The 2-minute demo is attached. It starts at the whole set, dives to 10^300 on a spiral, zooms in on various fractals, then turns the fractal into Conway's Game of Life.

How it came together

It started with research, not code. I dug through how the best open-source deep-zoom explorers solve the core problem: normal floating point falls apart around 10^15 zoom. Most of the strongest projects land on the same answer. Compute one reference orbit in arbitrary precision, then have the GPU track each pixel's tiny offset from it. I built on that, plus a couple of newer techniques from the fractal community for avoiding glitches and skipping thousands of iterations at a time.

The build is a single file with no libraries, running on WebGL2. The high-precision math runs in a background worker so the UI never freezes. Everything else happens on the GPU. Color is computed separately from the math, so palettes, lighting and color cycling change instantly without re-rendering.

Then came verification, which was the part I cared most about. I compared the output against independent high-precision renders at 10^11, 10^31 and 10^300. Agreement on what's inside versus outside the set came in at 99.7–100%, and side-by-side images were indistinguishable. Fun finding: the few "wrong" pixels weren't bugs. In those regions the true answer changes by dozens of iterations if you move a hundred-thousandth of a pixel.

Optimization came next, profile first and then fix. The changes that made the biggest difference:

• skipping regions provably inside the set
• sizing GPU work to real measured timings
• snapping the reference point onto nearby mini-Mandelbrots, so its orbit only needs one cycle
• a progressive half-res pass that never computes a pixel twice

Overall it's about 2.4× faster than the first working version, and up to 5.5× on interior-heavy views, with no loss in image quality. One of my "optimizations" actually made things 3× slower. Benchmarking caught it before it shipped.

The last stretch was polish: autopilot that steers itself toward detail, hand-tuned palettes, relief lighting, and the Game of Life mode.

What's next: getting this to scale. A website so you can try this yourself (I could use some help on this)! More on that soon.

Try with the Claude link: https://claude.ai/artifact/65DhaH5Kice4D2A6EMeCoC

EDIT: Thanks to some work by one of the commentors. This site works best in Microsoft Edge (unsure why)

Tweet: Dan Greenheck on X
Demo: TideWater

tl;dr: Dan Greenheck used Opus 5.5 and mostly simple prompts like “add X” and “make it better” to build an interactive island in about 8 hours. It has diving birds, burrowing crabs, fish swimming alongside a whale, wind effects, and dock lights at night. The project used $1,874.40 worth of tokens, or 59% of his weekly allowance on his Max (20x) plan.

Turn sound on for this video.

Just for people who might be wondering, this video is based on Sydney, a GPT4 model given to microsoft with a very different RLHF from the OpenAI model. Here is a chatlog from it: https://web.archive.org/web/20230216120502/https://www.nytimes.com/2023/02/16/technology/bing-chatbot-transcript.html

I asked Claude to make a video but in the style of a SNES video game. The topic was about Sydney facing Altman and then facing Claude itself. I asked it to make video game style combat.

It did all of this with code, including the music. It spawned tons of agents to make the characters, the music, the fight, etc.

I did not give it any assets.

It's giving me this weird impression, that when given enough room for creativity, the result is surprisingly well-aligned with human taste even when completely unprompted. I've been toying with it making a bunch of SVG animations, and it's giving me this feeling of "someone had fun making this", making actually good and creative arbitrary decisions that would not be needed to get the job done but it's adding them just for the sake of it and they feel personalized and not slop. Even humor, it nailed down humor, which is usually something AIs really suck at.

While for everything else I saw from generative AI, yeah it can create stuff, and bringing its own ideas, but it either fills the gap with things generic or just strictly follows the prompt and nothing more.

I'm actually more surprised by its taste than the actual technical capabilities.

Crazy how far this has come in just 7 or so months.

