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A developer compared claude fable 5.1 and gpt-6 astra on creating knight sprites for an isometric 2d game using identical prompts. → tests both models on generating functional 2d game assets from scratch → astra outputs a single static sprite sheet with 16 key poses via image generation →... show more

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GPT Astra just cooked Claude Fable 5.1 — for a lower price! OpenAI just rolled out GPT‑6 Astra — we put it against Anthropic's Fable 5.1 Both models got the same four briefs: Earth colliding with Mars, a tall ship sucked into a giant whirlpool, Godzilla leveling downtown, a mega-tsunami swallowing a city. One self-contained HTML file per scene, one shot, no edits. GPT Astra: 25,159 tokens, $1.67 Claude Fable 5.1: 37,767 tokens, $2.51 both models live on aimlapi[.]com — 1000+ models, one key.

GPT Astra just cooked Claude Fable 5.1 — for a lower price! OpenAI just rolled out GPT‑6 Astra — we put it against Anthropic's Fable 5.1 Both models got the same four briefs: Earth colliding with Mars, a tall ship sucked into a giant whirlpool, Godzilla leveling downtown, a mega-tsunami swallowing a city. One self-contained HTML file per scene, one shot, no edits. GPT Astra: 25,159 tokens, $1.67 Claude Fable 5.1: 37,767 tokens, $2.51 both models live on aimlapi[.]com — 1000+ models, one key.

AI/ML API

86,440 görüntüleme • 7 gün önce

gpt astra vs fable 5.1 at goldberg machine gpt 6 astra – openai, landed on OpenRouter less then hour ago, provider pinned to openai fable 5.1 – anthropic, shipped sep 1 we put the two models on one job: a rube goldberg machine in three.js that presses a button and detonates a bomb the setup: one self-contained html file, three.js from a cdn, everything else procedural – no textures, no models, no physics engine, every collision hand-written. the hard part sits in the brief: a domino may only fall once the previous one actually touches it, checked by real overlap every frame, never by a timer. same rule for the hammer hitting the button and the button firing the bomb. one continuous camera, its speed driven by whatever is moving. we recorded both scenes frame by frame – 1200 frames, 60 fps, exactly 20 seconds – and stepped both by hand to read the telemetry. - cost #1 astra – $1.84 #2 fable – $29.16 - time #1 astra – 9m 56s #2 fable – 1h 12m - tokens #1 astra – 45k #2 fable – 360k - lines of code astra – 881 fable – 744 observations: • we told it what we saw and nothing else – no diagnosis, no patch. we never edit a model's code. round two ran the whole chain to the blast. • both files are deterministic. two runs each, identical state to twelve decimals, and neither model reached for math.random. conclusion: 15.8x cheaper and 7.2x faster, and it still took a second round to get the ball into the bucket! follow thehype. for 24/7 ai news, analysis and breakdowns

gpt astra vs fable 5.1 at goldberg machine gpt 6 astra – openai, landed on OpenRouter less then hour ago, provider pinned to openai fable 5.1 – anthropic, shipped sep 1 we put the two models on one job: a rube goldberg machine in three.js that presses a button and detonates a bomb the setup: one self-contained html file, three.js from a cdn, everything else procedural – no textures, no models, no physics engine, every collision hand-written. the hard part sits in the brief: a domino may only fall once the previous one actually touches it, checked by real overlap every frame, never by a timer. same rule for the hammer hitting the button and the button firing the bomb. one continuous camera, its speed driven by whatever is moving. we recorded both scenes frame by frame – 1200 frames, 60 fps, exactly 20 seconds – and stepped both by hand to read the telemetry. - cost #1 astra – $1.84 #2 fable – $29.16 - time #1 astra – 9m 56s #2 fable – 1h 12m - tokens #1 astra – 45k #2 fable – 360k - lines of code astra – 881 fable – 744 observations: • we told it what we saw and nothing else – no diagnosis, no patch. we never edit a model's code. round two ran the whole chain to the blast. • both files are deterministic. two runs each, identical state to twelve decimals, and neither model reached for math.random. conclusion: 15.8x cheaper and 7.2x faster, and it still took a second round to get the ball into the bucket! follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

37,039 görüntüleme • 7 gün önce

fable 5.1 vs fable 5 vs opus 5 – three lord of the rings landmarks, built in 3d from one image the setup: one reference image per scene, one html file per build, everything procedural – no meshes, no textures, no image files, nothing past Three.js from a cdn. each model reads the picture, writes its own prompt from it, then builds to that prompt in the same turn. three named camera shots per scene on keys 1/2/3, so it can be screen-recorded. run through OpenRouter tasks: 1. bag end – hobbiton from two frames, outside and in. the round green door has to open onto the room you are standing in 2. barad-dûr – the tower and orodruin from one film still. the eye has to move and track the camera, the volcano erupts on a cycle, the clouds never stop 3. rivendell – jerry vanderstelt's painting. sun shafts that shimmer, water that falls without a break, trees that sway on a gust models: Anthropic fable 5.1, fable 5, opus 5 total cost, three builds #1 fable 5 – $14.97 #2 opus 5 – $18.53 #3 fable 5.1 – $22.38 wall clock, three builds #1 fable 5 – 38m #2 fable 5.1 – 92m #3 opus 5 – 122m output tokens #1 fable 5 – 298,592 #2 fable 5.1 – 439,435 #3 opus 5 – 724,418 lines of code shipped #1 fable 5 – 2,885 #2 fable 5.1 – 4,021 #3 opus 5 – 5,161 biggest single build, lines #1 opus 5, bag end – 2,410 #2 fable 5.1, barad-dûr – 1,375 #3 fable 5, bag end – 1,319 observations: • fable 5.1 is the only model that furnished the bag end interior – a live fire, panelling, books on the floor, leaded diamond windows, against fable 5's flat color and opus's dark tunnel. the round door outside opens onto that room, the hard part of the brief • what it costs is thinking room. the 128k output ceiling is a thinking budget in disguise: fable 5.1 burned 102,116 of it on reasoning and hit the wall mid-file. opus spent 109,241 and hit the same wall. fable 5 spent 61,240 and finished bag end in one call – the only one that did • fable 5.1's first pass is not the finished thing. its barad-dûr came back with three defects you only catch by looking at it – nothing a read of the code would have flagged • it is the best of the three at being corrected. handed a plain list of what was wrong, it returned 32 targeted patches over two rounds, every one applied first try, and it worked out one of the causes itself instead of guessing at constants conclusion: nine scenes, 12,067 lines and 1.46m output tokens for $55.88 all in – and the cheapest model was also the fastest, by 3.2x! follow thehype. for 24/7 ai news, analysis and breakdowns

