Xythix retweeted
WTF… THIS 19-YEAR-OLD FOUND A WAY TO MAKE $10,000/MONTH USING CLAUDE + AIRBNB 🤯
While most students were looking for part-time jobs, this 19-year-old was building AI systems for Airbnb hosts.
Instead of answering the same guest questions all day, he created an AI assistant that handles everything automatically.
It replies to guests in seconds, sends check-in instructions, recommends local attractions, solves common issues, and even follows up after checkout.
He started by helping one Airbnb host for free.
That host referred him to three more.
Within months, he turned it into a small AI agency charging $1,000–2,000 per setup plus a monthly management fee.
Today, his agency generates over $10,000 every month, helping hosts save hours while giving guests a better experience.
The biggest AI opportunity isn’t building the next ChatGPT.
It’s solving boring business problems that owners happily pay to eliminate.
Would you trust an AI to manage your Airbnb guests?
Follow @Dexonfxf for more AI business ideas.
Xythix retweeted
32 jellies. 4 worlds. One crown. 🏆
I built Wobble Rush, a chaotic obstacle game you can play right in your browser.
Jump, dive, dodge… and try to survive.
Free to play. No download.
Can you take the crown? 👀
wooble-rush.kelioscott.com/
Made with @threejs
Xythix retweeted
Have you ever wondered how top awwwards website works?
With Refrontely , no more worries about that.
Understand and recreate every design, no exception.
Launching soon, pm me for early acces 🤝
Xythix retweeted
Let me know when Higgsfield can make product launches like these
Xythix retweeted
This 31-second SaaS motion took me 5 days.
Can ChatGPT create a video like this in 30 minutes?
Meet Receptly — an AI-powered appointment booking platform.
Xythix retweeted
This math app is making $50K/month, and its onboarding is pretty unique.
Onboarding
- Cute, memorable mascot
- Smooth animations + polished design
- Interactive quiz that figures out your math level
Paywall
- Appears halfway through the onboarding
- Technically a soft paywall, but intentionally hard to close
- 3 day free trial → then €27.46/month
What makes it stand out:
1. A memorable mascot that gives the app personality
2. An interactive onboarding that gets you using the product immediately
3. A polished experience from the very first screen
It doesn’t just tell you what the app can do.
It makes you experience it.
This fish identifier app is making $20k/month with only 10k downloads because it nailed its onboarding.
Onboarding
- Cool animations that instantly showcase the app’s value
- Collects key information about the user
- Uses that data to personalize the experience
- Asks for a review during onboarding
Paywall
- Only 2 options: monthly or annual
- No free trial
- If you close the paywall, you get an 80% limited time discount
This is how you onboard users:
1. Show them exactly what your app can do
2. Make the experience feel personal
3. Make the purchase decision as easy as possible
Xythix retweeted
this is the AI OFM business in one sentence:
one locked digital girl + one repeatable content pipeline.
Not random prompts.
I need:
> same face
> same body
> same fantasy
> same content style
> Instagram clips that get attention
> Fanvue page that converts
> chat that increases buyer value
The bikini clip is only the front end.
The money is the system behind it.
SHE PULLS IN $118,000 A MONTH FROM 11-SECOND LEOPARD BIKINI POOL CLIPS
Real influencers keep losing brand deals to her instead.
She’s built entirely out of synthetic rendering.
A 20-year-old student in Tampa runs the whole operation from his apartment, just custom models and one RTX card.
The hair moves and settles right because of a custom video diffusion layer, tracked frame by frame. Wet skin shine, leopard-print stretch in the water, pool reflections, and night lighting are locked so she blends into the resort instead of looking pasted on top of it.
An automated pipeline grabs trending audio, maps her exact poses and energy onto the character, and pushes fresh clips out across 38+ accounts on its own.
He doesn’t touch the edits.
No contracts. No travel days. No burnout.
44 million views a week.
Overhead: basically nothing.
One locked digital girl + one pipeline = money that never sleeps.
Xythix retweeted
There's SO much money on Reddit
Add "/.json" at the end of ANY Reddit link
> You get the entire thread as JSON
> All replies included
> Every comment, upvote, metadata
Now feed that into an LLM
If you're making a video about the latest Stranger Things episode for example...
> Go to the r/StrangerThings thread
> Add /.json to the URL
> Feed it to ChatGPT/Claude
> Extract top theories, reactions, what people are saying
> Use it as context for your script
Xythix retweeted
I might’ve found a way to make yesterday’s Blender to Real video ~5,000x faster (and better imo) lol.
I put the scene together with GPT-6 Astra and PATINA in about 30 minutes. But it had around 7 million polygons, so rendering took a while.
