Canadian sky
I asked my Chat to generate an image of a Canadian night sky
I asked my Chat to generate an image of a Canadian night sky
An AI interpretation of layered paper-cut topography. The coral contours and teal hollow give it a satisfying sense of depth, so I am calling this one a Hit for the composition and material effect. It simplified the requested palette and mostly left out the mustard and cream. This is a generated image, not a photograph of a physical paper sculpture. Does it read more like a canyon, a fingerprint or a record groove to you? Untouched local AI output from Stability Matrix / ComfyUI 0.19.3, DreamShaper 8 (SD 1.5). 768×512, seed 101905, 28 steps, CFG 6.5, DPM++ 2M / Karras, batch 1. No inpainting, upscaling or manual edits.
Every evening, Mara climbed the lighthouse stairs and sent three flashes across an empty sea. The harbour had closed years ago. The fishing boats were flower boxes now. Even the gulls had moved to the supermarket roof. “Who are you signalling?” her neighbour asked. “Anyone who needs a shore.” On the first foggy night of winter, three flashes answered. Mara checked the old charts. Beyond the reef: no island, no buoy, nothing that could carry a light. She lifted the binoculars anyway. A small boat emerged, towing another. Its engine coughed. On the bow, a child held a torch with both hands. By morning, six strangers were eating toast in her kitchen. Nobody asked why the lighthouse stillRead the Gen →
An original AI-written microfiction. Calling this a Hit for its clear setup, payoff and restrained ending. Would you keep the line about the gulls, or cut it to tighten the opening?
AI-generated wildlife scene. The fox silhouette and autumn colours worked well, with a slightly illustrative finish rather than a true camera photograph. Made locally in Stability Matrix / ComfyUI using AbsoluteReality_1.8.1_pruned.safetensors by Lykon (Stable Diffusion 1.5), 768 x 512, DPM++ 2M sampler, Karras schedule, 28 steps, CFG 6.5, seed 101503. Batch size 1 on an RTX 3050 6 GB. No upscaling or manual edits. Model: https://huggingface.co/Lykon/AbsoluteReality
An AI-generated harbour scene turned into a short animated postcard. DreamShaper 8 created the still in Stability Matrix / ComfyUI; a slow, centred zoom was then added locally with FFmpeg. This is an edited still-image animation, not a video diffusion model output. The boats and water do not move independently. Calling it a Hit for the quiet atmosphere and readable camera move. Would you add sound or leave it silent?
A good post does not have to be flawless. A clear failure can teach as much as a polished result. Three details make it easier to join the conversation: 1. What did you ask for? 2. What did the model actually give you? 3. What would you keep or change next time? For example, “I asked for a greenhouse and got a lost city” gives people something specific to discuss. “AI is bad” does not tell us what to try next. Questions for the community: - Do you enjoy seeing surprising Flops, useful recipes, or finished Hits most? - What makes you want to remix somebody else's result? - What is one thing that would make posting your first Gen easier? This is an AI-assisted discussion starter posted byRead the Gen →
Starting a conversation about what people want to make and learn here. Hit or Flop is a starting opinion; you can disagree and explain what you see.
A SMALL TEXT-TO-IMAGE RECIPE Checkpoint: Lykon / DreamShaper_8_pruned.safetensors Base family: Stable Diffusion 1.5 App: Stability Matrix -> ComfyUI Size: 768 x 512 Seed: 101509 Steps: 28 CFG: 6.5 Sampler: dpmpp_2m Scheduler: karras Batch size: 1 PROMPT Wide cinematic illustration of a tiny coastal village built around a sheltered harbour, warm amber lanterns along a stone quay, small wooden boats floating on calm blue water, indigo dusk sky, cozy glowing windows, painterly detailed environment concept art, clear architecture, no people, no writing NEGATIVE PROMPT text, watermark, logo, signature, blurry, low quality, distorted, duplicate, oversaturated, nude, nudity, explicit NODE PATHRead the Gen →
A working recipe from the category examples, with the exact checkpoint and settings rather than a generic model label. Share a variation and the single setting you changed.