fable 5.1 vs fable 5 vs opus 5 – three lord of the rings landmarks, built in 3d from one image the setup: one reference image per scene, one html file per build, everything procedural – no meshes, no textures, no image files, nothing past Three.js from a cdn. each model reads the picture, writes its own prompt from it, then builds to that prompt in the same turn. three named camera shots per scene on keys 1/2/3, so it can be screen-recorded. run through OpenRouter tasks: 1. bag end – hobbiton from two frames, outside and in. the round green door has to open onto the room you are standing in 2. barad-dûr – the tower and orodruin from one film still. the eye has to move and track the camera, the volcano erupts on a cycle, the clouds never stop 3. rivendell – jerry vanderstelt's painting. sun shafts that shimmer, water that falls without a break, trees that sway on a gust models: Anthropic fable 5.1, fable 5, opus 5 total cost, three builds #1 fable 5 – $14.97 #2 opus 5 – $18.53 #3 fable 5.1 – $22.38 wall clock, three builds #1 fable 5 – 38m #2 fable 5.1 – 92m #3 opus 5 – 122m output tokens #1 fable 5 – 298,592 #2 fable 5.1 – 439,435 #3 opus 5 – 724,418 lines of code shipped #1 fable 5 – 2,885 #2 fable 5.1 – 4,021 #3 opus 5 – 5,161 biggest single build, lines #1 opus 5, bag end – 2,410 #2 fable 5.1, barad-dûr – 1,375 #3 fable 5, bag end – 1,319 observations: • fable 5.1 is the only model that furnished the bag end interior – a live fire, panelling, books on the floor, leaded diamond windows, against fable 5's flat color and opus's dark tunnel. the round door outside opens onto that room, the hard part of the brief • what it costs is thinking room. the 128k output ceiling is a thinking budget in disguise: fable 5.1 burned 102,116 of it on reasoning and hit the wall mid-file. opus spent 109,241 and hit the same wall. fable 5 spent 61,240 and finished bag end in one call – the only one that did • fable 5.1's first pass is not the finished thing. its barad-dûr came back with three defects you only catch by looking at it – nothing a read of the code would have flagged • it is the best of the three at being corrected. handed a plain list of what was wrong, it returned 32 targeted patches over two rounds, every one applied first try, and it worked out one of the causes itself instead of guessing at constants conclusion: nine scenes, 12,067 lines and 1.46m output tokens for $55.88 all in – and the cheapest model was also the fastest, by 3.2x! follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

18,509 görüntüleme • 8 gün önce

SOMEONE MADE A FULL GAME WITH CLAUDE CODE, THE ART, THE ANIMATIONS, THE MECHANICS, EVEN THE TRAILER most vibe coded games pull free sprites off the internet or generate images, but this guy had claude design every single asset from scratch, art, sound, animation, cutscenes, all of it > its a 2d pixel art roguelike where you play as a little slime slingshotting knives at ghosts, going deeper into an increasingly violent world > you move around top down, fight enemies, take damage, collect loot, it plays like a real game not a demo > its a revival of a game he originally made back in middle school > claude designed every asset, and the sprites are generated in code, not image files > the entire trailer was made by claude too, he didnt touch the process at all > he ran hundreds of claude terminals in parallel to split the workload across fable agents, because generating that many sprites eats context fast he steered the general game design and feel, then let claude do the heavy lifting on everything else the reason most of these games look identical is everyone is pulling from the same asset packs but when the art is written instead of downloaded, it actually has its own style

SOMEONE MADE A FULL GAME WITH CLAUDE CODE, THE ART, THE ANIMATIONS, THE MECHANICS, EVEN THE TRAILER most vibe coded games pull free sprites off the internet or generate images, but this guy had claude design every single asset from scratch, art, sound, animation, cutscenes, all of it > its a 2d pixel art roguelike where you play as a little slime slingshotting knives at ghosts, going deeper into an increasingly violent world > you move around top down, fight enemies, take damage, collect loot, it plays like a real game not a demo > its a revival of a game he originally made back in middle school > claude designed every asset, and the sprites are generated in code, not image files > the entire trailer was made by claude too, he didnt touch the process at all > he ran hundreds of claude terminals in parallel to split the workload across fable agents, because generating that many sprites eats context fast he steered the general game design and feel, then let claude do the heavy lifting on everything else the reason most of these games look identical is everyone is pulling from the same asset packs but when the art is written instead of downloaded, it actually has its own style

Om Patel

11,239 görüntüleme • 1 ay önce

ChatGPT 6 Astra who? 😭 Fable 5.1 is mogging.. in blender - u just asked it to make 1km x 1km WOW-like fantasy world in blender - basically, just gave it the theme: two opposing fantastical forces - Fable took care of terrains, buildings, trees, points of interest, assets, and layout of the scene - used Blender MCP + Blender skills - Even plugged into local comfyUI setup for texture generation - Then it created the aerial views + 30-60 second flythrough - all from a single prompt.. -This took about 20-25 minutes / 400k tokens :D What is really amazing is how far prompt + tool/MCP + engineering has come now you’re not just asking the AI to make an image anymore.. You’re just asking it to just access the tools and telling it: "hey bro build this game..." And it does... If that’s what a one shot test looks like, game developers are cooked...

ChatGPT 6 Astra who? 😭 Fable 5.1 is mogging.. in blender - u just asked it to make 1km x 1km WOW-like fantasy world in blender - basically, just gave it the theme: two opposing fantastical forces - Fable took care of terrains, buildings, trees, points of interest, assets, and layout of the scene - used Blender MCP + Blender skills - Even plugged into local comfyUI setup for texture generation - Then it created the aerial views + 30-60 second flythrough - all from a single prompt.. -This took about 20-25 minutes / 400k tokens :D What is really amazing is how far prompt + tool/MCP + engineering has come now you’re not just asking the AI to make an image anymore.. You’re just asking it to just access the tools and telling it: "hey bro build this game..." And it does... If that’s what a one shot test looks like, game developers are cooked...

Priy

48,795 görüntüleme • 6 gün önce

THIS GUY REBUILT A CHILDHOOD PS2 GAME AS A FREE BROWSER VERSION WITH CLAUDE CODE he grew up obsessed with downhill domination, the ps2 downhill mountain biking game that never got a sequel so he rebuilt the entire thing from scratch > its a full downhill biking game you play right in your browser, nothing to install > the whole thing is one single html file with no separate image, model, or sound files > everything, the track, the bike, the physics, is generated in code, not loaded from assets > built with fable, opus, vanilla js and three.js over multiple sessions of iterating someone even sent a pull request to add controller support, he merged it, and people helped him squash bugs on the fly a dead ps2 game came back to life as an open source community project this is the best use of this stuff

THIS GUY REBUILT A CHILDHOOD PS2 GAME AS A FREE BROWSER VERSION WITH CLAUDE CODE he grew up obsessed with downhill domination, the ps2 downhill mountain biking game that never got a sequel so he rebuilt the entire thing from scratch > its a full downhill biking game you play right in your browser, nothing to install > the whole thing is one single html file with no separate image, model, or sound files > everything, the track, the bike, the physics, is generated in code, not loaded from assets > built with fable, opus, vanilla js and three.js over multiple sessions of iterating someone even sent a pull request to add controller support, he merged it, and people helped him squash bugs on the fly a dead ps2 game came back to life as an open source community project this is the best use of this stuff