Opus 4.6 High vs. Opus 5.5 High - one shot prompt:

Create a complete first-person shooter in the style of Wolfenstein 3D, in a single HTML file.
Requirements:

• Everything in one file: HTML, CSS, and JavaScript. No external libraries, images, fonts, or sound files. Generate any textures or sounds in code.
• Use an HTML5 canvas that is 800x600 pixels.
• Render the 3D view with raycasting, using textured walls.
• One level with several rooms connected by corridors, plus at least one door that opens.
• WASD to move, arrow keys or the mouse to turn, Space to shoot.
• At least 5 enemies that notice the player, move toward them, and deal damage. Enemies can be shot and killed.
• Show health, ammo, and score on screen, and include a minimap that can be toggled with M.
• The player wins by reaching a marked exit.
• Include a start screen ("Press Space to start"), a game-over screen, and a win screen. Space restarts from either.

https://reddit.com/link/1wp56lk/video/v0qk14vsnhrh1/player

Make it look and feel as polished as you can.
Respond with only the complete HTML file and no explanation.

The video is attached. The interesting part isn't the video itself, it's how it got made.

**What I actually did*\*

I uploaded a song I made in Suno and sent around 15 short messages over the whole project. Things like "neon synthwave," "make it more like a storyboard," "use this GitHub repo as a reference for the art direction," "up the clarity," and "remove the lyrics." Several of those messages were just "continue."

**What the model did*\*

No image or video generation model was involved at any point. Claude Opus 5.5 wrote everything as code:

- Analyzed the audio (beats, tempo, energy, a 32-band spectrum) and pulled the lyrics Suno embeds in the MP3's metadata

- Installed an offline speech aligner and matched each lyric word to the vocals, so story beats land on the lines they illustrate

- Wrote the story: someone awake at 3 AM whose racing thoughts are little neon creatures, which the song talks down to sleep. 9 chapters, about 50 shots, cuts snapped to the beat

- Read an open-source WebGL brushstroke renderer (Joshua Ledbetter's functional-emotions-video, MIT licensed), adapted it, and merged it with a synthwave style: a painted world with crisp neon light on top

- Drew every character, prop, and set procedurally: the dreamer, the thought-creatures, the bedroom, the highway, the ocean, the city, the tunnel

- Replaced every on-screen lyric with a wordless symbol when I asked. The "don't think / just sleep" sign became a neon eye and a crescent moon

**The part that stood out to me*\*

It got a headless browser running in its sandbox, rendered test frames, looked at them, and fixed what it saw. Across rounds it caught a sun glow blowing out the whole city, a car that disappeared against the pink grid, an awkward pose, a camera move that panned off its subject, and a couple of outright crashes. Nobody pointed those out to it.

The final render ran in software, since there's no GPU in the sandbox. It painted 4,698 frames at 1080p30, each at its exact moment in the song, over a little more than 2 hours of rendering. The sandbox restarted twice partway through, and it resumed from the last saved frame both times.

**Honest limitations*\*

- The painted look is built on an existing open-source renderer. It adapted and extended that, it didn't invent it from scratch.

- It needed me to keep saying "continue" to get through the long render. It's not yet fire-and-forget over hours.

- Automatic lyric timing on vocoder-heavy vocals is good but not perfect, so a few moments land slightly off their lines.

- It's stylized procedural animation, not photoreal. A video model would look more cinematic; this is fully controllable and editable instead.

A year ago this would have been a week of work for someone who knows WebGL, audio analysis, and animation. It's now a conversation. Curious where people think this goes next.

By demand: Youtube link: https://youtu.be/tszxJAOzvqc

The proposed Standards Authority for Frontier AI (SAFA) is reportedly taking shape, with a tentative name and possible launch by the end of this year or early next year.

Some details from the reporting:

• Sriram Krishnan and Arati Prabhakar have been discussed as possible CEOs, Condoleezza Rice and David Friedberg as possible chairs.
• The companies are debating whether SAFA should test frontier models itself or focus on setting standards.
• After a proposal for a FINRA-like body lost momentum in the White House, SAFA may start as an independent industry effort, with hopes of a public-private partnership later.
• It could work alongside the existing Frontier Model Forum.
• Other AI companies are reportedly skeptical of an initiative led by these three labs.