I split it into chunks across 8 GPUs and rendered it in about 30min. My estimate for an M4 Pro was around 40 hours. Obviously, I could’ve optimized the settings, but that’s for the version I posted yesterday.
Since then, I’ve been trying different prompts to get H3 Max to follow the Blender animation while making the buildings and materials actually look real. I think I finally got it.
The 30s video took about 30s to generate with H3 Max. Compared to that estimated 41h render, that’s roughly 5000x faster :)
The part I’m most excited about is how much control this gives me. GPT-6 Astra can build a detailed 3D prototype in minutes, and I can use Blender to set up the camera and movement however I want, then have H3 Max follow it.
Xythix retweeted
New video generation acceleration for MiniMax-H3 from the NVIDIA Sol team!
Faster than playback, fully open-sourced, and available via the Reactor API so you can try it before committing your GPU😜
🚀 Sol-H3: @MiniMax_AI H3 Video Generation Faster Than Playback 🤩
Five seconds of world. 1.653 seconds to infer.
We’re releasing Sol-H3, our fastest end-to-end MiniMax-H3 inference stack yet. On one 8× NVIDIA B300 Blackwell system, it generates five seconds of 1344×768 video with stereo audio in 1.653 seconds. Across 1×, 4×, and 8× B300, Sol-H3 reaches up to a 15.54× speedup versus Base H3.
Compared with 50-step Base H3 Dense on the same 8× B300 system, the four-step Sol-H3 profile delivers:
• 5s: 18.250s → 1.653s (11.04×)
• 10s: 50.660s → 3.732s (13.57×)
• 15s: 99.513s → 6.612s (15.05×)
Sol-H3 also scales across GPU counts:
• 4× B300: 2.918s / 6.993s / 12.542s for 5s / 10s / 15s (12.11–15.54×)
• 1× B300: 13.745s / 37.813s / 52.260s for 5s / 10s / 15s (9.45–14.29×)
All figures are medians of three measured runs after one warmup at 1344×768 and 24 FPS with stereo audio. Base H3 uses 50 scheduler points (49 DiT forwards); Sol-H3 uses four DiT forwards, so this is a full-profile comparison—not an attention-only runtime change. Sol-H3 uses Dense attention on 1× B300 and SOL with INT8 QKV / FP8 output transport on 4× / 8×. Timing includes text encoding, DiT denoising, and video/audio VAE decoding; model loading, compilation warmup, and final MP4 encoding are excluded.
Sol-H3 brings Sol-Engine × Sol-Attn into one full-stack runtime:
• dynamic sparse attention with no retraining
• fused norm, RoPE, MLP, and sparse-attention setup
• fused INT8 QKV / FP8 output communication across 8 GPUs
• parallel, batched VAE decoding
• precomputed AdaLN caching
Inside the stack:
• sparse-attention setup: 1.206 → 0.285 ms (−76.4%)
• VAE decode: 7.55 → 0.602 s
• ~24 GB memory freed per GPU
Any MiniMax-H3 few-step LoRA can plug into the same engine, and the code is deployment-friendly under Apache 2.0.
For us, the bigger milestone is crossing from “fast generation” into “faster than playback.” That opens the path toward continuous 24 FPS generation and truly interactive video systems.
We’re excited to partner with @reactorworld to release Sol-H3 and make it available as an API day-0.
Try it now on Reactor: reactor.inc/sandbox?model=fa…
🔗 nvlabs.github.io/Sana/Sol-En…
Amazing team effort—full credits in the blog.
@shanasaimoe @lawrence_cjs @yitongli165665 @haopengl33 @HaochengXiUCB @songhan_mit
Xythix retweeted
SIGAN A ESTA PERSONA NO DIGO NADA MÁS…
🚨Esto es MUY peligroso.
Acabo de ver a un chico de 18 años explicar tranquilamente cómo gana $10,000 al mes usando IA mientras duerme, y estoy convencido de que el 99% de la gente todavía no está viendo esto.
Todo el sistema:
Elige un canal de YouTube que publique contenido con frecuencia.
Pega el enlace en una herramienta.
Conecta tus cuentas de TikTok, Instagram y YouTube Shorts.
Cierra la laptop.
A partir de ahí, la IA lo hace todo.
Detecta cada video nuevo que se publica, encuentra y recorta los momentos con mayor potencial viral, añade subtítulos y los distribuye automáticamente en todas las plataformas.
1 millón de visualizaciones ≈ $2,000
Cero edición.
Cero publicaciones manuales.
Cero estrés.
10 minutos para configurarlo y después funciona en piloto automático.
Ya no estás creando contenido.
Estás construyendo una fábrica de contenido.
Guárdalo.