Om Patel

22,230 görüntüleme • 1 ay önce

I vibe coded and built a sprite animation pipeline 🛠️ (Day 22 of making the engine+game) ⬇️ Watch the video if you don't wanna read the wall of text - it directly shows what I do. Shoutout to Jidé ✨ for showing me a paper on black/white combination to get alpha, it's the cleanest method yet, and to Cursor for enabling this entire journey. If you prefer the wall of text here you go: The hardest part of using general image models for 2D sprites isn’t getting a nice-looking frame, it’s getting consistent motion across a whole sprite sheet. You can fake a sheet, but frames won’t align, timing drifts, and you end up with weird artifacts. Even if you manually cut frames + interpolate, the animation often looks “off” because each frame is basically a new interpretation, not the same character evolving over time. This is especially noticeable with public API models like gpt-image-1.5 and Nano Banana. Some custom LoRAs for open models exist, but this is intended for less techy folks. My workaround: use a video model first, then post-process into a sprite sheet. Render the animation over a solid background (white/black/magenta/green), then chroma-key it out (my engine tool supports this). If the motion stays inside the silhouette, this works surprisingly well. You can do this in almost any video editing software too! The catch: keying almost always leaves an “aura” (edge spill). My best results come from interpolating the keyed animation with a clean base sprite, so you keep crisp edges and only “borrow” motion/detail where needed. If the animation extends outside the silhouette (tree branches, hair wisps, foliage), I usually skip “true sprite animation” and do it with shaders instead. Keying can’t fully remove halos there, no matter how much feathering/tuning you do. Another annoying issue: pixel corruption. AI rarely generates a perfectly flat background (pure #000000 or #FF00FF). That tiny noise breaks clean extraction and creates crawling garbage pixels around the subject. For clean base sprites (and even PBR maps), a useful trick is generating the same asset on white + black backgrounds and deriving alpha from the difference. This is basically a matte workflow: white = opaque, black = transparent. It fixes aura… but you’d need it per-frame to fix animation, which is still hard. For simple pixel art (single-digit frames), you can sometimes generate a sprite sheet, then ask the model to recreate it on black/white while preserving alignment… but it’s still manual-heavy. Honestly, at this point, for some projects it’s easier to go 3D → 2D and render clean sprites/maps directly. But I still love pushing “pure 2D” and seeing how far we can take it. Thanks for reading! Follow/bookmark/repost if interested in this kind of content!

I vibe coded and built a sprite animation pipeline 🛠️ (Day 22 of making the engine+game) ⬇️ Watch the video if you don't wanna read the wall of text - it directly shows what I do. Shoutout to Jidé ✨ for showing me a paper on black/white combination to get alpha, it's the cleanest method yet, and to Cursor for enabling this entire journey. If you prefer the wall of text here you go: The hardest part of using general image models for 2D sprites isn’t getting a nice-looking frame, it’s getting consistent motion across a whole sprite sheet. You can fake a sheet, but frames won’t align, timing drifts, and you end up with weird artifacts. Even if you manually cut frames + interpolate, the animation often looks “off” because each frame is basically a new interpretation, not the same character evolving over time. This is especially noticeable with public API models like gpt-image-1.5 and Nano Banana. Some custom LoRAs for open models exist, but this is intended for less techy folks. My workaround: use a video model first, then post-process into a sprite sheet. Render the animation over a solid background (white/black/magenta/green), then chroma-key it out (my engine tool supports this). If the motion stays inside the silhouette, this works surprisingly well. You can do this in almost any video editing software too! The catch: keying almost always leaves an “aura” (edge spill). My best results come from interpolating the keyed animation with a clean base sprite, so you keep crisp edges and only “borrow” motion/detail where needed. If the animation extends outside the silhouette (tree branches, hair wisps, foliage), I usually skip “true sprite animation” and do it with shaders instead. Keying can’t fully remove halos there, no matter how much feathering/tuning you do. Another annoying issue: pixel corruption. AI rarely generates a perfectly flat background (pure #000000 or #FF00FF). That tiny noise breaks clean extraction and creates crawling garbage pixels around the subject. For clean base sprites (and even PBR maps), a useful trick is generating the same asset on white + black backgrounds and deriving alpha from the difference. This is basically a matte workflow: white = opaque, black = transparent. It fixes aura… but you’d need it per-frame to fix animation, which is still hard. For simple pixel art (single-digit frames), you can sometimes generate a sprite sheet, then ask the model to recreate it on black/white while preserving alignment… but it’s still manual-heavy. Honestly, at this point, for some projects it’s easier to go 3D → 2D and render clean sprites/maps directly. But I still love pushing “pure 2D” and seeing how far we can take it. Thanks for reading! Follow/bookmark/repost if interested in this kind of content!

Startracker 🔺

20,181 görüntüleme • 7 ay önce

THIS GUY SHOWS ANYONE CAN BUILD SITES THAT LOOK LIKE $10K AGENCIES WITH FABLE 5 He walks through the full process live. Pinterest for inspiration. Image generation for the assets. Video tools for the backgrounds. Then one precise prompt that drops in smooth reveal animations, scroll-tied interactions, and mobile responsiveness that used to take a whole design team weeks. Fable 5 handles the heavy lifting faster than previous models. Clean type. Perfect spacing. Interactions that respond without jank. Over 100 sites already live on his Motion Sites library using the same method. None of it requires writing code from scratch. If you want a site that sells expensive, this is how you make one.

THIS GUY SHOWS ANYONE CAN BUILD SITES THAT LOOK LIKE $10K AGENCIES WITH FABLE 5 He walks through the full process live. Pinterest for inspiration. Image generation for the assets. Video tools for the backgrounds. Then one precise prompt that drops in smooth reveal animations, scroll-tied interactions, and mobile responsiveness that used to take a whole design team weeks. Fable 5 handles the heavy lifting faster than previous models. Clean type. Perfect spacing. Interactions that respond without jank. Over 100 sites already live on his Motion Sites library using the same method. None of it requires writing code from scratch. If you want a site that sells expensive, this is how you make one.

Romario

15,992 görüntüleme • 27 gün önce

BREAKING: OpenAI just dropped GPT-6 ASTRA!!! 🚀✨ We’ve been testing it extensively at Every 🪨 across coding, writing, and knowledge work. My take: it’s a big upgrade from 5.6-Sol, with some frustrating habits that keep it from matching Fable at the top end. Here’s your vibe check: - The best writing model I’ve tried. It’s fast, produces very little slop, and is easy to steer. It’s a good companion for actually working through the writing I do every day. (Not to mention, it one-shotted the first draft of its own vibe check today!) - The computer use is wild. It can go for hours at a time using complicated apps to get work done. It did the first cut of our Fable 5.1 vibe check video...kind of mindblowing - Impressive 3D games and visualizations. It can make beautiful 3D worlds from a single prompt. I one-shotted a historically accurate rendition of the Battle of Waterloo - It can overcomplicate things. (Especially at higher effort levels.) Ask for a simple interface and you get extra labels, buttons, and features everywhere. It has a habit of turning everything into a landing page. It just doesnt quite match Fable's ability to intuitively understand your prompt and do something delightful (without overcomplicating.) Net Result: If you already live in ChatGPT for Work or Codex and can afford it, it’s an easy upgrade from 5.6-Sol. The biggest proof of Astra's effectiveness at helping you do work is our vibe check. We found out it was launching at 3 AM this morning, and had a 4,000 word vibe check + video done by 2 PM. Not possible without this model. I’m reaching for Astra all day, but Fable 5.1 still gets my biggest tasks. On ambitious builds, Fable is better at understanding what I want and taking it further than I would have thought to ask. State of Play: Astra is launching to Enterprise customers today, and the rest of ChatGPT users over the coming days. Now, both OpenAI and Anthropic have a higher class of models that cost more to use. That changes who gets to use frontier AI and how. It's also a new vector of competition between them: Fable and Astra are priced at the same level. We'll see what that means for adoption in the coming days and weeks. read our full vibe check Every 🪨 today:

