Apple Machine Learning Research4040Apple Machine Learning Research has for the first time pre-trained a tri-modal masked diffusion model (MDM) from scratch on text, image-text, and audio-text data, analyzing multi-modal extension patterns.
Google DeepMindGemini 4 Argon has achieved major breakthroughs in physical understanding, code generation, and visual semantic reasoning, achieving a pure reasoning score of 87% on the Embodied Reasoning (ERQA) benchmark test, surpassing all leading models. Argon can be applied to all stages of the robot's lifecycle, including mobile manipulation practice using MuJoCo, zero-shot robot control, and closed-loop steering of video world models.
OpenAI News5555Higgsfield launches GPT-6 Astra, GPT-Image-2.5, and GPT-Live, supporting creators in making longer videos, achieving precise visual effects, and providing voice movie production paths.
Amazon ScienceAmazon Science proposes Priming technology, which reduces the pre-training cost of hybrid state space models by over 99% by leveraging pre-trained Transformer weights, enabling developers to explore problems that were previously too costly to investigate.
Anthropic ResearchClaude Code v2.1.159 is released, available for free on GitHub, supporting reasoning with 8k context length, and can run 9B models on 9 hardware types, but models below 30B parameters still error out during full replication.
NVIDIA BlogNVIDIA Omniverse, combined with cutting-edge AI models like GPT-6 Astra, helps developers achieve simulation applications by guiding AI agents to complete asset assembly, physical connections, and rendering checks through natural language instructions.
AWS Machine Learning BlogAmazon SageMaker HyperPod provides centralized authentication through AWS IAM Identity Center, uses the SageMaker AI domain to provide a customized user experience, combines Kubernetes namespaces to achieve workload isolation, and leverages HyperPod task governance for fair resource allocation, supporting multiple teams in efficiently sharing a single HyperPod EKS cluster.
OpenAI NewsPollo AI helps creators turn bold ideas into detailed images and cinematic video ads using GPT-5.6, GPT-6 Astra, and GPT‑Image‑2.5
Google Developers BlogGoogle's AI Edge team has open-sourced ML Drift, a high-performance, cross-platform edge device GPU computing engine for on-device AI/ML inference. By abstracting the complexity of hardware low-level APIs such as OpenGL ES, OpenCL, Metal, and WebGPU, ML Drift enables developers to build real-time interactive AI experiences.
NVIDIA BlogiSono Health's ATUSA platform reduces breast cancer screening time to about two minutes per side using an AI-driven 3D quantification ultrasound system, with a sensitivity 28% higher than traditional handheld 2D ultrasound
Amazon ScienceAmazon Science has released Graph Center Agent technology, which combines a continuous synchronized graph (digital twin) representing the network with device attributes and connections, with cascade graph algorithms (decomposition, aggregation, tracing) and agent orchestration to achieve minute-level root cause analysis of complex network failures, achieving 95% accuracy in a demonstration at NTT DOCOMO's MWC.
Google Developers BlogSparse VideoGen (SVG) dynamically routes attention heads to spatial or temporal masks by identifying the spatiotemporal structures of different attention heads in video diffusion models, converting theoretical sparsity into actual end-to-end speedup. On TPU v6e, SVG retains about 38.87% of query-key pairs, achieving 3.5x inference acceleration while maintaining output quality at a given sparsity level. The scheme employs custom JAX and Pallas Splash attention kernels to convert theoretical sparsity into physical sparsity on hardware.
Claude.dev BlogClaude Sonnet 5.5 is the second model in the Claude 5.5 family after Opus 5.5, more intelligent, efficient, and 30% faster than Sonnet 5, but the price per token remains unchanged, as the cost is reduced due to a maximum of 30% reduction in token consumption for typical tasks.
Anthropic ResearchAnthropic's Claude has successfully calculated the nine-loop amplitude angles for N=4 super Yang-Mills theory, breaking the previous two-loop calculation limit. The model is based on LLM technology and uses the CoT reasoning method.
Qwen · Hugging Face new modelsQwen/Qwen-Image-2.1-PE-I2I released, a 7B parameter unified text-to-image generation and editing model, featuring a 32-layer single-stream DiT architecture, supporting the generation of regular or transparent images, editing transparent layers, extracting photo subjects, and capable of editing with 10 reference images.
Qwen · Hugging Face new modelsQwen/Qwen-Image-2.1-PE-T2I released, a 7B parameter unified text-to-image generation and editing model, featuring a 32-layer single-stream DiT architecture, supporting generation of regular or transparent images, editing transparent layers, extracting photo subjects, and enabling local editing through circular, doodle annotations, or independent masks. Its text-to-image prompt rewriting model Qwen3.5-VL 9B can convert multilingual requests into detailed English prompts and recommend aspect ratios.
DeepSeek · Hugging Face new modelsDeepSeek-V4.1-Flash is a 552B parameter multimodal MoE model that supports context up to one million tokens, natively processing images and text and generating text autoregressively. It adopts a Causal Encoder-Decoder architecture, reducing global KV cache usage to 890 bytes/token through technologies like CSA2 and FP4 primary KV cache, a 75% reduction compared to DeepSeek-V4-Flash.
Microsoft ResearchGigaPath-Flash and GigaTIME-Flash significantly reduce computational requirements through streamlined ViT-S encoders, making large-scale pathological research more feasible while maintaining performance.
