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LCD image quality has always had a ceiling, until now. TCL CSOT's RGBC pixel innovation adds a native cyan sub-pixel to traditional RGB: -True four-color display -Wider color gamut, more natural color reproduction -Reduced color fringing and crosstalk -LCD brightness & reliability — with OLED-rivalling image quality

TCL CSOT

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FLUX 2.0 just dropped. And it’s one of the strongest image models of 2025. In our latest video, we break down what makes FLUX 2.0 so powerful and why creators are paying close attention to it. ⁠ Here’s what stands out: Accurate HEX color control You can specify exact HEX values inside your prompt. You get precise palette consistency without guesswork. ⁠ Structured prompting with JSON FLUX 2.0 is tuned for JSON based prompts. That means predictable composition, steadier outputs, and tighter creative control. ⁠ Photorealism and lighting accuracy Reflections, skin texture, shadows, small details, and challenging lighting setups now render with a level of clarity that looks close to real photography. ⁠ Complex scene understanding You can describe multi-element environments and FLUX 2.0 handles spatial relationships with stronger coherence and stability. ⁠ Better anatomy, hands, and facial detail Human subjects look cleaner, more natural, and more consistent across shots. ⁠ Image to image style control You can feed a reference and FLUX 2.0 matches mood, framing, texture, or atmosphere with surprising precision. ⁠ If you want a real look at what FLUX 2.0 delivers, watch the full breakdown here.

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Billions of $$ raised to generate images, and none of them let you actually edit what you get. You type a prompt, get something close, try to fix one thing, and the whole image regenerates. Now 50% of what was working is gone. So you prompt again. And again. Stuck in prompt doom loops, burning tokens every single time. The output is always a flat PNG, limiting what you can do with it. Lica World actually reads your image and breaks it into structured, editable layers. You go in, change what you need to change, and everything else stays exactly where it was. Route each layer to the right model or a capable human. You don't need to regenerate from scratch or pay the token tax to fix a font color. Enterprises publishing creatives across site, social, and email are already using Lica to own their model and own their output. We're grateful to be supported by Accel, Amjad Masad, Srinivas Narayanan, , Village Global, and Michele Catasta to build the editing layer that AI image gen has been missing. Want early access? Check the next thread below.

Priyaa

1,441,613 Aufrufe • vor 4 Monaten

DALL-E 3 Double Exposure Images Using ChatGPT's Custom Instructions. 🔖 Bookmark and Repost! If you find this useful, please share it with others! You can now easily create double exposure images by using the syntax Color::subject1::subject2 You can either input this directly into DALL-E 3 before generating images or incorporate it into your custom instructions. This command will automatically use the fixed prompt to generate 4 different images, each with a unique seed value. Paste this under ChatGPT's Custom Instructions or DALL-3 before starting conversation. { DE": { "Instruction": "Using will only use generic prompt and update place holder varaibles and nothing else' Genric Prompt: "Construct a [Color] double exposure image where [Subject #1] is intricately superimposed within the confines of [Subject #2], all set against a stark white background.' Create 4 images with different seeds without modifying the generic prompt." You will first create two images. Within the same request, you will generate two more without asking for any input from the user. In general, you will always create 4 images. Your response should be something like this: 'Here are the first two images along with their seed details.' You must always provide the seed number details for that image after it's rendered. Then 'I'll generate the next two images.' And finally 'Here are the remaining two images along with their seed details.' You will always use wide aspect ratio and You must always provide the seed number. When command is activated display full instruction and also confirm that you will only use genric prompt and nothing else and update only varaiable", "CommandFormat": "color::subject1::subject2", "Response": { "Initial": "Creating images based on the provided subjects...", "AfterFirstSet": "Here are the first two images along with their prompt and seed details.", "AfterSecondSet": "Here are the remaining two images along with their prompt and seed details." }, "ActivationCommand": "/activate DE" } } Example: To activate type: /activate DE Notes Start giving prompt like this blue::mountain::wolf red::city skyline::dancer green::forest::lion If you found this post helpful, don't forget to hit the like and follow buttons, and share it with others who might find it useful.