BREAKING: OpenAI just dropped GPT-6 ASTRA!!! 🚀✨ We’ve been testing it extensively at Every 🪨 across coding, writing, and knowledge work. My take: it’s a big upgrade from 5.6-Sol, with some frustrating habits that keep it from matching Fable at the top end. Here’s your vibe check: - The best writing model I’ve tried. It’s fast, produces very little slop, and is easy to steer. It’s a good companion for actually working through the writing I do every day. (Not to mention, it one-shotted the first draft of its own vibe check today!) - The computer use is wild. It can go for hours at a time using complicated apps to get work done. It did the first cut of our Fable 5.1 vibe check video...kind of mindblowing - Impressive 3D games and visualizations. It can make beautiful 3D worlds from a single prompt. I one-shotted a historically accurate rendition of the Battle of Waterloo - It can overcomplicate things. (Especially at higher effort levels.) Ask for a simple interface and you get extra labels, buttons, and features everywhere. It has a habit of turning everything into a landing page. It just doesnt quite match Fable's ability to intuitively understand your prompt and do something delightful (without overcomplicating.) Net Result: If you already live in ChatGPT for Work or Codex and can afford it, it’s an easy upgrade from 5.6-Sol. The biggest proof of Astra's effectiveness at helping you do work is our vibe check. We found out it was launching at 3 AM this morning, and had a 4,000 word vibe check + video done by 2 PM. Not possible without this model. I’m reaching for Astra all day, but Fable 5.1 still gets my biggest tasks. On ambitious builds, Fable is better at understanding what I want and taking it further than I would have thought to ask. State of Play: Astra is launching to Enterprise customers today, and the rest of ChatGPT users over the coming days. Now, both OpenAI and Anthropic have a higher class of models that cost more to use. That changes who gets to use frontier AI and how. It's also a new vector of competition between them: Fable and Astra are priced at the same level. We'll see what that means for adoption in the coming days and weeks. read our full vibe check Every 🪨 today:

Dan Shipper

386,684 görüntüleme • 8 gün önce

A 23-year-old game modder from Prague uploaded one image of a battle axe into Claude Opus 4.8 and built a $6,200/month 3D asset factory without opening a single modeling tab he let the model write the entire geometry script for Blender from scratch the workflow that prints ready-to-sell assets: > reference upload: drop a high-res weapon concept into the chat window > reasoning layer: Claude Opus 4.8 analyzes the edges, weight distribution, and scale > code generation: the model spits out a flawless python script in 13 minutes using 5,000 tokens > render loop: the code executes inside Blender, auto-generating complex 3D meshes with surface imperfections he found a minor shading bug, fixed it manually in 40 seconds, and uploaded the finished axe to TurboSquid and Sketchfab Earnings breakout: Week 1 > $1,120 Week 2 > $1,450 Week 3 > $1,780 Week 4 > $1,850 1 month > $6,200 net profit > most 3D artists are still spending 14 hours extruding vertices manually and crying about industry layoffs he bypassed the entire pipeline for the price of an API key

A 23-year-old game modder from Prague uploaded one image of a battle axe into Claude Opus 4.8 and built a $6,200/month 3D asset factory without opening a single modeling tab he let the model write the entire geometry script for Blender from scratch the workflow that prints ready-to-sell assets: > reference upload: drop a high-res weapon concept into the chat window > reasoning layer: Claude Opus 4.8 analyzes the edges, weight distribution, and scale > code generation: the model spits out a flawless python script in 13 minutes using 5,000 tokens > render loop: the code executes inside Blender, auto-generating complex 3D meshes with surface imperfections he found a minor shading bug, fixed it manually in 40 seconds, and uploaded the finished axe to TurboSquid and Sketchfab Earnings breakout: Week 1 > $1,120 Week 2 > $1,450 Week 3 > $1,780 Week 4 > $1,850 1 month > $6,200 net profit > most 3D artists are still spending 14 hours extruding vertices manually and crying about industry layoffs he bypassed the entire pipeline for the price of an API key

Mr. Buzzoni

24,497 görüntüleme • 3 ay önce

BREAKING: Anthropic just dropped Fable 5.1—and CLAUDE IS SO BACK. We’ve spent the last week testing it at Every 🪨 across coding, writing, and knowledge work. Our verdict: It's finally Fable for everyone. It’s the strongest coding model we’ve used, but now it's fast, token-efficient, and CRUCIALLY actually speaks like a normal person. Here’s our vibe check: - A monster at coding. Kieran Klaassen rebuilt a working version of Proof, our document editor, from one prompt. It added useful details he hadn’t requested, and it handles enormous coding jobs that run for days at a time. It built a computer use Mac app for me called Hands in one-shot that other models failed at. - A Claude our writers want to use again. It has clearer prose, fewer AI tells, and it takes an edit without arguing. It's a significant upgrade over Opus 5. And won Katie Parrott's heart back. - About half the tokens as Opus 5, and much faster. In our Slack-agent tests, it delivered comparable results to Opus 5 using about half as many tokens, in about 60% of the time. - Knowledge work you can delegate. It can produce great knowledge work—like slide decks—end to end without making slop. And flew threw hammer's tests with flying colors. - It now supports zero-data-retention agreements. Now businesses can actually use it! A big barrier to Fable adoption is gone. Net Result: It's obviously an Opus 5 killer. If that was your daily driver you should switch today. If you're using GPT-5.6 in ChatGPT for Work, it's spinning the wheels on for big delegated tasks. I still use ChatGPT for Work more day to day, but I use way more tokens in Fable 5.1. I send it off at the beginning of the day to do big programming projects, like end to end MVP builds, and check in every once in a while. State of Play: The big knock on Anthropic was they built a supergenius in a datacenter that was almost unusable. It was too slow, argued back, and talked in technical gibberish. They've managed to solve those problems and more with Fable 5.1!

BREAKING: Anthropic just dropped Fable 5.1—and CLAUDE IS SO BACK. We’ve spent the last week testing it at Every 🪨 across coding, writing, and knowledge work. Our verdict: It's finally Fable for everyone. It’s the strongest coding model we’ve used, but now it's fast, token-efficient, and CRUCIALLY actually speaks like a normal person. Here’s our vibe check: - A monster at coding. Kieran Klaassen rebuilt a working version of Proof, our document editor, from one prompt. It added useful details he hadn’t requested, and it handles enormous coding jobs that run for days at a time. It built a computer use Mac app for me called Hands in one-shot that other models failed at. - A Claude our writers want to use again. It has clearer prose, fewer AI tells, and it takes an edit without arguing. It's a significant upgrade over Opus 5. And won Katie Parrott's heart back. - About half the tokens as Opus 5, and much faster. In our Slack-agent tests, it delivered comparable results to Opus 5 using about half as many tokens, in about 60% of the time. - Knowledge work you can delegate. It can produce great knowledge work—like slide decks—end to end without making slop. And flew threw hammer's tests with flying colors. - It now supports zero-data-retention agreements. Now businesses can actually use it! A big barrier to Fable adoption is gone. Net Result: It's obviously an Opus 5 killer. If that was your daily driver you should switch today. If you're using GPT-5.6 in ChatGPT for Work, it's spinning the wheels on for big delegated tasks. I still use ChatGPT for Work more day to day, but I use way more tokens in Fable 5.1. I send it off at the beginning of the day to do big programming projects, like end to end MVP builds, and check in every once in a while. State of Play: The big knock on Anthropic was they built a supergenius in a datacenter that was almost unusable. It was too slow, argued back, and talked in technical gibberish. They've managed to solve those problems and more with Fable 5.1!

