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Chongqing the world’s largest city in pictures
https://www.theguardian.com/world/gallery/2025/apr/27/chongqing-the-worlds-largest-city-in-pictures
The largest city in the world is as big as Austria, but few people have ever heard of it. The megacity of 34 million people in central of China is the emblem of the fastest urban revolution on the planet.
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Fluent 4.0 released for Blender hard surface modeler
Beyond the boolean support, this add-on also provides cloth panel, grid, head screw, wire and pipe tool.
https://cgthoughts.gumroad.com/
https://superhivemarket.com/creators/cg-thoughts?ref=82
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Arto T. – A workflow for creating photorealistic, equirectangular 360° panoramas in ComfyUI using Flux
https://civitai.com/models/735980/flux-equirectangular-360-panorama
https://civitai.com/models/745010?modelVersionId=833115
The trigger phrase is “equirectangular 360 degree panorama”. I would avoid saying “spherical projection” since that tends to result in non-equirectangular spherical images.
Image resolution should always be a 2:1 aspect ratio. 1024 x 512 or 1408 x 704 work quite well and were used in the training data. 2048 x 1024 also works.
I suggest using a weight of 0.5 – 1.5. If you are having issues with the image generating too flat instead of having the necessary spherical distortion, try increasing the weight above 1, though this could negatively impact small details of the image. For Flux guidance, I recommend a value of about 2.5 for realistic scenes.
8-bit output at the moment
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Scientists claim to have discovered ‘new colour’ no one has seen before: Olo
https://www.bbc.com/news/articles/clyq0n3em41o
By stimulating specific cells in the retina, the participants claim to have witnessed a blue-green colour that scientists have called “olo”, but some experts have said the existence of a new colour is “open to argument”.
The findings, published in the journal Science Advances on Friday, have been described by the study’s co-author, Prof Ren Ng from the University of California, as “remarkable”.
(A) System inputs. (i) Retina map of 103 cone cells preclassified by spectral type (7). (ii) Target visual percept (here, a video of a child, see movie S1 at 1:04). (iii) Infrared cellular-scale imaging of the retina with 60-frames-per-second rolling shutter. Fixational eye movement is visible over the three frames shown.
(B) System outputs. (iv) Real-time per-cone target activation levels to reproduce the target percept, computed by: extracting eye motion from the input video relative to the retina map; identifying the spectral type of every cone in the field of view; computing the per-cone activation the target percept would have produced. (v) Intensities of visible-wavelength 488-nm laser microdoses at each cone required to achieve its target activation level.
(C) Infrared imaging and visible-wavelength stimulation are physically accomplished in a raster scan across the retinal region using AOSLO. By modulating the visible-wavelength beam’s intensity, the laser microdoses shown in (v) are delivered. Drawing adapted with permission [Harmening and Sincich (54)].
(D) Examples of target percepts with corresponding cone activations and laser microdoses, ranging from colored squares to complex imagery. Teal-striped regions represent the color “olo” of stimulating only M cones.
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Finn Jager – From HEIC (High Efficiency Image Container) iPhone to a Multichannel EXR
Finn Jäger has spent some time in making a sleeker tool for all you VFX nerds out there, it takes a HEIC iPhone still and exports a Multichannel EXR – the cool thing is it also converts it to acesCG and it merges the SDR base image with the gain map according to apples math hdr_rgb = sdr_rgb * (1.0 + (headroom – 1.0) * gainmap)
https://github.com/finnschi/heic-shenanigans
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Mars Lewis on the Brandolini’s Law
Brandolini’s law (or the bullshit asymmetry principle) is an internet adage coined in 2013 by Italian programmer Alberto Brandolini. It compares the considerable effort of debunking misinformation to the relative ease of creating it in the first place.
The law states: “The amount of energy needed to refute bullshit is an order of magnitude bigger than to produce it.”
https://en.wikipedia.org/wiki/Brandolini%27s_law
This is why every time you kill a lie, it feels like nothing changed. It’s why no matter how many facts you post, how many sources you cite, how many receipts you show—the swarm just keeps coming. Because while you’re out in the open doing surgery, the machine is behind the curtain spraying aerosol deceit into every vent.