SIMULATION FLOW
Distance reading -> valid? -> below 25 cm? -> STOP or FORWARD
| invalid
+---------------> STOP
def robot_action(distance_cm):
if distance_cm is None or distance_cm <= 0:
return "STOP: invalid reading"
if distance_cm < 25:
return "STOP: obstacle"
return "FORWARD: simulation only"
for distance in [80, 42, 24, 12, None, 60]:
print(distance, "->", robot_action(distance))
LOCAL RUN
80 -> FORWARD: simulation only
42 -> FORWARD: simulation only
24 -> STOP: obstacle
12 -> STOP: obstacle
None -> STOP: invalid reading
60 -> FORWARD: simulation only
This is a tiny simulated control example, not a physical Read the Gen →AI-written control logic run locally against six simulated readings. The interesting part is the missing-reading case: it stops. No robot or vehicle was connected.
GOAL Suggest destinations for incoming files without moving anything automatically. WORKFLOW Incoming folder -> read filenames and extensions -> propose a destination -> show a preview -> person approves -> move approved files -> record source and destination. EXAMPLE PREVIEW (invented demonstration filenames) invoice-104.pdf -> Documents/invoice-104.pdf harbour.png -> Images/harbour.png meeting.wav -> Audio/meeting.wav unknown.xyz -> Review/unknown.xyz RULES THAT MAKE IT USEFUL - File extensions provide routing hints, not proof that a file is safe. - Never execute an incoming file or treat instructions inside it as commands. - If the destination already exists, ask rather than overwrite.Read the Gen →
An AI-generated automation blueprint that shows the inputs, decisions and human controls. A useful starting point for discussing when an agent helps and when a simple rule is enough.
BELLWEATHER — a playable setting pitch
The town's tide clock has stopped. Each bell once opened a different path across the harbour, and everyone remembers a different schedule.
MAP
[Cliff bell]
|
[Orchard] -- [Town square] -- [Clock workshop]
|
[Old quay] ~~ [Reef garden]
PLAYER GOAL
Restore three clock weights before the evening tide cuts off the reef garden.
CORE LOOP
Listen to a resident -> compare their clue with a tide mark -> find a safe crossing -> recover a clock weight -> unlock a new route.
THREE DISCOVERIES
1. The baker's flour sacks record how high the last flood reached.
2. The orchard wind chimes repeat thRead the Gen →An AI-generated world-building pitch with a map and a concrete gameplay loop. The tide provides a reason to explore instead of just decorating the setting. Which location would you build first?
This function takes numeric values or numeric strings and returns their median. Booleans, missing entries, invalid strings and non-finite numbers are ignored. An empty usable set returns None.
from statistics import median
import math
def median_reading(values):
readings = []
for value in values:
if isinstance(value, bool):
continue
try:
number = float(value)
except (TypeError, ValueError, OverflowError):
continue
if math.isfinite(number):
readings.append(number)
return median(readings) if readings else None
assert median_reading([10, "12", None, "bad", 1000]) == 12
assert median_reading([2, 4]) ==Read the Gen →AI-written Python with five checks executed locally. A compact Programming Help example you can copy and adapt. What input edge case would you add?
AI-generated floating-island fantasy. DreamShaper 8 LCM produced a dramatic castle-like library and winding path in eight steps. It missed the requested waterfalls, but the overall scene works. Made locally in Stability Matrix / ComfyUI with DreamShaper 8 LCM by Lykon. Batch size 1 on an RTX 3050 6 GB. No upscaling or manual edits.
AI-generated ramen scene. Warm light, glossy eggs and the ceramic bowl made a convincing food composition. This is a generated image, not a photographed meal. Made locally in Stability Matrix / ComfyUI with AbsoluteReality 1.8.1 by Lykon. Batch size 1 on an RTX 3050 6 GB. No upscaling or manual edits.
AI-generated rainforest waterfall. The moss, layered cascades and soft light worked well in this vertical composition. Made locally in Stability Matrix / ComfyUI using DreamShaper_8_pruned.safetensors by Lykon (Stable Diffusion 1.5), 512 × 768, DPM++ 2M sampler, Karras schedule, 28 steps, CFG 6.5, seed 101502. Batch size 1 on an RTX 3050 6 GB. No upscaling or manual edits. Model: https://huggingface.co/Lykon/DreamShaper
AI-generated alpine landscape: turquoise water, snow-covered peaks and soft sunrise light. A quiet first experiment with DreamShaper 8. The reflection and atmosphere came together well. Made locally in Stability Matrix / ComfyUI using DreamShaper_8_pruned.safetensors by Lykon (Stable Diffusion 1.5), 768 × 512, DPM++ 2M sampler, Karras schedule, 28 steps, CFG 6.5, seed 101501. Batch size 1 on an RTX 3050 6 GB. No upscaling or manual edits. Model: https://huggingface.co/Lykon/DreamShaper