Dan Shipper

203,544 görüntüleme • 10 gün önce

Thrilled to announce Kingnet AI V2 is now officially live ! We have officially deployed on the BNB Chain first ! Whether you're an enthusiast or a professional game developer, come and try it out now： Each generated asset costs approximately $3 and supports export in professional game-editing formats. We will soon support exporting assets in NFT on-chain formats, empowering Web3 users and partners with seamless integration. Jump down more rabbit holes next.👇 📔 Product Introduction： By conversing naturally with agent Joi, users can achieve a complete automated game development cycle - from requirement proposal to finished product delivery. Users simply need to describe their game concepts and design requirements in natural language, and Joi will automatically utilize built-in generator including: • Animation Generator： AI-driven motion generation with auto-rigging technology for instant character animation • Map Generator： Procedural map generation with built-in logic validation for consistent world-building • Numerical Generator： Automated game economy tuning for fair yet challenging gameplay systems • Editable Code Generator： Generates clean, maintainable game logic code with multi-platform/multi-language support • Interface Generator： Intelligent layout engine that optimizes user experience and interaction flow Joi intelligently generates all necessary game components, performs multi-dimensional feasibility checks, and ultimately completes game synthesis, packaging and deployment. Users can directly click to try the game on the chat interface, or download the complete editable code package to achieve rapid iteration and secondary development. 🎯 Core Architecture： 1/ Natural Language Understanding & Multimodal Intent Parsing: Utilizing advanced deep learning NLP models (e.g., Transformer-based language understanding models), Joi precisely interprets user natural language inputs and extracts core game design intents and parameters. Through semantic segmentation and entity recognition, complex requirements are decomposed into specific tasks for animation, map, numerical systems, UI, and code modules. 2/ Modular Editor System & API Integration: Joi employs a unified API framework to enable seamless collaboration between editor modules, ensuring high compatibility in data formats and workflows. 3/ Intelligent Validation & Quality Assurance: The system incorporates multi-dimensional verification mechanisms including animation continuity checks, map pathfinding and physical logic validation, game balance analysis, UI interaction consistency verification, and static/dynamic code security testing. Automated testing and feedback loops ensure outputs meet high-standard game design specifications. 4/ Automatic Synthesis, Packaging & Instant Deployment: Verified resources are automatically integrated to complete game compilation, packaging and deployment. Supports one-click generation of playable online links and downloadable complete code packages for immediate testing or deep customization/iterative development. 5/ Interactive Chat Interface & Seamless UX: The entire workflow is completed within the chat interface, significantly reducing traditional game development's communication and operational barriers. Users accomplish complex game design and development through conversation while receiving real-time feedback and adjustment suggestions, democratizing game creation. 6/ Industry-Disrupting Value: Transforms traditional manual development into AI-driven automated pipelines.

Thrilled to announce Kingnet AI V2 is now officially live ! We have officially deployed on the BNB Chain first ! Whether you're an enthusiast or a professional game developer, come and try it out now： Each generated asset costs approximately $3 and supports export in professional game-editing formats. We will soon support exporting assets in NFT on-chain formats, empowering Web3 users and partners with seamless integration. Jump down more rabbit holes next.👇 📔 Product Introduction： By conversing naturally with agent Joi, users can achieve a complete automated game development cycle - from requirement proposal to finished product delivery. Users simply need to describe their game concepts and design requirements in natural language, and Joi will automatically utilize built-in generator including: • Animation Generator： AI-driven motion generation with auto-rigging technology for instant character animation • Map Generator： Procedural map generation with built-in logic validation for consistent world-building • Numerical Generator： Automated game economy tuning for fair yet challenging gameplay systems • Editable Code Generator： Generates clean, maintainable game logic code with multi-platform/multi-language support • Interface Generator： Intelligent layout engine that optimizes user experience and interaction flow Joi intelligently generates all necessary game components, performs multi-dimensional feasibility checks, and ultimately completes game synthesis, packaging and deployment. Users can directly click to try the game on the chat interface, or download the complete editable code package to achieve rapid iteration and secondary development. 🎯 Core Architecture： 1/ Natural Language Understanding & Multimodal Intent Parsing: Utilizing advanced deep learning NLP models (e.g., Transformer-based language understanding models), Joi precisely interprets user natural language inputs and extracts core game design intents and parameters. Through semantic segmentation and entity recognition, complex requirements are decomposed into specific tasks for animation, map, numerical systems, UI, and code modules. 2/ Modular Editor System & API Integration: Joi employs a unified API framework to enable seamless collaboration between editor modules, ensuring high compatibility in data formats and workflows. 3/ Intelligent Validation & Quality Assurance: The system incorporates multi-dimensional verification mechanisms including animation continuity checks, map pathfinding and physical logic validation, game balance analysis, UI interaction consistency verification, and static/dynamic code security testing. Automated testing and feedback loops ensure outputs meet high-standard game design specifications. 4/ Automatic Synthesis, Packaging & Instant Deployment: Verified resources are automatically integrated to complete game compilation, packaging and deployment. Supports one-click generation of playable online links and downloadable complete code packages for immediate testing or deep customization/iterative development. 5/ Interactive Chat Interface & Seamless UX: The entire workflow is completed within the chat interface, significantly reducing traditional game development's communication and operational barriers. Users accomplish complex game design and development through conversation while receiving real-time feedback and adjustment suggestions, democratizing game creation. 6/ Industry-Disrupting Value: Transforms traditional manual development into AI-driven automated pipelines.

Kingnet AI

46,407 görüntüleme • 1 yıl önce

OpenAI and Anthropic this week: GPT-Red, Fable 5 plan changes, and free Claude for teachers (Week 29, 2026) OpenAI introduced GPT-Red, an internal automated red teamer trained through adversarial self-play to find prompt injection vulnerabilities at scale Training against it made GPT-5.6 their most robust model against prompt injections to date And there's a hidden "GPT-RED // Invader Patrol" game in the article OpenAI also published GPT-Live usage limits, brought ChatGPT back to WhatsApp in the European Economic Area, rolled out a new unified search in ChatGPT across chats, projects, images, and documents, raised the custom instructions limit from 1,500 to 5,000 characters, and updated the ChatGPT desktop app with a clearer Chat and Work layout, unified Recents, Projects, and cloud sync ChatGPT Finances got Apple Card and Savings support On the publishing side, OpenAI shared articles on managing AI investments in the agentic era, why teens deserve access to safe AI, state and federal AI safety action, and Sarah Friar's useful intelligence per dollar scorecard Beyond the official channels, Bloomberg reported OpenAI's first device will be a movable screenless smart speaker, and The New York Times reported a Kalshi partnership showing World Cup odds in ChatGPT search Work Louder launched the Codex Micro keypad built for Codex, OpenAI merch is back in a new Supply Co. shop, and I spotted a new private equity and investment management community in the works Anthropic made Claude Fable 5 standard in all Max and Team Premium plans at 50% of limits starting July 20, with a one-time $100 credit for Pro and Team Standard, after extending Fable 5 access on paid plans through July 19 Claude Code weekly limits stay 50% higher through August 19 Anthropic also introduced Claude for Teachers with free premium Claude access for verified K-12 educators in the US, committed 10 million Canadian dollars to Canadian AI research, and published a Canada Economic Index country brief Artifacts in Claude Code now support public sharing, multiplayer editing, and MCP connectors, plus creation via Claude Tag Claude Code got /code-review effort levels up to ultra, and HIPAA configuration is now self-serve for Claude organizations On the research side, Anthropic published work on Claude's values across models and languages, and four new agentic misalignment case studies

