OpenAI’s New AI Model: 50x Faster!
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Nagyon jó videós vagy, kedvelem a tartalmaid, informatívak és érdekesek, nagyon érdekelnek a mesterséges intelligenciás (AI) tartalmak . 😊
0:35 : What? [MISSINGNO] is evolving!
ai channel 2 second papers coming soon
How does it get from noise to such a clear image in only one step? It’s crazy how fast things are changing.
Flux.1 could do similar few step inference.
Imagine using that “neural net Doom”- technique on real world data? We could build a complete simulation of the entire planet.
It was my Startup idea for 2 years but now I realised it’s a little bit too delusional for me to execute so now I am trying to build a platform for creators to create their dream utilise generative designing and AI agents
If we had a computer the size of the moon, we probably could.
Interesting, i need to check the papers
I thought the editing mistake 2 minutes in was going to be ai making a 2 minutes paper episode
When this works realtime in VR, going to see a lot of social changes.
The word „social“ won’t exist any more.
I like when the vidoes are closer to two minutes. Thank you.
Waiting on Neural Two Minute Papers: The Video Game. Blast your way through AI models, fellow slayer-scholars. 😈
We are living in the singularity, with fascinating and terrifying implications!
2:02 was that an editing mistake or was it supposed to be like this
I thought an ad started suddenly lol
WHAT A TIME TO BE ALIVE!!!!
I love❤ the bumper directly at the middle of video 🙂
I was hoping to see a noise-correcting animation for the Two Minute Paper logo, we would all had to hold on to our papers
The potential of consistency models in animation is exciting! Imagine animators creating scenes in minutes rather than hours, a whole new world of storytelling might be on the horizon.
If a major task in a job is fine in minutes instead of hours, so 60x productivity, the job is probably obsolete (as a job. L, so with it’s demand etc; the activity could be done anyway as a hobby).
I can definitely envision a future game engine that’s just a huge series of AI prompts.
i feel like we are getting close to the holodeck…maybe not the hologram part, but the way the programs are made via prompts.
This new development with OpenAI’s *Consistency Models* is truly groundbreaking. We’re now entering a phase where the generation of complex data, such as images, audio, and video, can happen in just **1 or 2 steps** instead of the traditional 20+ steps required by *diffusion models*. This shift isn’t just a technical leap; it’s a fundamental transformation in the speed and efficiency of AI.
Imagine this: if we can now create high-quality images from noise in a fraction of the time, the potential applications are endless. Real-time graphical enhancements in **video games**, such as artistic filters or ultra-realistic low-frame renders, become viable, even on consumer-grade hardware. Essentially, these *consistency models* act as ultra-fast filters, enabling immersive, real-time graphics without the need for massive computational power.
Moreover, this rapid image generation hints at something even more revolutionary—**general AI models** capable of handling *text*, *audio*, *video*, and even *robotic control* in real time. If an AI can generate visuals this efficiently, what’s stopping it from handling other modalities like *voice commands* or even controlling physical systems? We could be on the cusp of AI that can **play video games**, control robotic systems, interact with us in natural language, and even act as personal assistants—all from a single, unified software platform.
For gaming, the implications are wild. Imagine a super-intelligent AI trained to not only play games but also *become your personal coach* or *even play alongside you*—predicting strategies, executing flawless maneuvers, and adapting in real-time. This isn’t just a gaming revolution, but a step toward **AI-enhanced creativity** where artists, gamers, and developers alike can harness AI to generate art, environments, and even entire worlds at speeds previously thought impossible.
In short, this advancement in AI brings us much closer to a world where **general-purpose AI**—capable of generating text, images, videos, and interacting across multiple domains—can be deployed on **consumer hardware**. It could revolutionize everything from **video game graphics**, to **AI assistants**, to **robotic control**, turning your computer into the ultimate multi-purpose tool for creativity, entertainment, and productivity.
Yeah, except that with SDXL they already experimented with no less than four distinct methods to get from 20 steps to 1-4 steps: Turbo, LCM, Lightning and Hyper. Flux also applied the methodology to get the Schnell model.
This is fascinating. It frames improvements in tech as direct ways to improve the game design and play experiences, which is something that a lot of graphical upgrades really don’t do under the modern paradigm. There’s still the problem of coherence over time that would make it really hard to make a game that makes any sense, but even just the ability to make the graphics part of the interface has some really interesting potential. You could handmake waypoints in the world and in the plot and have the computer create filler to get you from one to the next in a pretty immersive way. It isn’t enough to have an extemporaneous gaming experience but it’s enough to allow developers to expand on branching narratives or filling out a world to a much greater extent.
Thx a lot for comparing with Flux-schnell and next time plz mention Flow Matching to 😉 explaining how to distill flows from diffusion and then training Models on that