work together as a team to fulfill more complex tasks directed by the user. Similar experiments have been done outside of OpenAI in the past (using API access), but OpenAI has so far resisted a more agentic model for ChatGPT. As we’ve seen (first with GPTs and now with this), OpenAI seems to be slowly angling toward that goal itself, but only time will tell if or when we see true agentic teamwork in a shipping service.

ChatGPT’s new @-mentions bring multiple personalities into your AI convo Read More »