BREAKING NEWS
LATEST POSTS
-
A Looming Threat to Bitcoin (and the financial world)- The Risk of a Quantum Hack
Advancements in quantum computing pose a potential threat to Bitcoin’s security. Google’s recent progress with its Willow quantum-computing chip has highlighted the possibility that future quantum computers could break the encryption protecting Bitcoin, enabling hackers to access secure digital wallets and potentially causing significant devaluation.
Researchers estimate that a quantum computer capable of such decryption is likely more than a decade away. Nonetheless, the Bitcoin developer community faces the complex task of upgrading the system to incorporate quantum-resistant encryption methods. Achieving consensus within the decentralized community may be a slow process, and users would eventually need to transfer their holdings to quantum-resistant addresses to safeguard their assets.
A quantum-powered attack on Bitcoin could also negatively impact traditional financial markets, possibly leading to substantial losses and a deep recession. To mitigate such threats, President-elect Donald Trump has proposed creating a strategic reserve for the government’s Bitcoin holdings.
-
posemy.art – Create Poses for Drawing Reference and AI apps in Seconds for Free
Export into compatible formats for stable diffusion:
Open Pose, Depth, Canny, Normals and Regular images
-
Mickmumpitz – Create CONSISTENT CHARACTERS from an INPUT IMAGE with FLUX and a character sheet! (ComfyUI Tutorial + Installation Guide + Lora training)
https://www.patreon.com/posts/create-from-with-115147229
Note: the image below is not from the workflow
Nodes:
Install missing nodes in the workflow through the manager.
Models:
Make sure not to mix SD1.5 and SDLX models.
Follow the details under the pdf below.
General suggesions:
– Comfy Org / Flux.1 [dev] Checkpoint model (fp8)
The manager will put it under checkpoints, which will not work.
Make sure to put it under the models/unet folder for the Load Diffusion Model node to work.
– same for realvisxlV50_v50LightningBakedvae.safetensors
it should go under models/vae
-
Emmanuel Tsekleves – Writing Research Papers
Here’s the journey of crafting a compelling paper:
1️. ABSTRACT
This is your elevator pitch.
Give a methodology overview.
Paint the problem you’re solving.
Highlight key findings and their impact.
2️. INTRODUCTION
Start with what we know.
Set the stage for our current understanding.
Hook your reader with the relevance of your work.
3️. LITERATURE REVIEW
Identify what’s unknown.
Spot the gaps in current knowledge.
Your job in the next sections is to fill this gap.
4️. METHODOLOGY
What did you do?
Outline how you’ll fill that gap.
Be transparent about your approach.
Make it reproducible so others can follow.
5️. RESULTS
Let the data speak for itself.
Present your findings clearly.
Keep it concise and focused.
6️. DISCUSSION
Now, connect the dots.
Discuss implications and significance.
How do your findings bridge the knowledge gap?
7️. CONCLUSION
Wrap it up with future directions.
What does this mean for us moving forward?
Leave the reader with a call to action or reflection.
8️. REFERENCES
Acknowledge the giants whose shoulders you stand on.
A robust reference list shows the depth of your research.
FEATURED POSTS
-
Composition – cinematography Cheat Sheet
Where is our eye attracted first? Why?
Size. Focus. Lighting. Color.
Size. Mr. White (Harvey Keitel) on the right.
Focus. He’s one of the two objects in focus.
Lighting. Mr. White is large and in focus and Mr. Pink (Steve Buscemi) is highlighted by
a shaft of light.
Color. Both are black and white but the read on Mr. White’s shirt now really stands out.
(more…)
What type of lighting?
-
MiniMax-Remover – Taming Bad Noise Helps Video Object Removal Rotoscoping
https://github.com/zibojia/MiniMax-Remover
MiniMax-Remover is a fast and effective video object remover based on minimax optimization. It operates in two stages: the first stage trains a remover using a simplified DiT architecture, while the second stage distills a robust remover with CFG removal and fewer inference steps.
