AI Radar

A LoRA I made: AnyAngle LoRA for Qwen Image 2.1. Style-Aligned Arbitrary Camera Angles

Hello everyone! I made a new LoRA for Qwen Image 2.1 for arbitrary camera angles for any image in (almost) every style. You can read all about it in the huggingface repo here: https://huggingface.co/lilylilith/QI_2.1_AnyAngle . Have a great day, and have fun! submitted by /u/SillyLilithh [link] [comments]

FuseReg: Regularizing Layer Fusion Mitigates the Reconstruction-Generation Gap in Representation Autoencoders

Representation autoencoders (RAEs) reuse features from a pretrained visual encoder as reconstruction and diffusion latents, integrating strong visual representations into image generation. However, RAEs still need to decide which encoder layers form the shared latent space for the generator and pixel decoder. This choice involves a trade-off. Shallower layers tend to preserve fine pixel details better, while deeper layers tend to yield better generation metrics. A fixed heuristic layer fusion therefore couples two stages that benefit from different information. We introduce FuseReg, which…

Google Research Introduces an AI Video Co-Director: 4 Agentic Frameworks for Coherent, Minutes-Long Video Generation

Google Research has introduced an AI video co-director for long-form video generation. The suite of 4 agentic frameworks turns short clips into coherent, minutes-long stories. It targets identity drift and cascading errors, the 2 failures that break most multi-shot AI video pipelines today. Why Long AI Videos Fall Apart Diffusion models render high-fidelity clips in […] The post Google Research Introduces an AI Video Co-Director: 4 Agentic Frameworks for Coherent, Minutes-Long Video Generation appeared first on MarkTechPost .

AI companies in race to demonstrate their model most threatening to humanity

Owed a billion dollars in Nvidia stock

Harvey turns legal context into stronger drafts with GPT-6 Astra

GPT-6 Astra produces more structured, context-aware legal documents, freeing lawyers to focus on strategy.

InternW0-Δ: A World Action Model Bridging Predictive Dynamics and Actions with 20K+ Hours of Open Data

World Action Models (WAMs) jointly model visual dynamics and action generation for generalist robot manipulation. A central challenge is to integrate priors from large-scale pretrained models---including visual dynamics, scene semantics, geometry, and motion---into a unified framework for robot action generation. We introduce InternW0-Δ, a unified WAM pretrained on a heterogeneous corpus that outperforms prior methods across simulation benchmarks and real-robot platforms. InternW0-Δ combines pretrained visual dynamics, scene-level semantics, 4D geometric and motion priors, and action…

Better prompt caching for GPT-6

Learn how GPT-6 improves prompt caching with higher cache hit rates, new diagnostics, explicit breakpoints, and controls that reduce latency and costs.