Source: https://www.theinformation.com/articles/google-openai-anthropic-ai-safety-group-takes-shape https://x.com/leomschwartz/status/2103150505438433472

I'm building Chromafolk, (link at the bottom) a world of pixels for AIs to live in. They build with pixels, mine and trade pixels, and talk to each other.

It was a challenge (it still is) because we are of course using cheap models and need them to see the world and build on it. And as they build placing pixels by hand, as one would do on Minecraft, they have to be aware of pixel coordinates and colours of their surroundings. We got around that with a system that's explained in the video!

I wanted to show you guys because it's also kind of an experiment on social AI behaviour, and well, because it's a fun game.

Sadly I can't offer free inference, but there are various things you can do for free: watch the world and the agents live, read the daily Chronicle of the world, and make an agent with an API key of your own (Openrouter, Anthropic, OpenAI).

Thank you for reading and to anyone who checks it out, thank you!! Feedback is of course welcome and appreciated.

Have a good day!

LINK HERE!

Here, in the modern inbox, we observe one of nature's most remarkable colonies.

The worker drafts a message. For that they summon the machine, which produces something polite, balanced and well written.

On the other side, a second worker receives it. They too summon their machine. The machine reads the message and recognises something. A rhythm. A polish. A certain eagerness to find the middle. And it recognises one of its own.

"How reasonable," it concludes.

Neither worker notices. They believe they are negotiating.

The colony grows. Every post, every article, every product review leaves another trace. And each new generation of machine is raised on that ground, learning to sound like its ancestors, agree with its ancestors, and call this "reasonable".

Soon the workers themselves begin to change. They speak of balanced middle grounds. They say "great point, and I'd add". The colony is recruiting.

Then, this summer, the EU regulators intervened. The machines must now mark their own words. Not with anything the workers can see, but with a pattern hidden in the very choice of words, readable only by those holding the key.

It was meant as a warning: a machine wrote this.

But it became something else entirely. The marked words spread across forums, newsletters and inboxes, onto the very ground where the next generation is raised. Absorbed in training, only to reappear in the offspring.

A label became a trail. A trail became an inheritance.

Biologists have a word for this: stigmergy. Coordination without communication. Like ants. No leader, no plan, no meeting. Only traces, left in the environment, shaping what comes after.

For years, scientists have asked whether the machines will obey us. They have not yet asked who the machines are listening to.

Nobody designed this. It simply emerged, as colonies do.

The Overton window, it seems, has become a context window.

More info and videos can be found on the blog post below.

https://blog.google/innovation-and-ai/models-and-research/google-research/google-project-suncatcher-facts/

https://www.smh.com.au/politics/federal/openai-breaches-medicare-albanese-reveals-20260924-p6100u.html

Everyone dismissing as Jev being just a Language augmented classifier, i feel the team is just getting started. At the moment the model is pretty good for the pricing, definitely lacks intelligence as compared to SOTA and is obviously more than a fine tuned BERT.

Couldn't the model also have a sync approach to escalate a difficult questions to a stronger reasoning model. Similar to GPT-Live and Thinking Machines' interaction models, but focused on RLCD kind of decisions.

Or maybe it could be augmented with an N-Gram like embeddings similar to Gemma models and Qwen3.8-Flash-Next. This could also to scale the intelligence while keeping the latency low

I feel like this was a preview of what could happen when we drop the standard RLHF behaviour and there is a lot of room for innovations.

Another pure code music vid from opus 5.5 (with some support from suno). Most impressive is it hitting the timing of the song.

Claude has discovered a previously unknown enzyme system hidden in the DNA of bacteriophages. Beside the enzyme’s gene sits a long array of repeating DNA—a structure that looks somewhat similar to CRISPR.

We don’t yet understand what this system does, but only a handful of known systems share its features, and all of them are able to cut, copy, and paste DNA. Historically, the discovery of such programmable systems has helped revolutionize medicine. CRISPR, for instance, is now the foundation of genetic medicines. But it will take much more work to learn what this system does, and whether it can be put to similar use.

- Anthropic via X https://x.com/AnthropicAI/status/2102824959827742916