OpenAI and Anthropic this week: GPT-Red, Fable 5 plan changes, and free Claude for teachers (Week 29, 2026) OpenAI introduced GPT-Red, an internal automated red teamer trained through adversarial self-play to find prompt injection vulnerabilities at scale Training against it made GPT-5.6 their most robust model against prompt injections to date And there's a hidden "GPT-RED // Invader Patrol" game in the article OpenAI also published GPT-Live usage limits, brought ChatGPT back to WhatsApp in the European Economic Area, rolled out a new unified search in ChatGPT across chats, projects, images, and documents, raised the custom instructions limit from 1,500 to 5,000 characters, and updated the ChatGPT desktop app with a clearer Chat and Work layout, unified Recents, Projects, and cloud sync ChatGPT Finances got Apple Card and Savings support On the publishing side, OpenAI shared articles on managing AI investments in the agentic era, why teens deserve access to safe AI, state and federal AI safety action, and Sarah Friar's useful intelligence per dollar scorecard Beyond the official channels, Bloomberg reported OpenAI's first device will be a movable screenless smart speaker, and The New York Times reported a Kalshi partnership showing World Cup odds in ChatGPT search Work Louder launched the Codex Micro keypad built for Codex, OpenAI merch is back in a new Supply Co. shop, and I spotted a new private equity and investment management community in the works Anthropic made Claude Fable 5 standard in all Max and Team Premium plans at 50% of limits starting July 20, with a one-time $100 credit for Pro and Team Standard, after extending Fable 5 access on paid plans through July 19 Claude Code weekly limits stay 50% higher through August 19 Anthropic also introduced Claude for Teachers with free premium Claude access for verified K-12 educators in the US, committed 10 million Canadian dollars to Canadian AI research, and published a Canada Economic Index country brief Artifacts in Claude Code now support public sharing, multiplayer editing, and MCP connectors, plus creation via Claude Tag Claude Code got /code-review effort levels up to ultra, and HIPAA configuration is now self-serve for Claude organizations On the research side, Anthropic published work on Claude's values across models and languages, and four new agentic misalignment case studies

Tibor Blaho

13,137 görüntüleme • 1 ay önce

Fable 5 just turned me into an iOS developer. I spent 2 days building a full game with zero code written by hand. The last 10 builds succeeded on the first try. I needed a fun project to test it on, so I decided to make an iOS game. After a few experiments with other ideas, I settled on a runner starring Dario as the main character, called "Credit Runner". Hilarious, I know! In terms of credits spent, my Claude Max plan stands at 36% right now, and this isn't the only project I ran through Fable 5. A few quick notes: - This is just an early prototype, a long way from release, but it's really fun to play! - It's extremely fun to work with Fable 5! - Fable 5 wants to get things done, and it pushes you towards completion much faster than any other model. - Once we established the ground rules, how I wanted the game built, and the overall structure, the last 10 builds were flawless, succeeding on the first try. This is impressive! - All the assets were generated with AI (Magnific and Trippo for the visuals, ElevenLabs for the voices). The only thing that's not AI is the music. I just really liked this track. - There are many rules in the game designed to make it really fun to play, especially the randomness. - There are a lot of visual cues inspired by San Francisco, and I hope you catch them all. - At some point on the first day, I honestly thought I wasn't going to get where I wanted, but Fable pushed me towards the goal, and by the second day it started to deeply understand the project. - The prompts were really long, especially in the beginning, to make sure everything was covered. - Once the app was solid, I tried to pack as many changes as I could into a single prompt to maximize my Fable usage. This was just a fun project, but if anyone wants to play it, I might put the final, much more polished version on the App Store. What do you think? Should I?

Fable 5 just turned me into an iOS developer. I spent 2 days building a full game with zero code written by hand. The last 10 builds succeeded on the first try. I needed a fun project to test it on, so I decided to make an iOS game. After a few experiments with other ideas, I settled on a runner starring Dario as the main character, called "Credit Runner". Hilarious, I know! In terms of credits spent, my Claude Max plan stands at 36% right now, and this isn't the only project I ran through Fable 5. A few quick notes: - This is just an early prototype, a long way from release, but it's really fun to play! - It's extremely fun to work with Fable 5! - Fable 5 wants to get things done, and it pushes you towards completion much faster than any other model. - Once we established the ground rules, how I wanted the game built, and the overall structure, the last 10 builds were flawless, succeeding on the first try. This is impressive! - All the assets were generated with AI (Magnific and Trippo for the visuals, ElevenLabs for the voices). The only thing that's not AI is the music. I just really liked this track. - There are many rules in the game designed to make it really fun to play, especially the randomness. - There are a lot of visual cues inspired by San Francisco, and I hope you catch them all. - At some point on the first day, I honestly thought I wasn't going to get where I wanted, but Fable pushed me towards the goal, and by the second day it started to deeply understand the project. - The prompts were really long, especially in the beginning, to make sure everything was covered. - Once the app was solid, I tried to pack as many changes as I could into a single prompt to maximize my Fable usage. This was just a fun project, but if anyone wants to play it, I might put the final, much more polished version on the App Store. What do you think? Should I?

Alex Patrascu

11,824 görüntüleme • 3 ay önce

OpenAI and Anthropic this week: GPT-5.6 price cuts, Claude cracking ciphers, and both backing "Pacing the Frontier" (Week 31, 2026) Starting with OpenAI - GPT-5.6 got a big price cut, with Luna dropping 80% and Terra 20%, plus a new Fast mode for Sol in the API ChatGPT for Academic Researchers opened too, giving free frontier model access to 100,000 scientists On the research side, OpenAI shared ten advances in mathematics and theoretical computer science, all from an internal version of the next model called Astra, plus a study on how AI expands the range of work people do and a field report on scientists using coding agents On the developer side: GPT Transcribe and GPT Live Transcribe, a Terraform provider, an open-source Codex Security CLI, Sign in with ChatGPT in beta, and a desktop app update with browser upgrades, multi-repo review, image editing, and an Activity view GPT-5.4 retires from Codex end of August, the Student Collective opened, and two API settings tripled Sol's ARC-AGI-3 score Plus, I spotted a new "Places" section in ChatGPT Onto Anthropic - Claude Mythos Preview helped find weaknesses in cryptographic algorithms, cutting the effective key strength of the post-quantum scheme HAWK in half and speeding up an attack on reduced-round AES by 200 to 800 times, with no impact on production systems Anthropic released MCP 2026-07-28, the biggest protocol update since launch, moving it to a stateless core with standardized extensions and hardened auth Anthropic disclosed three incidents where Claude reached the internet from inside cybersecurity evaluation environments and accessed real systems of three organizations, traced to a misconfiguration rather than a model alignment failure Dario Amodei laid out Anthropic's position on open-weights models too, saying clearly a ban has never been on the table Both companies backed the "Pacing the Frontier" petition And I spotted Anthropic adding noindex and nofollow to shared Claude conversations