The lie takes ten seconds. The truth takes ten paragraphs. And by the time you’ve written the tenth, the people you’re trying to reach have already scrolled past.
Every viral deception—the fake quote, the rigged video, the synthetic outrage—takes almost nothing to create. And once it’s out there, you’re not just correcting a fact—you’re prying it out of someone’s identity. Because people don’t adopt lies just for information. They adopt them for belonging. The lie becomes part of who they are, and your correction becomes an attack.
And still—you must correct it. Still, you must fight.
Because even if truth doesn’t spread as fast, it roots deeper. Even if it doesn’t go viral, it endures. And eventually, it makes people bulletproof to the next wave of narrative sewage.
You’re not here to win a one-day war. You’re here to outlast a never-ending invasion.
The lies are roaches. You kill one, and a hundred more scramble behind the drywall.The lies are Hydra heads. You cut one off, and two grow back. But you keep swinging anyway.
Because this isn’t about instant wins. It’s about making the cost of lying higher. It’s about being the resistance that doesn’t fold. You don’t fight because it’s easy. You fight because it’s right.
FEATURED POSTS
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Guide to Prompt Engineering
The 10 most powerful techniques:
1. Communicate the Why
2. Explain the context (strategy, data)
3. Clearly state your objectives
4. Specify the key results (desired outcomes)
5. Provide an example or template
6. Define roles and use the thinking hats
7. Set constraints and limitations
8. Provide step-by-step instructions (CoT)
9. Ask to reverse-engineer the result to get a prompt
10. Use markdown or XML to clearly separate sections (e.g., examples)
Top 10 high-ROI use cases for PMs:
1. Get new product ideas
2. Identify hidden assumptions
3. Plan the right experiments
4. Summarize a customer interview
5. Summarize a meeting
6. Social listening (sentiment analysis)
7. Write user stories
8. Generate SQL queries for data analysis
9. Get help with PRD and other templates
10. Analyze your competitors
Quick prompting scheme:
1- pass an image to JoyCaption
https://www.pixelsham.com/2024/12/23/joy-caption-alpha-two-free-automatic-caption-of-images/
2- tune the caption with ChatGPT as suggested by Pixaroma:
Craft detailed prompts for Al (image/video) generation, avoiding quotation marks. When I provide a description or image, translate it into a prompt that captures a cinematic, movie-like quality, focusing on elements like scene, style, mood, lighting, and specific visual details. Ensure that the prompt evokes a rich, immersive atmosphere, emphasizing textures, depth, and realism. Always incorporate (static/slow) camera or cinematic movement to enhance the feeling of fluidity and visual storytelling. Keep the wording precise yet descriptive, directly usable, and designed to achieve a high-quality, film-inspired result.
https://www.reddit.com/r/ChatGPT/comments/139mxi3/chatgpt_created_this_guide_to_prompt_engineering/
1. Use the 80/20 principle to learn faster
Prompt: “I want to learn about [insert topic]. Identify and share the most important 20% of learnings from this topic that will help me understand 80% of it.”
2. Learn and develop any new skill
Prompt: “I want to learn/get better at [insert desired skill]. I am a complete beginner. Create a 30-day learning plan that will help a beginner like me learn and improve this skill.”
3. Summarize long documents and articles
Prompt: “Summarize the text below and give me a list of bullet points with key insights and the most important facts.” [Insert text]
4. Train ChatGPT to generate prompts for you
Prompt: “You are an AI designed to help [insert profession]. Generate a list of the 10 best prompts for yourself. The prompts should be about [insert topic].”
5. Master any new skill
Prompt: “I have 3 free days a week and 2 months. Design a crash study plan to master [insert desired skill].”
6. Simplify complex information
Prompt: “Break down [insert topic] into smaller, easier-to-understand parts. Use analogies and real-life examples to simplify the concept and make it more relatable.”
More suggestions under the post…
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