A developer just killed the real estate walkthrough industry by scanned an entire house with his phone. Uploaded it.
Now anyone on Earth can walk through it in a browser tab. No app. No VR. No agent. No appointment.
Click → you’re inside. Every room. Every angle. Every shadow. Photoreal.
The economics are brutal for the old model:
→ Agent fee on a $500k home: $15,000
→ Cost to produce this scan: roughly $200
→ Time to "tour" 50 houses: one evening
→ File size: smaller than a TikTok clip
The science is wild too:
It runs on 3D Gaussian Splatting instead of polygons.
Millions of tiny glowing splats of color and depth reconstruct the scene from your photos, and it loads photoreal on a phone.
Freelancers are already charging $300 to $800 per scan for realtors, Airbnbs, venues, and dealerships.
One person + one phone + one weekend = a business.
Open source. Built on PlayCanvas.
Free GitHub: https://t.co/B4eW6rFRKc
Meet Janhavi Ajit Rao.After spending 18 years as a software engineer, she made a decision that very few people would dare to make.
At the age of 40, she quit her successful engineering career and joined MBBS to become a doctor.
She studied Electronics in California, worked at top technology companies in the US and India, and even founded her own technology company.
In 2003, she was diagnosed with rheumatoid arthritis, an autoimmune disease. During her treatment, she saw how doctors changed patients' lives.
That inspired her to leave engineering behind and dedicate her life to medicine.
So, in 2013, she joined M.S. Ramaiah Medical College, Bengaluru, as an MBBS student.
After 8 years of hard work, she earned her MBBS degree.
Today, at the age of 47, she pursuing her M.D , currently working as Primary care physician in United States
FYI check :-
https://t.co/KHEsWDujuG
Seedance 2.0 on OpenArt AI
Prompt:
Main subject: young Korean woman, early 20s, natural everyday appearance, faded charcoal-grey sleeveless crop top, loose high-waisted light-wash jeans, black canvas sneakers, black cord necklace, black wavy hair in a messy side ponytail with wispy bangs. Realistic skin texture, minimal makeup, warm and approachable personality. Maintain consistent identity, clothing, hairstyle, and appearance throughout the entire video.
Location: Authentic Korean residential neighborhood during a calm late morning. Narrow concrete alleys, low-rise homes, small terraces, potted plants, laundry lines, bicycles, utility poles, overhead wires, mature trees casting moving shadows, quiet residential atmosphere. No stores, advertisements, cafés, crowds, or commercial activity.
Visual Style: Ultra-realistic documentary realism. Genuine candid behavior. Natural body language. Unscripted slice-of-life feeling. Strong environmental authenticity. Rich real-world details and believable human motion.
Camera Style: Early-2000s consumer DV camcorder aesthetic. Friend casually recording everyday moments. Heavy handheld shake, imperfect framing, frequent autofocus hunting, lens breathing, exposure pumping when moving between sun and shade, occasional motion blur, subtle rolling shutter, mild digital compression artifacts, faded colors, soft contrast, slight sensor noise. No stabilization. No cinematic camera moves. No modern color grading.
00:00–00:02
Outside a small house entrance. She sits on a low concrete wall adjusting her ponytail with both hands raised. A light breeze moves loose strands of hair. She smiles naturally while the camera struggles to hold focus.
00:02–00:04
The camera follows her into a narrow alley lined with potted plants and concrete walls. She notices a stray cat approaching and crouches down. Framing drifts off-center as the operator tries to keep up.
00:04–00:06
She gently pets and feeds the cat. Autofocus repeatedly shifts between her face and the animal. Morning sunlight flickers through leaves overhead.
00:06–00:08
Small front yard beside her house. She hangs laundry on a clothesline while fabrics sway in the breeze. Exposure changes as clouds briefly pass overhead.
00:08–00:10
On a quiet terrace with a ceramic coffee cup. She sits comfortably watching the neighborhood, occasionally brushing hair behind her ear. Loose handheld side angle with natural camera drift.
00:10–00:12
Close side profile. Someone off-camera greets her. She turns, raises her hand, smiles warmly, and casually says, “Annyeong.” The camera catches the moment slightly late.
00:12–00:15
Walking slowly down a tree-lined residential lane holding her coffee cup. She notices the camera, gives a small genuine smile, then looks away and continues walking. Recording cuts abruptly to black mid-motion as if the camcorder was switched off.
Audio: Natural ambient sound only — morning birds, distant motorcycles, light wind, leaves rustling, faint neighborhood chatter, cat sounds, footsteps on concrete, fabric moving on clotheslines, subtle residential ambience. No music. No sound design. No narration.
Goal: Authentic Korean neighborhood life captured like a forgotten home video from the early 2000s — candid, imperfect, realistic, warm, and deeply believable.
Introducing Cursor for iOS.
Build from anywhere by launching always-on cloud agents. Or remotely control agents running on your computer from the app.
Composer 2.5 is 75% off in the app now through July 5.
An open-source robot vacuum you build yourself — Raspberry Pi, ROS 2, 2D LiDAR, Home Assistant, 3D printed chassis. No cloud, fully local.
oomwoo is early stage and building in public. The community can contribute modules in parallel — from SLAM navigation to dust bin design.
https://t.co/ip0HWptZg0
#ROS2 #RaspberryPi
NVIDIA just made AI detect objects 10x faster by deleting one step.
It's called LocateAnything, and it removes the biggest bottleneck no one else was fixing in vision-language models.
Normally a model builds each bounding box one coordinate token at a time. 100 objects means thousands of tokens before an answer. NVIDIA scrapped that: their Parallel Box Decoding predicts the whole box in a single forward pass, as one atomic unit.
→ 12.7 boxes/sec on one H100
→ 10x faster than Qwen3-VL
→ +3.8% F1 on LVIS, accuracy up, not down
→ 3B params, runs on one consumer GPU
Treating the box as one unit keeps its coordinates tied together, which is why accuracy climbed instead of falling.
One model handles detection, GUI grounding, OCR, and document understanding, ready for computer-use agents, robotics, and document pipelines.
100% open source, weights, code, demo, and paper all live.
AI can build an app in an afternoon. But getting it safely into other people's hands is a whole other challenge!
This is the problem that I've been working on these past few months. I'm proud to finally share how we solved it with Block App Kit!
https://t.co/hXm6NdcMUW
"Can @v0 use my design system?" you've asked.
Now the answer is: @v0 can use the exact same components your product uses in prod.
We put it to the test with @microsoft Fluent, @shopify Polaris, @ibm Carbon, @palantirtech Blueprint, @vercel Geist (ofc), and more. Watch ↓
99 percent of trading strategies fail because people overfit for the past instead of stress testing for the future.
i am dropping the raw code for a simple reversal setup that clocked 192,000 percent roi and i am showing you how to break it.
stop buying courses and start running these templates to see if your edge is real or just a math error.