Results for “irm”

Irr reference tool. Use when working with irr in finance contexts.

Expert Australian Information Security Manual (ISM) advisor for government entities and their supply chains. Use for ISM control selection, gap analysis, system authorisation, IRAP assessment preparation, security documentation, and ASD compliance. Triggers on: ISM controls, ASD compliance, IRAP assessment, PROTECTED system scoping, Essential Eight vs ISM, system authorisation, NC/OS/ PROTECTED/SECRET/TOP SECRET classification markings, security objectives, ISM guidelines or chapters, control applicability markings, cybersecurity documentation for Australian government, and any question about the ASD Information Security Manual framework or Australian government cybersecurity obligations.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Instaura/atua em IRDR — Incidente de Resolucao de Demandas Repetitivas (CPC 976, requisitos simultaneos: I efetiva repeticao sobre questao unicamente de direito + II risco a isonomia/seguranca; legitimados 977; admissibilidade 981; suspensao no Estado/regiao 982 I; tese aplicada a todos e aos casos futuros 985; revisao 986; REsp/RE 987) ou IAC — Incidente de Assuncao de Competencia (CPC 947, questao relevante de grande repercussao social SEM repeticao; acordao vinculante §3), com efeito vinculante da tese (CPC 927 III). Use quando o operador disser IRDR, incidente de resolucao de demandas repetitivas, IAC, assuncao de competencia, tese vinculante regional, muitos processos iguais, suspensao por IRDR.

Guides through the complete ISO/IEC 27001:2022 ISMS lifecycle from scoping and risk assessment to certification and continual improvement, including Annex A control selection and Statement of Applicability creation.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Designing and evaluating AI/ML systems: prompt engineering, RAG design, LLM application patterns, AI safety, evaluation frameworks, MLOps, cost optimization. Use for AI pipelines or eval harnesses.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Implements production LLM operations: RAG pipelines, embeddings, vector databases, fine-tuning, advanced prompt engineering, cost estimation, quality evals, semantic caching, streaming, and agents.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Use when auditing an ACM IMC submission for HotCRP readiness, covering the paper-registration step, the acmart template with BBL upload, the full/short page limits, double-blind anonymity including vantage-point details, the mandatory Ethics section, the artifact-availability declaration, cycle choice, and desk-reject triage before the AoE cutoff.

Drafts an Irrevocable Life Insurance Trust (ILIT) compliant with IRC § 2042 and state trust laws to exclude life insurance from the grantor's taxable estate. Covers Crummey withdrawal rights, trustee powers, distributions, and execution formalities. Use when drafting ILITs, life insurance trusts, estate tax exclusion trusts, or Crummey trusts.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Drafts U.S. internal legal memoranda using IRAC structure to analyze issues, synthesize authority, assess risks, and recommend strategy. Use when asked to draft a research memo, internal memo, issue analysis, case strategy memo, or any IRAC-based legal analysis.

Generates synthetic body MRI volumes using NVIDIA's NV-Generate-CTMR rflow-mr model. Wraps the upstream diffusion inference pipeline with config staging, output validation, and NIfTI volume summarization.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Provides guidance on production AI operations including RAG pipelines, vector databases, embeddings, fine-tuning, prompt engineering, cost estimation, and quality evaluation.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Guides production LLM operations: RAG pipelines, embeddings, vector databases, fine-tuning, prompt engineering, cost estimation, quality evals, and AI architectures.

Designs and automates identity governance lifecycle processes including joiner-mover-leaver workflows, role mining, access requests, periodic recertification, and orphaned account remediation using IGA platforms.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Retrieve, analyze, and update Jira tickets directly from your AI coding workflow using MCP or REST API.

Executes Python code iteratively via an MCP bridge to produce verified results for calculations, data analysis, and task decomposition.

LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.

Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.

通用跨模型审查：Review LLM 对任意研究制品进行独立评审，输出结构化评分、wiki 实体映射与改进建议

Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.

Builds input and output validation guardrails for LLM-powered applications to prevent prompt injection, data leakage, toxic content generation, and hallucinated outputs using NeMo Guardrails, Presidio, and Guardrails AI.

Use when planning an IROS project timeline from venue fit through the spring paper deadline, the separate video deadline, the summer review silence, the June notification, the July camera-ready, IEEE Xplore publication, registration, and presentation, with backward-planning offsets for a real-robot paper on the fall IEEE/RSJ calendar.

Run NVIDIA garak probe suites against an LLM endpoint to test for jailbreaks, prompt injection, data leakage, and toxic generation, then interpret the hit-rate report for triage and reporting.

Conduct authorized security assessments of LLM applications and AI agents, covering prompt injection, tool abuse, RAG exposure, memory poisoning, and model supply-chain risks.

Executes Python code iteratively via an MCP bridge to produce verified results for calculations, data analysis, and task decomposition.