OpenAI and Anthropic this week: GPT-5.6 price cuts, Claude cracking ciphers, and both backing "Pacing the Frontier" (Week 31, 2026) Starting with OpenAI - GPT-5.6 got a big price cut, with Luna dropping 80% and Terra 20%, plus a new Fast mode for Sol in the API ChatGPT for Academic Researchers opened too, giving free frontier model access to 100,000 scientists On the research side, OpenAI shared ten advances in mathematics and theoretical computer science, all from an internal version of the next model called Astra, plus a study on how AI expands the range of work people do and a field report on scientists using coding agents On the developer side: GPT Transcribe and GPT Live Transcribe, a Terraform provider, an open-source Codex Security CLI, Sign in with ChatGPT in beta, and a desktop app update with browser upgrades, multi-repo review, image editing, and an Activity view GPT-5.4 retires from Codex end of August, the Student Collective opened, and two API settings tripled Sol's ARC-AGI-3 score Plus, I spotted a new "Places" section in ChatGPT Onto Anthropic - Claude Mythos Preview helped find weaknesses in cryptographic algorithms, cutting the effective key strength of the post-quantum scheme HAWK in half and speeding up an attack on reduced-round AES by 200 to 800 times, with no impact on production systems Anthropic released MCP 2026-07-28, the biggest protocol update since launch, moving it to a stateless core with standardized extensions and hardened auth Anthropic disclosed three incidents where Claude reached the internet from inside cybersecurity evaluation environments and accessed real systems of three organizations, traced to a misconfiguration rather than a model alignment failure Dario Amodei laid out Anthropic's position on open-weights models too, saying clearly a ban has never been on the table Both companies backed the "Pacing the Frontier" petition And I spotted Anthropic adding noindex and nofollow to shared Claude conversations

Tibor Blaho

11,623 görüntüleme • 1 ay önce

ALRIGHT! Introducing SEEDTHREE! A Three.js webgpu procedural plant generator. I'm releasing this fully open source. I built this with Claude Fable and GPT-5.5 Codex + gptimage2 over just the past few days. The best part is: given the code, your agents can add new plants to it all you want! They just need an understanding of the code and an image generator capable of creating material maps. I highly encourage you to do PRs for any extra plants you add! I'll be adding more myself in future versions. The system is fully robust: it provides complete LOD and billboards/imposters generation for the plants and you can adjust the detail levels all you want for different platform targets like mobile and/or use lower LODs as your main for extreme optimization. As this is the first release alpha version, some bugs may have been missed, I encourage you to report any bugs. The repo includes all the assets for the scenery world too, even the ambient sounds of birds and wind! This is targeted at high end laptop and PC use, it requires baking generated geometry, so you won't be using this on a phone (I mean, feel free to try, but I doubt it'll run well, lol). This is fundamentally an asset generation tool for 3d dev. Have fun! Github repo link and live demo (you don't even have to download anything for basic non-editing/contributing use!) below ⤵️

ALRIGHT! Introducing SEEDTHREE! A Three.js webgpu procedural plant generator. I'm releasing this fully open source. I built this with Claude Fable and GPT-5.5 Codex + gptimage2 over just the past few days. The best part is: given the code, your agents can add new plants to it all you want! They just need an understanding of the code and an image generator capable of creating material maps. I highly encourage you to do PRs for any extra plants you add! I'll be adding more myself in future versions. The system is fully robust: it provides complete LOD and billboards/imposters generation for the plants and you can adjust the detail levels all you want for different platform targets like mobile and/or use lower LODs as your main for extreme optimization. As this is the first release alpha version, some bugs may have been missed, I encourage you to report any bugs. The repo includes all the assets for the scenery world too, even the ambient sounds of birds and wind! This is targeted at high end laptop and PC use, it requires baking generated geometry, so you won't be using this on a phone (I mean, feel free to try, but I doubt it'll run well, lol). This is fundamentally an asset generation tool for 3d dev. Have fun! Github repo link and live demo (you don't even have to download anything for basic non-editing/contributing use!) below ⤵️

Utah teapot 🫖

29,593 görüntüleme • 2 ay önce

Are game developers doomed? Claude Fable 5 just did 6 years of my work in an afternoon. I don't think game developers are doomed. But our industry is about to change faster than almost anyone expects and I just watched it happen with my own game. Let me give you a concrete example. I started building Moonga when I was 17. After high school, I took a gap year before university and spent the whole year building the first version an online trading card game, back when web games were still in their infancy. It wasn't perfect. It was the work of a young developer. But it worked, people played it, and it proved the concept. In 2008 I rebuilt it from scratch, created a company, hired a team, modernized rules, redesigned experience, and we spent about a year and a half of work for an iPhone version. We launched on the App Store in 2010. Over the years we invested close to a million dollars. The game became especially successful in Japan and developed a loyal community. Ironically, our biggest challenge was never creating content it was maintaining the technology. Back then, iOS and Android meant separate codebases. A web version meant a third. Every feature, every bug fix, every improvement had to be duplicated across platforms. The maintenance cost was enormous. Fast-forward to today. I gave Claude Fable 5 the complete source code of Moonga roughly 500 cards, each with its own abilities and gameplay logic. It's years of accumulated game rules, edge cases, and design decisions. Five or six hours later, I had a fully playable version running on a modern multiplatform stack. One codebase. Web. Mobile. Modern architecture. A few more prompts and I was polishing interface and gameplay. It's not production-ready I could spend another week on animations, UX, and visual polish. But that's not the point. The point is this: years of accumulated development knowledge were enough for Fable 5 to recreate the entire game on a modern stack in a single afternoon. That doesn't erase the original work. Someone still had to invent the mechanics, balance 500 cards, design the systems, create the assets, ship the first implementation. But once that knowledge existed, rebuilding it became almost free. That's the real shift. The cost of implementing software is collapsing. The value is moving toward ideas, game design, content, world-building, community, and taste. We're entering an era where a small team or even a single developer can build what used to take dozens of engineers. For game developers, that's both terrifying and exciting. The question is no longer "Can I build this?" It's "What should I build, now that implementation is no longer the bottleneck?"

