'optimize' 검색 결과

Review nine parts of a LinkedIn profile and get prioritized fixes with before-and-after rewrites. Tailor headlines, About sections, work experience, and featured content to attracting clients, finding a job, or establishing professional expertise.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Auditing a LinkedIn profile before starting a content strategy
• Rewriting a headline and About section
• Choosing featured content for client outreach or job seeking

Turn a recurring workflow into an agent skill, or improve an existing one. Draft instructions, compare test outputs against a baseline, review quality and resource usage, and refine the description that determines when the skill is invoked.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turning a recurring workflow into a new skill
• Improving an existing skill using test feedback
• Comparing skill quality, execution time, and token usage

Create resumes, reports, papers, and other documents with LaTeX, a document typesetting system, then produce PDFs and page previews. Also convert document formats and handle PDF tasks such as merging files and filling forms.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating reports and papers with charts and citations
• Preparing resumes and cover letters
• Converting handwritten PDFs into LaTeX

Turn a detailed outline into a philosophy or interdisciplinary manuscript. Draft chapters with repeated quality reviews, check terminology and arguments across sections, and prepare the manuscript, evaluation reports, abstract, and metadata for submission.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Draft a full paper from a detailed outline
• Review argument and citation quality chapter by chapter
• Check terminology and argument flow across chapters

Plan philosophy and interdisciplinary papers by comparing preprint platforms, searching literature, identifying unanswered questions, and assessing originality. Receive a detailed outline with section word counts, key citations, and improvements based on a reviewer-style assessment.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning a philosophy or interdisciplinary paper
• Choosing a suitable preprint platform
• Finding research gaps and assessing originality

Turn plain-language questions into SQL for SQLite and PostgreSQL using database structure as context. Review queries against 13 optimization rules and interpret execution plans, which show how the database retrieves data, to investigate slow queries.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turning plain-language questions into SQL
• Investigating slow queries
• Checking index usage

Deploy code changes to a live hero training run by starting a new run from a permanent checkpoint, a saved training state. Compare matching training steps against agreed criteria and roll back if the trial fails.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Deploy backend or optimizer changes to a live training run
• Compare loss and throughput across matching training steps
• Rehearse checkpoint handoff and rollback procedures

Audit and rewrite content to help it become a cited source in AI search answers. Develop strategies for ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews, focusing on how these services use content in generated responses.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Auditing existing content for AI search visibility
• Rewriting articles to support citation in AI answers
• Planning content improvements for each AI search service

Implement filtering, aggregation, joins, and file processing with Polars for tabular data that fits in memory. Use lazy evaluation, which optimizes operations before running them, and parallel execution to improve pipelines and migrate pandas code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Migrate slow pandas processing to Polars
• Filter and aggregate CSV or Parquet data
• Join multiple tables and reshape results

Apply NOWAIT to shorten reasoning model outputs by suppressing reflection words during generation. Includes integration examples for HuggingFace Transformers and vLLM, with guidance on model suitability and potential accuracy loss in distilled models.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reducing tokens used in lengthy reasoning
• Introducing NOWAIT into model inference
• Checking model suitability and accuracy risks

Support experimental validation of designed proteins through a cloud laboratory. Prepare and optimize sequences, submit tests for binding, expression, thermal stability, or enzyme activity, track experiment progress, and retrieve results through the API.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Submit designed proteins for binding tests
• Request expression, thermal stability, or enzyme activity tests
• Optimize sequences for solubility before experiments

Optimize stock allocations from price data using NVIDIA cuOpt, with controls for severe losses or overall variability. Compare risk and return, inspect allocation tables, backtest against benchmarks, and evaluate scheduled or drift-triggered rebalancing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Calculate allocations under risk and asset weight limits
• Compare allocations across risk preferences
• Backtest an allocation against an equal-weight portfolio

Diagnose slow loading, high memory use, and low frame rates in USD 3D scenes. It coordinates measurement, scene validation, and optimization, then produces reports comparing available before-and-after evidence and an optimized scene when changes are performed.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate slow loading in USD scenes
• Diagnose low frame rates and high memory use
• Review repeated structures in large CAD scenes

Helps tune activation recomputation in Megatron Bridge, recalculating intermediate training values to reduce GPU memory use. Guides selective or full-layer settings, checks compatibility, and compares memory peaks with training speed to assess whether a configuration completes training steps.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate training failures caused by activation memory
• Choose recomputation targets for attention or MoE models
• Compare GPU memory savings against training speed

Generate small-molecule candidates from a starting structure, optimize supported molecular properties, and save results for validation. Local deployment also supports embeddings, numerical representations of molecules, and workflows that convert between molecular structures and learned internal representations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Generate molecular candidates around a seed structure
• Optimize candidates for QED or plogP
• Obtain molecular embeddings with a local deployment

Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Optimize existing Azure resources and analyze Reservations or Savings Plans. WHEN: "optimize Azure costs", "reduce cloud spending", "rightsize resources", "find idle resources", "orphaned disk", "deleted VM still charged", "public IP still charging", "reservation utilization", "Savings Plan coverage", "commitment recommendation", "why is pay-as-you-go still charged". DO NOT USE FOR: cost spikes, forecasts, pricing estimates, budgets, or governance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when the user asks to "allocate my influencer budget", "optimize spend across tiers", or "compare budget scenarios"; produces a tier/platform/content allocation table, ROI and CPM/CPE projections, scenario comparisons, and mid-campaign reallocation moves. Not for building the full campaign plan — use campaign-planner. 达人预算分配/投放预算优化

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when the user asks to "optimize for AI citations"; improves citation readiness for ChatGPT, Perplexity, AI Overviews, Gemini, and Claude. Not for structural on-page SEO — use on-page-seo-checker; not for net-new drafting — use content-writer. AI引用优化/GEO优化/AI搜索

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when the user asks to "plan my paid account structure", "pick Search vs PMax", "lay out ad groups / asset groups", or "audit paid-vs-organic cannibalization"; designs campaign-type selection, ad-group/asset-group layout, targeting + match types, negative/exclusion hygiene, and a paid↔organic overlap audit, and scores the ROAS A (Audience) dimension + structure. Not for computing the final RQS — use ad-account-auditor; not for budget split — use budget-optimizer; not for organic site architecture — use site-structure-optimizer. 付费广告账户结构/广告系列规划/否定关键词

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when the user asks to "optimize my Shopping feed", "fix product disapprovals", "improve product titles/attributes", or "build feed-driven PMax asset groups"; audits and rewrites the Shopping/Performance Max product feed — title/description patterns, required and recommended attributes, GTIN/availability/price hygiene, disapproval triage, and feed-driven asset-group / listing-group structure — informing the ROAS O (Offer) dimension. Not for text ad copy — use ad-creative-builder; not for scoring the account or the RQS — use ad-account-auditor. 商品Feed优化/购物广告Feed/商品标题优化/商品禁投修复

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when the user asks to "optimize entity presence", reconcile an entity identity, or update canonical Knowledge Graph facts; audits and maintains machine-facing identity, sameAs, schema, disambiguation, and AI-recognition evidence through the entities registry. Not for page-level AI-citation readiness - use geo-content-optimizer; not for human-facing brand canon - use narrative-registry. 实体注册/知识图谱

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when the user asks to "optimize our landing page for influencer traffic", "fix our promo-code landing page", or "improve conversion from a creator campaign"; produces a message-match audit, page-structure and social-proof recommendations, a promo-code/CTA conversion plan, and an A/B test roadmap. Not for measuring campaign results after launch — use performance-analyzer. 落地页优化/达人流量转化提升

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.