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DeepSeek AI Releases DeepSeek-V4: Compressed Sparse Attention and Heavily Compressed Attention Enable One-Million-Token Contexts

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DeepSeek-AI has released a preview version of the DeepSeek-V4 series: two Mixture-of-Experts (MoE) language models built around one core challenge making one-million-token context windows practical and affordable at inference time. The series consists of DeepSeek-V4-Pro, with 1.6T total parameters and 49B activated per token, and DeepSeek-V4-Flash, with 284B total parameters and 13B activated per token. […]

DeepSeek AI Releases DeepSeek-V4: Compressed Sparse Attention and Heavily Compressed Attention Enable One-Million-Token Contexts Read More »

Google DeepMind Introduces Decoupled DiLoCo: An Asynchronous Training Architecture Achieving 88% Goodput Under High Hardware Failure Rates

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Training frontier AI models is, at its core, a coordination problem. Thousands of chips must communicate with each other continuously, synchronizing every gradient update across the network. When one chip fails or even slows down, the entire training run can stall. As models scale toward hundreds of billions of parameters, that fragility becomes increasingly untenable.

Google DeepMind Introduces Decoupled DiLoCo: An Asynchronous Training Architecture Achieving 88% Goodput Under High Hardware Failure Rates Read More »

Mend Releases AI Security Governance Framework: Covering Asset Inventory, Risk Tiering, AI Supply Chain Security, and Maturity Model

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There’s a pattern playing out inside almost every engineering organization right now. A developer installs GitHub Copilot to ship code faster. A data analyst starts querying a new LLM tool for reporting. A product team quietly embeds a third-party model into a feature branch. By the time the security team hears about any of it,

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Mend.io Releases AI Security Governance Framework Covering Asset Inventory, Risk Tiering, AI Supply Chain Security, and Maturity Model

Mend.io Releases AI Security Governance Framework Covering Asset Inventory, Risk Tiering, AI Supply Chain Security, and Maturity Model Read More »

OpenAI Releases GPT-5.5, a Fully Retrained Agentic Model That Scores 82.7% on Terminal-Bench 2.0 and 84.9% on GDPval

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OpenAI has released GPT-5.5, its most capable model to date and the first fully retrained base model since GPT-4.5. GPT-5.5 is designed to complete complex, multi-step computer tasks with minimal human direction. Think of it as the difference between an assistant who needs a checklist and one who understands the underlying goal and figures out

OpenAI Releases GPT-5.5, a Fully Retrained Agentic Model That Scores 82.7% on Terminal-Bench 2.0 and 84.9% on GDPval Read More »

A Coding Tutorial on OpenMythos on Recurrent-Depth Transformers with Depth Extrapolation, Adaptive Computation, and Mixture-of-Experts Routing

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In this tutorial, we explore the implementation of OpenMythos, a theoretical reconstruction of the Claude Mythos architecture that enables deeper reasoning through iterative computation rather than increased parameter size. We build and analyze models using both GQA and MLA attention mechanisms, examine memory efficiency through KV-cache comparisons, and validate stability via the spectral properties of

A Coding Tutorial on OpenMythos on Recurrent-Depth Transformers with Depth Extrapolation, Adaptive Computation, and Mixture-of-Experts Routing Read More »

Google Cloud AI Research Introduces ReasoningBank: A Memory Framework that Distills Reasoning Strategies from Agent Successes and Failures

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Most AI agents today have a fundamental amnesia problem. Deploy one to browse the web, resolve GitHub issues, or navigate a shopping platform, and it approaches every single task as if it has never seen anything like it before. No matter how many times it has stumbled on the same type of problem, it repeats

Google Cloud AI Research Introduces ReasoningBank: A Memory Framework that Distills Reasoning Strategies from Agent Successes and Failures Read More »

Xiaomi Releases MiMo-V2.5-Pro and MiMo-V2.5: Matching Frontier Model Benchmarks at Significantly Lower Token Cost

Xiaomi MiMo team publicly released two new models: MiMo-V2.5-Pro and MiMo-V2.5. The benchmarks, combined with some genuinely striking real-world task demos, make a compelling case that open agentic AI is catching up to the frontier faster than most expected. Both models are available immediately via API, and priced competitively. What is an Agentic Model, and

Xiaomi Releases MiMo-V2.5-Pro and MiMo-V2.5: Matching Frontier Model Benchmarks at Significantly Lower Token Cost Read More »

Alibaba Qwen Team Releases Qwen3.6-27B: A Dense Open-Weight Model Outperforming 397B MoE on Agentic Coding Benchmarks

Alibaba’s Qwen Team has released Qwen3.6-27B, the first dense open-weight model in the Qwen3.6 family — and arguably the most capable 27-billion-parameter model available today for coding agents. It brings substantial improvements in agentic coding, a novel Thinking Preservation mechanism, and a hybrid architecture that blends Gated DeltaNet linear attention with traditional self-attention — all

Alibaba Qwen Team Releases Qwen3.6-27B: A Dense Open-Weight Model Outperforming 397B MoE on Agentic Coding Benchmarks Read More »

Google Introduces Simula: A Reasoning-First Framework for Generating Controllable, Scalable Synthetic Datasets Across Specialized AI Domains

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Training powerful AI models depends on one resource that is quietly running out: specialized data. While the internet provided a seemingly infinite supply of text and images to train today’s generalist models, the next wave of AI breakthroughs — in cybersecurity, legal reasoning, healthcare, and other niche domains — requires data that simply doesn’t exist

Google Introduces Simula: A Reasoning-First Framework for Generating Controllable, Scalable Synthetic Datasets Across Specialized AI Domains Read More »