AI Radar

Some of my tests with qwen image 2.1

I highly recommend to read the official documentations for better output The lighting and details are nuclear Downsides as i noticed: Limited style diversity, too much hellucination, bad understanding of physics, limited multi-languages support submitted by /u/CosmicTurtle44 [link] [comments]

Hex turns complex analysis into visual reports with GPT‑6 Astra

GPT-6 Astra helps Hex’s data agents turn answers into interactive visualizations that employees are proud to share.

World model companies are keeping a lot of secrets

Everyone in the world-models space is sitting on a pile of cash and a ton of buzz, but good luck getting anyone — from the founders to their own data suppliers — to tell you what they're actually building.

Over 85% of Japanese Game Developers Now Use Generative AI, According to TGS Report

CESA reports that over 85% of Japanese game developers use generative AI at least occasionally, while studios are prioritizing human review, restricted tools, and policies against using raw outputs unchanged.

The Official Unity Plugin for Codex

Unity's official plugin for Codex is an official plugin that gives OpenAI's Codex Unity-written skills, so the agent works from Unity's own guidance for jobs like sprite atlases, URP renderer features, in-app purchases, and localization instead of from whatever it absorbed about Unity elsewhere.

Pirate Face Rescues LLM Models from Deletion

DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression

The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost of long-context computation, prefill remains computationally expensive, and large KV caches continue to strain HBM and SSD capacity and data-transfer bandwidth. Together, these compute, storage, and bandwidth demands constitute the primary bottleneck to further lowering deployment costs. To address this challenge, we introduce DeepSeek-V4.1-Flash, a multimodal Mixture-of-Experts (MoE) model with 552B backbone parameters and support for…

Qwen Image 2.1

Can MiniMax-H3 Reason About the Physical World? An Evaluation of Omni-Modal Generative Model

Recent Omni-Modal Generative Models (Omni-Models) have advanced content generation toward unified modeling of text, images, video, and audio. MiniMax-H3 exemplifies this transition by combining multimodal context understanding with joint audio-visual generation in a shared latent framework. Its unified architecture raises a fundamental question: Can multimodal alignment improve the model's world reasoning, and what new evaluation paradigms do omni-modal inputs enable? To investigate this question, this work introduces a comprehensive evaluation framework organized around four complementary…