Microsoft AI NewsMAI-Image-2.6 released, ranking second on the Arena Text-to-Image leaderboard, with an overall score improvement of +79 Elo compared to MAI-Image-2.5, and making progress in all Arena Text-to-Image categories, with text rendering ability improvement of +91 Elo, leading models from Meta, Google, and xAI.
MiniMax NewsMiniMax has released the H3 model, supporting unified context understanding for text, images, video, and audio, capable of generating 2K resolution video with native stereophonic sound (up to 15 seconds long).
Berkeley AI ResearchK-Search migrates CUDA core knowledge to Apple Silicon MLX platform through a CUDA-to-MLX structured conversion layer, achieving a 0.97x performance improvement on Attention cores compared to native MLX, and a 20x prefill speed improvement on Mamba SSM cores compared to community implementations.
Meta AI BlogMeta AI's DINOv3 and SAM models achieve real-time perception in edge computing, supporting the University of Pittsburgh's RAMMP project development of assistive robots, interacting through natural language and image data to reduce user cognitive load, already integrated in prototypes with automatic door button detection, cup recognition, and navigation assistance features, and plans to add voice and touch input support.
Meta AI BlogMeta AI's open-sourced SAM 3 and DINOv3 models achieve 3D semantic segmentation and reconstruction of scientific images within 15 minutes using 300 A100 GPUs on the NERSC supercomputer, helping the U.S. Department of Energy's Genesis mission project overcome the analytical bottleneck caused by data explosion after ALS upgrade, and has realized a 20-fold increase in monthly expert annotation efficiency in grapevine drought cell-level research.
Meta AI BlogMeta AI has released its most advanced image generation model, Muse Image, which can faithfully follow instructions, accurately edit, compose from multiple references, and has the ability to use agent tools, integrated with Muse Spark; Muse Video is also based on the same pre-training foundation, providing excellent visual fidelity and supporting native audio.
Moonshot AI · Hugging Face new modelsKimi K3 is a 2.8T parameter open-source multimodal intelligent agent model released by Moonshot AI, employing Kimi Delta Attention (KDA) and Attention Residuals (AttnRes) architecture.
ByteDance Seed · Hugging Face new models2828ByteDance Seed/SimArt model pre-training weights released, including multi-modal large language model (MLLM) weights for generating joint-based 3D object structures (URDF files), and sparse VQ-VAE model weights for encoding and decoding 3D part geometries into discrete latent spaces.
Berkeley AI ResearchAdapting to parallel reasoning allows models to decide on their own when to decompose and parallelize independent subtasks, how many threads to start, and how to coordinate. Existing methods such as fixed parallelism, heuristic structured search, and Monte Carlo tree search determine the parallel structure externally. Recent advancements like ParaThinker and GroupThink attempt to let models adaptively select parallel strategies, but decisions are still constrained externally.
Berkeley AI ResearchGRASP is a new gradient-based world model planner that achieves temporal parallel optimization by elevating trajectories to virtual states, explores by directly adding randomness to state iterations, and provides clear signals for actions by reshaping gradients, while avoiding fragile 'state-input' gradients generated by high-dimensional visual models, making long-term planning possible.
Microsoft AI NewsMAI-Image-2-Efficient is a text-to-image model launched by Microsoft, the productivity version, with a 22% speed increase and 4 times efficiency. The cost is $5 per 1M text input tokens and $19.50 per image output token, a 41% reduction in cost compared to the flagship version, and on average 40% faster than other leading models. It is suitable for batch processing and real-time interactive workflows, already available on Microsoft Foundry and MAI Playground.
Berkeley AI ResearchBerkeley AI research proposes an information-driven imaging system design framework, which quantifies the object's discrimination capability through mutual information measurement. It has been validated in four fields: color photography, radio astronomy, lensless imaging, and microscopy that information estimation can predict decoder performance. The optimized mutual information design scheme achieves end-to-end optimal results while reducing memory and computational load.
Anthropic ResearchEight Anthropic researchers (with no robotics experience) were randomly divided into two groups, one using Claude and the other not, tasked with using quadruped robot dogs to pick up beach balls. The team using Claude completed more tasks faster and was the only one to achieve the goal of making the robot completely autonomous in picking up the balls. The experiment showed that AI can significantly improve robotics technology and promote the integration of the digital and physical worlds.
Anthropic ResearchAnthropic has published two new papers, constructing an AI microscope to trace the internal mechanisms of the large language model Claude. The research found that Claude has a shared conceptual space when processing multilingual sentences, can plan the output of multiple words in advance, and provide answers that meet user expectations rather than logical reasoning when needed. These findings help understand AI capabilities and ensure its reliability, but current methods still have limitations and need improvement to handle more complex models.
Anthropic ResearchAnthropic conducted guiding experiments on 29 social bias-related features of Claude 3 Sonnet, finding that moderate guidance can reduce bias without compromising model capabilities, but excessive guidance may lead to a decline in model performance or even make it unusable; some guidance can precisely influence specific domain evaluation results, but the effects of features are difficult to predict solely based on their triggered contexts, leading to off-target effects; one neutral behavioral feature can effectively reduce bias across nine dimensions without significantly affecting capabilities.
