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SLAM XCAM 8K VR180 3D Camera
8K 30FPS VR180 3D Video | Dual 1/1.5″ CMOS Sensors | 10-bit Color | Snapdragon8 GN2 | Android13 | 6.67″AMOLED|5000mAh |100Mbps Data
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Invoke.com – The Gen AI Platform for Pro Studios
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How does Stable Diffusion work?
https://stable-diffusion-art.com/how-stable-diffusion-work/
Stable Diffusion is a latent diffusion model that generates AI images from text. Instead of operating in the high-dimensional image space, it first compresses the image into the latent space.
Stable Diffusion belongs to a class of deep learning models called diffusion models. They are generative models, meaning they are designed to generate new data similar to what they have seen in training. In the case of Stable Diffusion, the data are images.
Why is it called the diffusion model? Because its math looks very much like diffusion in physics. Let’s go through the idea.
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Hunyuan video-to-video re-styling
The open-source community has figured out how to run Hunyuan V2V using LoRAs.
You’ll need to install Kijai’s ComfyUI-HunyuanLoom and LoRAs, which you can either train yourself or find on Civitai.
1) you’ll need HunyuanLoom, after install, workflow found in the repo.
https://github.com/logtd/ComfyUI-HunyuanLoom
2) John Wick lora found here.
https://civitai.com/models/1131159/john-wick-hunyuan-video-lora -
Seaweed APT – Diffusion Adversarial Post-Training for One-Step Video Generation
https://cdn.seaweed-apt.com/assets/showreel/seaweed-apt.mp4
This demonstrate large-scale text-to-video generation with a single neural function evaluation (1NFE) by using our proposed adversarial post-training technique. Our model generates 2 seconds of 1280×720 24fps videos in real-time
FEATURED POSTS
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What the Boeing 737 MAX’s crashes can teach us about production business – the effects of commoditisation
Airplane manufacturing is no different from mortgage lending or insulin distribution or make-believe blood analyzing software (or VFX?) —another cash cow for the one percent, bound inexorably for the slaughterhouse.
The beginning of the end was “Boeing’s 1997 acquisition of McDonnell Douglas, a dysfunctional firm with a dilapidated aircraft plant in Long Beach and a CEO (Harry Stonecipher) who liked to use what he called the “Hollywood model” for dealing with engineers: Hire them for a few months when project deadlines are nigh, fire them when you need to make numbers.” And all that came with it. “Stonecipher’s team had driven the last nail in the coffin of McDonnell’s flailing commercial jet business by trying to outsource everything but design, final assembly, and flight testing and sales.”
It is understood, now more than ever, that capitalism does half-assed things like that, especially in concert with computer software and oblivious regulators.
There was something unsettlingly familiar when the world first learned of MCAS in November, about two weeks after the system’s unthinkable stupidity drove the two-month-old plane and all 189 people on it to a horrific death. It smacked of the sort of screwup a 23-year-old intern might have made—and indeed, much of the software on the MAX had been engineered by recent grads of Indian software-coding academies making as little as $9 an hour, part of Boeing management’s endless war on the unions that once represented more than half its employees.
Down in South Carolina, a nonunion Boeing assembly line that opened in 2011 had for years churned out scores of whistle-blower complaints and wrongful termination lawsuits packed with scenes wherein quality-control documents were regularly forged, employees who enforced standards were sabotaged, and planes were routinely delivered to airlines with loose screws, scratched windows, and random debris everywhere.
Shockingly, another piece of the quality failure is Boeing securing investments from all airliners, starting with SouthWest above all, to guarantee Boeing’s production lines support in exchange for fair market prices and favorite treatments. Basically giving Boeing financial stability independently on the quality of their product. “Those partnerships were but one numbers-smoothing mechanism in a diversified tool kit Boeing had assembled over the previous generation for making its complex and volatile business more palatable to Wall Street.”
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ComfyDock – The Easiest (Free) Way to Safely Run ComfyUI Sessions in a Boxed Container
https://www.reddit.com/r/comfyui/comments/1j2x4qv/comfydock_the_easiest_free_way_to_run_comfyui_in/
ComfyDock is a tool that allows you to easily manage your ComfyUI environments via Docker.
Common Challenges with ComfyUI
- Custom Node Installation Issues: Installing new custom nodes can inadvertently change settings across the whole installation, potentially breaking the environment.
- Workflow Compatibility: Workflows are often tested with specific custom nodes and ComfyUI versions. Running these workflows on different setups can lead to errors and frustration.
- Security Risks: Installing custom nodes directly on your host machine increases the risk of malicious code execution.
How ComfyDock Helps
- Environment Duplication: Easily duplicate your current environment before installing custom nodes. If something breaks, revert to the original environment effortlessly.
- Deployment and Sharing: Workflow developers can commit their environments to a Docker image, which can be shared with others and run on cloud GPUs to ensure compatibility.
- Enhanced Security: Containers help to isolate the environment, reducing the risk of malicious code impacting your host machine.