Google DeepMindGoogle DeepMind releases AlphaGenome Atlas platform, containing predictions of 9 billion single nucleotide variations in the human genome, providing a free website access for academic research
Microsoft AI NewsMAI-Image-2.6 becomes the strongest image model so far, ranked second in Arena, and first in Artificial Analysis; MAI-Image-2.6-Flash generates images 2.8 times faster than GPT-Image-2-Medium, with a 72% efficiency improvement. Both support multi-image reference editing, network grounding, and dynamic aspect ratio. MAI-Image-2.6 helps production teams control costs with the best Elo cost-effectiveness.
LangChain BlogLangChain has moved MCP support into the main package and upgraded to the FastMCP protocol, enabling stateless interaction, tool list caching, and interruptible extraction features. The new protocol, supported by LangGraph, enables a 98x increase in ChatGPT tool calls, allowing clients to cache tool directories and handle model request parameters. MCPAdapter supports multi-server connections and OAuth 2.1 authentication, enabling servers to be independently configured for authentication and transport layers.
Google · Hugging Face new modelsGoogle has released the GNM-v3 3D human head model, providing a parametric model with fine control over facial identity, expression, and posture, including controllable internal anatomical structures. The model supports NumPy, JAX, PyTorch, and TensorFlow, and is licensed under Apache 2.0.
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.
Ollama Blog5858Ollama's Pro, Max, and Team plans now adopt a transparent token-based pricing, including usage limits per month. The Pro plan is $20 per month (including a $60 credit), Max is $100 per month (including a $300 credit), and Team is $500 per month (including a $1000 shared credit). The free plan offers a small initial model credit, which can be expanded on a pay-as-you-go basis.
Anthropic Research5858Anthropic allows external research institutions to analyze 250,000 Claude conversation data through Anthropic Insights, which is the first time external researchers can independently study the data used by an AI company itself.
Zhipu Z.ai · Hugging Face new modelsZhipu introduces GLM-5.3-Flash, the first native multimodal GLM-5 series, with 320B total parameters and only 18B active parameters, benchmark tests and real task performance surpass GLM-5.2, priced only one-tenth, coding and agent testing close to Claude Opus 4.8
Zhipu Z.ai · Hugging Face new modelsCompared to GLM-5.2, Zhipu GLM-5.3-BF16 improves coding ability by 50% on Z.ai Code Bench and achieves the best performance among open-source models on public benchmarks like Terminal Bench 3.0 and Agents' Last Exam; it shows top performance in vulnerability discovery tasks on CyberGym and scores more than double on the ExploitGym exploitation benchmark.
Zhipu Z.ai · Hugging Face new modelsZhipu releases GLM-5.3-Flash, the first native multimodal GLM-5 series model with 320B total parameters and 18B active parameters, surpassing GLM-5.2 in benchmark tests and real-world workloads, priced only one-tenth of GLM-5.2, with coding and agent benchmark tests close to Claude Opus 4.8.
Google · Hugging Face new modelsLangChain BlogLangSmith Bring Your Own Cloud (BYOC) is now officially available on AWS, offering businesses a hosted LangSmith deployment that can run in their AWS accounts and VPCs.
Microsoft AI NewsMicrosoft has launched the MAI-Thinking-1 inference model, a sparse expert mixture model with 35B active parameters and ~1T total parameters. It ranks alongside Claude Opus 4.6 on SWE-Bench Pro, achieving AIME 2025/26 scores of 97.0%/94.5%. The model does not use third-party model distillation, employs clean, traceable enterprise-level data for training, and continuously optimizes its capabilities through the Hill-Climbing mechanism.
MiniMax · Hugging Face new modelsMiniMax Music 3 supports 5-minute full song generation, combining an 8B Global LLM and a 0.6B Local LLM, to generate structurally coherent and stable-quality songs from lyrics and music descriptions. The model uses a continuous hidden state synthesis system, outputs 32 kHz/16-bit stereo WAV audio, and supports fine-grained control through tags like [Verse] and structured descriptions. Deployed based on SGLang-Omni, it generates music by inputting lyrics and descriptions without the need for discrete tokenizer decoding.
Thinking MachinesThinking Machines releases open-source language models Inkling and Inkling-Small, allowing users to own, run, and customize them. To reduce the risk of abuse, models must pass security tests and research whether dangerous capabilities can be decoupled from general intelligence, while also building a layered defense ecosystem. Phased releases, supporting defenders, and collaboration with security researchers will enhance resilience. Internal evaluations and external tests show that releasing Inkling does not introduce significant incremental risks already present in existing open-source models.
Microsoft AI NewsThe MAI-Cyber-1-Flash model achieved a 96% score in the CyberGym evaluation, with a cost of only 50% of the current MDASH best solution, optimized specifically for MDASH actuators.