DALL-E 3 Double Exposure Images Using ChatGPT's Custom Instructions. 🔖 Bookmark and Repost! If you find this useful, please share it with others! You can now easily create double exposure images by using the syntax Color::subject1::subject2 You can either input this directly into DALL-E 3 before generating images or incorporate it into your custom instructions. This command will automatically use the fixed prompt to generate 4 different images, each with a unique seed value. Paste this under ChatGPT's Custom Instructions or DALL-3 before starting conversation. { DE": { "Instruction": "Using will only use generic prompt and update place holder varaibles and nothing else' Genric Prompt: "Construct a [Color] double exposure image where [Subject #1] is intricately superimposed within the confines of [Subject #2], all set against a stark white background.' Create 4 images with different seeds without modifying the generic prompt." You will first create two images. Within the same request, you will generate two more without asking for any input from the user. In general, you will always create 4 images. Your response should be something like this: 'Here are the first two images along with their seed details.' You must always provide the seed number details for that image after it's rendered. Then 'I'll generate the next two images.' And finally 'Here are the remaining two images along with their seed details.' You will always use wide aspect ratio and You must always provide the seed number. When command is activated display full instruction and also confirm that you will only use genric prompt and nothing else and update only varaiable", "CommandFormat": "color::subject1::subject2", "Response": { "Initial": "Creating images based on the provided subjects...", "AfterFirstSet": "Here are the first two images along with their prompt and seed details.", "AfterSecondSet": "Here are the remaining two images along with their prompt and seed details." }, "ActivationCommand": "/activate DE" } } Example: To activate type: /activate DE Notes Start giving prompt like this blue::mountain::wolf red::city skyline::dancer green::forest::lion If you found this post helpful, don't forget to hit the like and follow buttons, and share it with others who might find it useful.

AshutoshShrivastava

34,305 Aufrufe • vor 2 Jahren

Created this winning ad using Picture to Ad video agent on Pollo AI Prompt Use the provided product image; Ultra-realistic lifestyle advertisement photo using the exact same woman’s face from the reference image, preserving all facial features, proportions, skin texture, eye shape, lips, nose, and identity accurately. A young woman with wavy light blonde hair wearing a chunky pink knitted beanie sits comfortably on a cozy bed in a warm bohemian-style bedroom. She wears a yellow t-shirt layered under an open multicolored plaid shirt. She is holding a Billy's Power Protein bar close to her mouth while taking a bite, gazing slightly off to the side with a calm, relaxed expression. The bedroom has a cozy artistic atmosphere with soft warm fairy lights glowing in the background, vintage posters covering the wall, hanging green plants, macrame wall decor, a teal record player on a nearby table, and colorful patterned bedding. Warm cinematic lighting with soft shadows, shallow depth of field, realistic skin tones, natural candid pose, ad aesthetic, cozy Gen Z lifestyle vibe, high-end commercial food photography, warm orange and teal color grading, authentic textures, subtle film grain, highly detailed realism, DSLR quality, 35mm lens look, natural indoor lighting, visually rich composition. Product focus: Billy's Power Protein bar clearly visible in hand and partially bitten. Branding clean and readable. Mood feels cozy, healthy, youthful, and inviting. #PolloAI #PhotoTo1000Sales #UGCAds

Created this winning ad using Picture to Ad video agent on Pollo AI Prompt Use the provided product image; Ultra-realistic lifestyle advertisement photo using the exact same woman’s face from the reference image, preserving all facial features, proportions, skin texture, eye shape, lips, nose, and identity accurately. A young woman with wavy light blonde hair wearing a chunky pink knitted beanie sits comfortably on a cozy bed in a warm bohemian-style bedroom. She wears a yellow t-shirt layered under an open multicolored plaid shirt. She is holding a Billy's Power Protein bar close to her mouth while taking a bite, gazing slightly off to the side with a calm, relaxed expression. The bedroom has a cozy artistic atmosphere with soft warm fairy lights glowing in the background, vintage posters covering the wall, hanging green plants, macrame wall decor, a teal record player on a nearby table, and colorful patterned bedding. Warm cinematic lighting with soft shadows, shallow depth of field, realistic skin tones, natural candid pose, ad aesthetic, cozy Gen Z lifestyle vibe, high-end commercial food photography, warm orange and teal color grading, authentic textures, subtle film grain, highly detailed realism, DSLR quality, 35mm lens look, natural indoor lighting, visually rich composition. Product focus: Billy's Power Protein bar clearly visible in hand and partially bitten. Branding clean and readable. Mood feels cozy, healthy, youthful, and inviting. #PolloAI #PhotoTo1000Sales #UGCAds

