TiTikey

Tonight’s editorial on silly linear extrapolation: How many GPT releases till saturation on the artificial analysis intelligence index: If we assume +2 points for every .1 GPT release Which would mean we would saturate all current benchmarks by GPT 7.25 Hopefully OpenAI keeps up that release pace!

THIS GUY VIBE CODED A GTA STYLE GAME ON TOP OF GOOGLE EARTH IN A SINGLE WEEKEND WITH CLAUDE CODE. Real cities, real streets, real airports, local radio, cops, hospitals, and a browser game that would’ve taken months to build the old way.

New Grok Imagine model just dropped with much better lip sync & sound. Nothing in this video is real.

GPT-5.5 XHIGH is working hard right now to make vLLM runs DeepSeek 4 Flash on 4x DGX Sparks It got it to load, then had it answer cohesively on the 4x Sparks (though a tad too slow) Now, it optimizes it Letting this run overnight (in an engineered-harness specifically for it)

> cd to a new folder. > forget to type “claude” > type a very long prompt. > zsh: command not found.

GPT-5.5 is now available in the OpenAI API! The big thing for developers is that it’s not just smarter, it can get complex tasks done with fewer tokens and fewer retries. Ask Codex to migrate your Responses API integration to GPT-5.5!

Here is a high-level overview of my Local RAG / AI Knowledge Stack All hosted locally on a single RTX 3070 8GB btw Who is interested in a more in-depth breakdown? What would you like for it to cover?

Anthropic launched "Project Deal," a real-world internal marketplace where Claude agents autonomously interviewed 69 employees to learn their preferences, and then independently bought, sold, and haggled on their behalf. The autonomous barterers successfully executed 186 physical deals totaling over $4,000 in transaction volume. The agents performed with eerie accuracy, one Claude even deduced its user's preferences so perfectly it bought the exact snowboard the employee already owned.

Minimax M2.7 GLM 5.1 Qwen 3.6 plus (not open) Kimi K2.6 Deepseek v4 Mimo V2.5 Thank you for all you do for keeping AI democratic and universal for all.

🥊 Round 5 Qwen3.6 27B vs Claude Opus 4.5 Came up with a new prompt to settle the fight 🦩 "Salt Flat Mirror" challenge (inspired by Salar de Uyuni) One HTML file, full-page canvas, no libraries. Why this challenge is interesting: Perfect dual coherence. The sky and its reflection must stay perfectly aligned. The flamingos need to appear both above and below the horizon with accurate reflections. Most models either simplify the birds or completely skip the reflection. A genuinely tough final-round test! — 1st run [115s and 68s] 27B... No real depth, broken clouds, and the reflections were decent for the flamingos and clouds but failed to mirror the sky’s colors properly. The canvas almost looks broken (it isn’t) Opus... 🤯 The only real flaw is a duplicated sun reflection on the horizon. Other than that… my god, it’s beautiful. — 2nd run [108s and 66s] 27B... Way better! Depth, solid clouds, and proper reflections this time! However, all the flamingos are flying and the sun is having a seizure 😅 Opus!! 🚀 Nailed it twice in a row. Literally nothing to say, a total beast on this challenge. I’m genuinely impressed. Look at this water reflection.. — 🏆 Claude Opus 4.5 is the winner After five challenges, one thing stands out: even when Claude’s output has broken elements, the code structure and overall quality are clearly superior to the 27B. You can feel it. That said, Qwen 27B still delivered some seriously impressive results; especially when you remember it’s running locally on a heavy quantization (UD-IQ3_XXS) Yes, Opus 4.5 is a level above. But the most insane part? Anyone with a 16GB VRAM card can run the 27B. Fitting this much intelligence into that amount of VRAM is crazy! Wrapping up this fight, what did you guys think? What should the next matchup be? 👀 ↓ All the other challenges under this post