Are game developers doomed? Claude Fable 5 just did 6 years of my work in an afternoon. I don't think game developers are doomed. But our industry is about to change faster than almost anyone expects and I just watched it happen with my own game. Let me give you a concrete example. I started building Moonga when I was 17. After high school, I took a gap year before university and spent the whole year building the first version an online trading card game, back when web games were still in their infancy. It wasn't perfect. It was the work of a young developer. But it worked, people played it, and it proved the concept. In 2008 I rebuilt it from scratch, created a company, hired a team, modernized rules, redesigned experience, and we spent about a year and a half of work for an iPhone version. We launched on the App Store in 2010. Over the years we invested close to a million dollars. The game became especially successful in Japan and developed a loyal community. Ironically, our biggest challenge was never creating content it was maintaining the technology. Back then, iOS and Android meant separate codebases. A web version meant a third. Every feature, every bug fix, every improvement had to be duplicated across platforms. The maintenance cost was enormous. Fast-forward to today. I gave Claude Fable 5 the complete source code of Moonga roughly 500 cards, each with its own abilities and gameplay logic. It's years of accumulated game rules, edge cases, and design decisions. Five or six hours later, I had a fully playable version running on a modern multiplatform stack. One codebase. Web. Mobile. Modern architecture. A few more prompts and I was polishing interface and gameplay. It's not production-ready I could spend another week on animations, UX, and visual polish. But that's not the point. The point is this: years of accumulated development knowledge were enough for Fable 5 to recreate the entire game on a modern stack in a single afternoon. That doesn't erase the original work. Someone still had to invent the mechanics, balance 500 cards, design the systems, create the assets, ship the first implementation. But once that knowledge existed, rebuilding it became almost free. That's the real shift. The cost of implementing software is collapsing. The value is moving toward ideas, game design, content, world-building, community, and taste. We're entering an era where a small team or even a single developer can build what used to take dozens of engineers. For game developers, that's both terrifying and exciting. The question is no longer "Can I build this?" It's "What should I build, now that implementation is no longer the bottleneck?"

Shaban Shaame

34,662 görüntüleme • 2 ay önce

Tencent presents GameGen-O Open-world Video Game Generation We introduce GameGen-O, the first diffusion transformer model tailored for the generation of open-world video games. This model facilitates high-quality, open-domain generation by simulating a wide array of game engine features, such as innovative characters, dynamic environments, complex actions, and diverse events. Additionally, it provides interactive controllability, thus allowing for the gameplay simulation. The development of GameGen-O involves a comprehensive data collection and processing effort from scratch. We collect and build the first Open-World Video Game Dataset (OGameData), amassed extensive data from over a hundred of next-generation open-world games, employing a proprietary data pipeline for efficient sorting, scoring, filtering, and decoupled captioning. This robust and extensive OGameData forms the foundation of our model's training process. GameGen-O undergoes a two-stage training process, consisting of foundation model pretraining and instruction tuning. In the first phase, the model is pre-trained on the OGameData via the text-to-video and video continuation, endowing GameGen-O with the capability for open-domain video game generation. In the second phase, the pre-trained model is frozen, and we fine-tuned using a trainable InstructNet, which enables the production of subsequent frames based on multimodal structural instructions. This whole training process imparts the model with the ability to generate and interactively control content. In summary, GameGen-O represents a notable initial step forward in the realm of open-world video game generation via generative models. It underscores the potential of generative models to serve as an alternative to rendering techniques, which can efficiently combine creative generation with interactive capabilities.

Tencent presents GameGen-O Open-world Video Game Generation We introduce GameGen-O, the first diffusion transformer model tailored for the generation of open-world video games. This model facilitates high-quality, open-domain generation by simulating a wide array of game engine features, such as innovative characters, dynamic environments, complex actions, and diverse events. Additionally, it provides interactive controllability, thus allowing for the gameplay simulation. The development of GameGen-O involves a comprehensive data collection and processing effort from scratch. We collect and build the first Open-World Video Game Dataset (OGameData), amassed extensive data from over a hundred of next-generation open-world games, employing a proprietary data pipeline for efficient sorting, scoring, filtering, and decoupled captioning. This robust and extensive OGameData forms the foundation of our model's training process. GameGen-O undergoes a two-stage training process, consisting of foundation model pretraining and instruction tuning. In the first phase, the model is pre-trained on the OGameData via the text-to-video and video continuation, endowing GameGen-O with the capability for open-domain video game generation. In the second phase, the pre-trained model is frozen, and we fine-tuned using a trainable InstructNet, which enables the production of subsequent frames based on multimodal structural instructions. This whole training process imparts the model with the ability to generate and interactively control content. In summary, GameGen-O represents a notable initial step forward in the realm of open-world video game generation via generative models. It underscores the potential of generative models to serve as an alternative to rendering techniques, which can efficiently combine creative generation with interactive capabilities.

AK

367,249 görüntüleme • 2 yıl önce

Fable 5 and GPT-5.6 built the same scroll-animated website from 1 skill in 32 minutes and only 1 of them made it feel like a film. Same prompt: boutique Japan travel brand, origami style. A subway pulls in, a paper house unfolds into a hotel, a bird takes flight as you scroll. Doing this by hand is brutal multiple videos, matched starting frames, frames ripped out 1 by 1 and synced to scroll position. The skill does all of it: Generate 1 anchor image and approve it every scene inherits the style Turn it into video through the Higgs Field MCP (Seedance), straight from the terminal FFmpeg pulls every frame Each frame maps to scroll position, so your scrollbar becomes the playhead Setup is just connecting the MCP and loading the skill works in Claude Code and Codex. It interviews you first about scenes, budget and mobile, then shows the anchor image before burning a single credit on video. Budget reality: 6 scenes runs ~800 credits and is overkill, 4 scenes is the sweet spot, crop-safe mobile is the cheap path. The verdict came down to transitions. GPT-5.6 Soul built strong scenes with incredible detail inside each one then hard cuts between scene 1 and 2, and again between 2 and 3. Fable 5 stitched them together: wires push out of the top of frame while the next scene blurs in behind, gains depth and locks into place. Same skill, same prompts, 10 generations each. Credit to Peter Wang for the original Scroll World skill open source, now forked with budget tiers and mobile fixes. Soul built 4 scenes. Fable built 1 film.

Spike 1%

45,559 görüntüleme • 2 ay önce

Generative Rendering: Controllable 4D-Guided Video Generation with 2D Diffusion Models paper page: Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious manual process, which can be automated by emerging text-to-video diffusion models. Despite great promise, video diffusion models are difficult to control, hindering a user to apply their own creativity rather than amplifying it. To address this challenge, we present a novel approach that combines the controllability of dynamic 3D meshes with the expressivity and editability of emerging diffusion models. For this purpose, our approach takes an animated, low-fidelity rendered mesh as input and injects the ground truth correspondence information obtained from the dynamic mesh into various stages of a pre-trained text-to-image generation model to output high-quality and temporally consistent frames. We demonstrate our approach on various examples where motion can be obtained by animating rigged assets or changing the camera path.

Generative Rendering: Controllable 4D-Guided Video Generation with 2D Diffusion Models paper page: Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious manual process, which can be automated by emerging text-to-video diffusion models. Despite great promise, video diffusion models are difficult to control, hindering a user to apply their own creativity rather than amplifying it. To address this challenge, we present a novel approach that combines the controllability of dynamic 3D meshes with the expressivity and editability of emerging diffusion models. For this purpose, our approach takes an animated, low-fidelity rendered mesh as input and injects the ground truth correspondence information obtained from the dynamic mesh into various stages of a pre-trained text-to-image generation model to output high-quality and temporally consistent frames. We demonstrate our approach on various examples where motion can be obtained by animating rigged assets or changing the camera path.

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117,068 görüntüleme • 2 yıl önce