Qwen Introduces Qwen3.7-Max: A Reasoning Agent Model With a 1M-Token Context Window
Alibaba's Qwen team introduced Qwen3.7-Max at the 2026 Alibaba Cloud Summit, describing it as its most advanced and comprehensive agent model to date. The model features a 1M-token context window, extended-thinking mode, and is designed for long-horizon tasks including coding, debugging, and multi-s...
Cohere Releases Command A+: A 218B Sparse MoE Model for Agentic Workflows That Runs on as Few as Two H100 GPUs
Cohere releases Command A+, an open-source 218B Sparse Mixture-of-Experts model consolidating four prior Command A variants into one. It runs on as few as two H100 GPUs at W4A4 quantization, supports 48 languages, and is Cohere's first multimodal reasoning model.
The post Cohere Releases Command A+:...
Roundtables: Can AI Learn to Understand the World?
Listen to the session or watch below AI companies want to build systems that understand the external world and overcome the limitations of LLMs. Recent developments have brought world models to the forefront of the AI discussion. Watch a conversation with editor in chief Mat Honan, senior AI editor ...
Trump delays AI security executive order: ‘I don’t want to get in the way of that leading’
President Trump delayed signing an executive order that would have required pre-release government security reviews of AI models, citing dissatisfaction with the order's language.
MagenticLite, MagenticBrain, Fara1.5: An agentic experience optimized for small models
MagenticLite is an agentic system for small models that works across the browser and local file system in a single workflow. It combines specialized models and orchestration to support efficient agentic performance on everyday tasks.
The post MagenticLite, MagenticBrain, Fara1.5: An agentic experien...
Making User-Sequence Data More Cost-Efficient, Faster, and Easier to Use
Authors (listed alphabetically)Ads Feature Engineering Infra team: Ajay Venkatakrishnan, Le ZhangCore ML Infra team: Eric Shang, Pihui WeiML Data team: Connor Votroubek, Yi HeUser Understanding team: Camilo Munoz, Simin LiIf you work on ranking, retrieval, or recommendation systems, you’ve probably ...
NVIDIA GTC Taipei at COMPUTEX: Live Updates on What’s Next in AI
At NVIDIA GTC Taipei at COMPUTEX, the world’s developers, researchers and industry leaders are converging to dive into the latest breakthroughs shaping every industry, covering topics spanning AI factories and scaling infrastructure to agentic and physical AI and more.
For over a century, both the prestige and budget of a corporate department have been measured by a single crude metric: headcount. If you manage 500 people, you’re a “distinguished leader.” If you manage five, you’re a footnote. This “empire of headcount” has governed everything from office square f...
Google Search just went from being an encyclopedia to an assistant. That’s the crux of everything Google announced in its recent I/O conference for 2026. The buzzword is “AI agents”, which now enter Google Search, its coding platforms, and even get a whole new standalone app for themselves. The idea...
Prompt Engineering Isn’t Enough — I Built a Control Layer That Works in Production
Most LLM failures in production aren’t random — they’re predictable.
I kept hitting broken JSON, silent failures, and outages that froze my entire app. Prompt engineering didn’t fix it.
So I built a control layer above the model — and took structured output reliability from 0% to 100% without changi...
One Model, Three Modalities: ByteDance Releases Lance for Image and Video Understanding, Generation, and Editing
ByteDance's Intelligent Creation Lab has released Lance, an open-source native unified multimodal model that handles image and video understanding, generation, and editing — all within a single framework, using only 3B activated parameters.
The post One Model, Three Modalities: ByteDance Releases La...
Neural Estimation of Pairwise Mutual Information in Masked Discrete Sequence Models
arXiv:2605.20187v1 Announce Type: new
Abstract: Understanding dependencies between variables is critical for interpretability and efficient generation in masked diffusion models (MDMs), yet these models primarily expose marginal conditional distributions and do not explicitly represent inter-variab...
GraphDiffMed: Knowledge-Constrained Differential Attention with Pharmacological Graph Priors for Medication Recommendation
arXiv:2605.20188v1 Announce Type: new
Abstract: Recommending safe and effective medication combinations from electronic health records (EHRs) is a core clinical AI problem, yet it remains difficult because patient trajectories are long, noisy, and clinically heterogeneous. Existing methods typicall...
TabPFN-MT: A Natively Multitask In-Context Learner for Tabular Data
arXiv:2605.20234v1 Announce Type: new
Abstract: Prior-Data Fitted networks (PFNs) have been very successful in tabular contexts, handling prediction tasks in context. However, they are designed for single-task inference, meaning that predicting several target values within a context requires repeat...
Provably Learning Diffusion Models under the Manifold Hypothesis: Collapse and Refine
arXiv:2605.20235v1 Announce Type: new
Abstract: Diffusion models generate high-dimensional data with remarkable quality, yet how their training efficiently learns the score function, bypassing the curse of dimensionality when data is supported on low-dimensional manifolds, remains theoretically une...
SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation
arXiv:2605.20189v1 Announce Type: new
Abstract: Despite the remarkable success of large language models (LLMs), they still face bottlenecks while deploying in dynamic, real-world settings with primary challenges being concept drift and the high cost of gradient-based adaptation. Traditional fine-tu...
Tool-Augmented Agent for Closed-loop Optimization,Simulation,and Modeling Orchestration
arXiv:2605.20190v1 Announce Type: new
Abstract: Iterative industrial design-simulation optimization is bottlenecked by the CAD-CAE semantic gap: translating simulation feedback into valid geometric edits under diverse, coupled constraints. To fill this gap, we propose COSMO-Agent (Closed-loop Optim...
AgentCo-op: Retrieval-Based Synthesis of Interoperable Multi-Agent Workflows
arXiv:2605.20425v1 Announce Type: new
Abstract: Designing multi-agent workflows is especially difficult in open-ended scientific settings where tasks lack curated training sets, reliable scalar evaluation metrics, and standardized interfaces between existing tools and agents. We propose AgentCo-op,...