Microsoft AI Releases MAI-Cyber-1-Flash: 5B-Active-Parameter Cyber ​​Model Pushes MDASH to 95.95% in CyberGym

Microsoft AI Releases MAI-Cyber-1-Flash: 5B-Active-Parameter Cyber ​​Model Pushes MDASH to 95.95% in CyberGym

Microsoft AI has released the MAI-Cyber-1-Flash, its first model specifically designed for cyber defense. The model does not run as a standalone storage. It runs inside MDASHMicrosoft scan harness for many models. MAI-Cyber-1-Flash is a converter capable of self-attention and minimal Mixture-of-Experts layers. It carries 137B is the number of parameters with 5B in effectand … Read more

Kimi AI and kvcache-ai Open Source ‘AgentENV’: A Distributed System Enabling Agentic Reinforcement Training (RL) in Kimi K3

Kimi AI and kvcache-ai Open Source ‘AgentENV’: A Distributed System Enabling Agentic Reinforcement Training (RL) in Kimi K3

Kimi’s Moonshot AI team and kvcache-ai are open source AgentENV (AENV)a distributed platform for operating agent environments at scale. AgentENV enables agentic reinforcement (RL) training for For me K32.8-trillion-Mixture-of-Experts Moonshot model. The code goes under MIT License. Why Environment Infra Holds Agentic RL Agentic RL is not just a sample script. It requires the model … Read more

Perplexity Releases pplx, a Single-Binary CLI That Deploys Its Search API to Terminal Coding Agents

Perplexity Releases pplx, a Single-Binary CLI That Deploys Its Search API to Terminal Coding Agents

Confusion is released pplxthe official command-line client for its Search API. The tool returns the base search results and the extracted page text, all as JSON. According to its documentation, it targets humans and coding agents alike. It is not a chat client. There is no chat mode, no model selection and no integrated feedback. … Read more

KwaiKAT Team Releases KAT-Coder-V2.5: An Agentic Code Model Trained on 100,000+ Verified Locations

KwaiKAT Team Releases KAT-Coder-V2.5: An Agentic Code Model Trained on 100,000+ Verified Locations

The KwaiKAT team at Kuaishou has introduced KAT-Coder-V2.5. It’s a code model that’s trained to run inside real, executable repositories rather than a single-turn code release. The given model is available through StreamLake. An open source variant, KAT-Coder-V2.5-Dev, was released separately from Hugging Face under Apache-2.0. AutoBuilder: environments that use target tests The study puts … Read more

FAIRChem v2 UMA for Multidomain Atomistic Simulation across Molecules, Catalysts, Materials, Vibrations, and Molecular Dynamics

FAIRChem v2 UMA for Multidomain Atomistic Simulation across Molecules, Catalysts, Materials, Vibrations, and Molecular Dynamics

In this lesson, we explore FAIRChem v2 and the potential of studying the universal UMA interatomic machine as an integrated framework for atomistic simulations in molecular chemistry, catalysis, and inorganic materials. We configure the environment, validate with Hugging Face to access the UMA model weights, and implement task-specific counters in the omol, oc20, and omat … Read more

Sakana AI Releases Fugu-Cyber: Orchestration Model Reporting 86.9% in CyberGym and 72.1% in CTI-REALM

Sakana AI Releases Fugu-Cyber: Orchestration Model Reporting 86.9% in CyberGym and 72.1% in CTI-REALM

Sakana AI released Fugu-Cyber ​​(model ID is fugu-cyber-v1.0), a special cybersecurity addition to its Fugu orchestration family. It’s not just a new frontier model. It is the last third place in the Fugu orchestrator, which is designed for safety considerations. Sakana introduced that orchestra about a month ago. Sakana reports … Read more

Meet Open Dreamer: JAX/Flax Reproduction of the Dreamer 4 World Model Pipeline, with Full Training Recipe Published

Meet Open Dreamer: JAX/Flax Reproduction of the Dreamer 4 World Model Pipeline, with Full Training Recipe Published

A small group of AI researchers (Reactor) released Open Dreamer, an open source implementation of the Dreamer 4 world model pipeline written in JAX and Flax NNX. What exactly was sent Two caches were released. next-state/open- dreamer manages the training pipeline: causal video token, action-conditioned latent dynamics model, output generation, and FVD goal. reactor-team/open-dreator runs … Read more

Designing High-Performance GPU Kernels with TileLang: Tensor-Core GEMM, Fused Softmax, FlashAttention, and Autotuning

Designing High-Performance GPU Kernels with TileLang: Tensor-Core GEMM, Fused Softmax, FlashAttention, and Autotuning

@tilelang.jit(out_idx=[-1]) def make_matmul(M: int, N: int, K: int, block_M: int = 128, block_N: int = 128, block_K: int = 32, num_stages: int = 3, threads: int = 128, use_swizzle: bool = False, dtype: str = “float16”, accum_dtype: str = “float”): @T.prim_func def main(A: T.Tensor((M, K), dtype), B: T.Tensor((K, N), dtype), C: T.Tensor((M, N), dtype)): with … Read more