Build Recurrent-Depth Transformers with OpenMythos for MLA, GQA, Sparse MoE, and Loop-Scaled Reasoning
In this tutorial, we explore OpenMythos by building an advanced recurrent-depth transformer workflow that runs end-to-end in Google Colab. We create both MLA and GQA model variants, compare their parameter counts, and check the stability of the recurrent injection matrix through its spectral radius....
Temporal Contrastive Transformer for Financial Crime Detection: Self-Supervised Sequence Embeddings via Predictive Contrastive Coding
arXiv:2605.21490v1 Announce Type: new
Abstract: We introduce the Temporal Contrastive Transformer (TCT), a representation learning framework designed to capture contextual temporal dynamics in sequences of financial transactions. The model is trained using a self-supervised contrastive objective to...
Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation
arXiv:2605.21491v1 Announce Type: new
Abstract: As language models accelerate scientific research by automating hypothesis generation and implementation, a new bottleneck emerges: evaluating and filtering hundreds of AI-generated ideas without exhaustive experimentation. We ask whether LMs can lear...
The Attribution Impossibility: No Feature Ranking Is Faithful, Stable, and Complete Under Collinearity
arXiv:2605.21492v1 Announce Type: new
Abstract: No feature ranking can be simultaneously faithful, stable, and complete when features are collinear. For collinear pairs, ranking reduces to a coin flip. We prove this impossibility, quantify it for four model classes, resolve it via ensemble averagin...
OpenAI named a Leader in enterprise coding agents by Gartner
OpenAI is named a leader in the 2026 Gartner Magic Quadrant for Enterprise AI Coding Agents, with Codex recognized for innovation and enterprise-scale deployment.
How CopilotKit Is Redefining the Agentic AI Stack in 2026
An inside look at CopilotKit’s 2026 shipping cycle. Learn how the new AG-UI protocol, AIMock testing suite, and Pathfinder server are providing the production architecture developers need for agentic AI.
The post How CopilotKit Is Redefining the Agentic AI Stack in 2026 appeared first on MarkTechPos...
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...