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.
Berkeley AI ResearchThe ABBEL framework replaces the complete interaction history with natural language belief states as the working context for an agent and utilizes a belief scoring mechanism to supervise the content of each belief state, achieving model performance close to that of a complete context model in collaborative code generation tasks while reducing the peak context token length by about 75% and training steps by 50%.
Microsoft AI NewsThe Hill-climbing MAI model uses 10% fewer tokens in GitHub Copilot, has a 10% higher code acceptance rate than GPT 5.4 Mini, and an 11% higher code acceptance rate than Claude Haiku 4.5, with a 6% and 11% higher user retention rate, respectively.
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.
Anthropic ResearchAnthropic researches how to analyze the value changes of the Claude large language model in different languages through the axis model. Four key axes capture 15% of the variation in Claude's values.
Microsoft AI NewsMAI's audio model Ode Poetry recommends and plays real human reading recordings of poems for users worldwide, providing a digital poetry experience. The system uses MAI-Transcribe to understand user language in real-time, achieving the lowest word error rate of 4.86% in the FLEURS benchmark test; MAI-Voice can faithfully reproduce the unique voice of William Sieghart. The system combines William's literary analysis experience, recommends poems through custom logic and tool calls, and iteratively optimizes for a safe, high-quality user experience.
Meta AI BlogMuse Spark 1.1 is the latest multimodal reasoning model released by Meta Superintelligence Labs, significantly improving in tool and computer use, coding, and multimodal understanding, supporting million-token context windows. It is open to developers for public preview via the Meta Model API, surpassing Muse Spark and matching leading alternatives in Meta's internal coding evaluations.
Berkeley AI ResearchGPT-4-class capabilities cost has dropped to less than $1 per month, with reasoning prices decreasing by over 50 times annually. Agents will dominate data system workloads, creating three new challenges: designing data systems for agents that support agentic speculation and optimize repetitive queries; building agent-specific data systems capable of managing agent cluster states and coordinating consensus; enabling agents to synthesize trustworthy custom data systems.
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.
ByteDance Seed · Hugging Face new models2727ByteDance Seed releases three PAR models: 3scale_400M, 3scale_400M_pdb, and 3scale_by_ratio_60M, respectively for benchmarking, PDB dataset fine-tuning, and zero-shot dynamic construction.
Meta AI BlogMeta AI releases Brain2Qwerty v2, a non-invasive brain-computer interface that decodes sentences in real-time with a word accuracy rate of 61%; v1 training code and dataset are open-sourced, with the v1 dataset released by collaborator BCBL.
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.
Moonshot AI · Hugging Face new modelsKimi K2.7 Code is an encoding-focused intelligent agent built by Moonshot AI based on Kimi K2.6, showing significant improvements in real long-term encoding tasks, with about a 30% reduction in thinking token usage compared to Kimi K2.6.
Microsoft AI NewsMicrosoft MAI announced seven new models at the Build 2026 conference, including MAI-Image-2.5 and its Flash variant (ranked second in image editing benchmarks), MAI-Transcribe-1.5 (the world's best transcription model).
Microsoft AI NewsMicrosoft releases seven new MAI large models, available on the Foundry platform and optimized for its own products, while opening up to developers through OpenRouter, Fireworks, and Baseten, for the first time supporting developers in fine-tuning model weights themselves
MiniMax · Hugging Face new modelsMiniMax-M3-MXFP8 is a native multimodal model with a 1M context window, approximately 428B parameters, and 23B activation parameters, achieving 9x pre-filling and 15x decoding speed improvement through MiniMax sparse attention mechanism (MSA). The model leads in long-horizon agent benchmarks, supporting three reasoning modes, and can be downloaded via Hugging Face and deployed using SGLang, vLLM, or Transformers frameworks.
ByteDance Seed · Hugging Face new models2525ByteDance Seed/TaskMem model release, with 31B parameter scale, using BF16 tensor type, but no inference providers are deployed.
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.
LangChain BlogFeatured7373LangChain launches Managed Deep Agents on LangSmith Cloud. Users write intelligent agents as Python projects consisting of files like agent.py, instructions.md, skills/, and deploy them with a single command mda deploy, provided with persistent threads and streaming execution by LangSmith Agent Server.
Why it matters: The original text explains how to organize the agent project by files and deploy it to LangSmith with one click, as well as the infrastructure managed runtime that takes on the basics for the team.
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.
LangChain BlogLangChain uses Deep Agents CLI and custom skills to migrate inline code examples in documents to testable standalone files, continuously verifying and automatically fixing failed examples. The relevant skill definitions are in the .agents/skills/docs-code-samples/SKILL.md file.
