… The deep research agent uses the create deep agent factory from LangChain’s deepagents library. from deepagents import create deep agent return create deep agent model=self.llm provider.get LLMRole.ORCHESTRATOR , system prompt=orchestrator prompt, tools=self.tools, subagents=self.subagents, middlew… …
… They’re powerful but missing core security primitives: sandboxing, permissions, and isolation. For long-running, self-evolving agents to actually work, you need three things simultaneously: safety, capability, and autonomy. …
… Teams can add a reusable deep research capability to their agent harnesses today. Get started by: Spinning up the server: Head over to the AI-Q GitHub repository for quick-start deployment instructions using Docker Compose or Helm. …
… The self. solve poisson method in the example code abstracts away the \ \omega t+\Delta t \xrightarrow{\text{FFT}} \hat{\omega} \xrightarrow{\text{Eq.\,3}} \hat{\psi} \xrightarrow{\text{IFFT}} \psi t+\Delta t \ pipeline for modularity. def step self - None: """Advance simulation by one timestep usi… …
… This enables quantitative researchers to iterate at high velocity—adjusting the forward-returns period or tightening the IC requirements—simply by editing a YAML file. llms: signal generator: type: nim model name: nvidia/nemotron-3-nano-30b-a3b base url: "https://integrate.api.nvidia.com/v1/" tempe… …
Agentic AI / Generative AI MiniMax M2.7 Advances Scalable Agentic Workflows on NVIDIA Platforms for Complex AI Applications Apr 11, 2026 By Anu Srivastava and Shruti Koparkar Discuss 0 Discuss 0 L T F R E The release of MiniMax M2.7 adds enhancements to the popular MiniMax M2.5 model, built for age… …
… NVIDIA is addressing this gap through its BESS Self-Qualification Guidelines, giving vendors a structured way to demonstrate product capabilities against AI-factory-specific requirements, and giving data center developers a basis for adopting them with confidence. …
… That matters because long context is becoming a core requirement for agentic applications. Agents store more than a single prompt and response. They carry system instructions, tool outputs, retrieved context, code, logs, memory, and multi-step reasoning traces across a workflow. …
… Beyond basic syntax differences, the translation must handle loop structure, TF32 tensor core conversion, and the shift from row-major to column-major layout. cuTile Python: @ct.kernel def matmul kernel A, B, C, tm: ct.Constant int , tn: ct.Constant int , tk: ct.Constant int : bid m = ct.bid 0 bid … …
… Since launch: 13 releases, 400+ commits, and external contributions from engineers across NVIDIA partner companies. Key additions include GPU reset, Kubernetes object monitor, event exporter, preflight checks, Slinky drain support, and GB200/GB300 support. …