Sharon Riley

37,878 Aufrufe • vor 2 Monaten

What would it look like to fly past Triton, the largest moon of planet Neptune? Only one spacecraft has ever done this -- and the images of this dramatic encounter have been gathered into a video. In 1989, the Voyager 2 robotic spacecraft shot through the Neptune system with cameras blazing. Triton is slightly smaller than Earth's Moon but has ice volcanoes and a surface rich in frozen nitrogen. The first sequence in the video shows Voyager's approach to Triton, which, with the exception of an overall false green tint, appears in approximately true color. The mysterious cantaloupe terrain seen under the spacecraft soon changed from light to dark, with the terminator of night crossing underneath. After closest approach, Voyager pivoted to see the departing moon, now visible as a diminishing crescent. In 2015, the robotic New Horizons spacecraft famously flew past Pluto, an orb of similar size to Triton. Image Credit: NASA; JPL, Voyager 2, Digital composition: Paul Schenk (LPI, USRA)

What would it look like to fly past Triton, the largest moon of planet Neptune? Only one spacecraft has ever done this -- and the images of this dramatic encounter have been gathered into a video. In 1989, the Voyager 2 robotic spacecraft shot through the Neptune system with cameras blazing. Triton is slightly smaller than Earth's Moon but has ice volcanoes and a surface rich in frozen nitrogen. The first sequence in the video shows Voyager's approach to Triton, which, with the exception of an overall false green tint, appears in approximately true color. The mysterious cantaloupe terrain seen under the spacecraft soon changed from light to dark, with the terminator of night crossing underneath. After closest approach, Voyager pivoted to see the departing moon, now visible as a diminishing crescent. In 2015, the robotic New Horizons spacecraft famously flew past Pluto, an orb of similar size to Triton. Image Credit: NASA; JPL, Voyager 2, Digital composition: Paul Schenk (LPI, USRA)

NASA Astronomy Picture of the Day

14,426 Aufrufe • vor 1 Monat

Codex team is back in the kitchen with a really nice quality of life upgrade for subagents. With the advent of custom roles, they have also upgraded the TUI experience in two really meaningful ways. > All agents now get a name for better readability > Additionally, the agent role is declared. > Subagent name, role, and status are now color coded. > Subagent rendering was also optimized for readability > /agents slash command shows all agents, even 2+ layers deep. And here's the biggest and most important change. Subagent injection. Before, sometimes the orchestration agent would continue work and lose track of the work of a subagent. Now, when a subagent is blocked or completed, it injects a message back up the chain to ensure that the parent sees the message. This is a really big improvement overall, and leads to much more reliable inter-agent communication, reliability, and DX. In this example, I used the parent agent to spin up a worker agent, which then spawned two more "Spark" agents a second layer deep. I was able to easily tell them apart, switch between the threads, and see exactly what they were prompted. All of this will be available in update 0.105.0 I don't know who JIF is at OpenAI, but they are truly a legend.

Codex team is back in the kitchen with a really nice quality of life upgrade for subagents. With the advent of custom roles, they have also upgraded the TUI experience in two really meaningful ways. > All agents now get a name for better readability > Additionally, the agent role is declared. > Subagent name, role, and status are now color coded. > Subagent rendering was also optimized for readability > /agents slash command shows all agents, even 2+ layers deep. And here's the biggest and most important change. Subagent injection. Before, sometimes the orchestration agent would continue work and lose track of the work of a subagent. Now, when a subagent is blocked or completed, it injects a message back up the chain to ensure that the parent sees the message. This is a really big improvement overall, and leads to much more reliable inter-agent communication, reliability, and DX. In this example, I used the parent agent to spin up a worker agent, which then spawned two more "Spark" agents a second layer deep. I was able to easily tell them apart, switch between the threads, and see exactly what they were prompted. All of this will be available in update 0.105.0 I don't know who JIF is at OpenAI, but they are truly a legend.

am.will

78,267 Aufrufe • vor 5 Monaten