'optimization' 검색 결과

Design and build backend services with API scaffolding, database migrations, authentication reviews, and load testing. Generate route handlers from OpenAPI specifications, identify PostgreSQL optimization opportunities, and compare architecture choices against traffic, data sensitivity, and reliability requirements.

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• Generating API route handlers from OpenAPI
• Investigating slow PostgreSQL queries
• Reviewing authentication and input validation

Guides migration of existing codebases to Rust without unsafe code, covering architecture, implementation, testing, and output comparisons. It measures performance before and after optimization and produces an interactive HTML report documenting results and unresolved differences.

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• Migrating a GitHub or local codebase to Rust
• Comparing original and migrated program outputs
• Measuring and optimizing a Rust port

Assess Google Cloud workloads for environmental sustainability using the Well-Architected Framework. Get recommendations on lower-carbon regions, efficient computing and storage, AI energy use, and ongoing emissions measurement with Carbon Footprint.

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• Reviewing cloud architecture for environmental impact
• Comparing deployment regions by carbon-free energy use
• Reducing energy waste in AI and computing workloads

Investigate failing or slow BigQuery jobs and unexpected cost increases. Compare execution details and resource usage with a normal baseline to isolate bottlenecks, identify likely causes, and determine practical remediation steps.

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• Investigate failed or slow BigQuery jobs
• Locate bottlenecks in execution stages
• Diagnose sudden increases in query or capacity costs

Plan how an AI agent uses limited input space through reusable prompt prefixes, shorter tool outputs, summaries, and task splitting. Measure token use, response quality, and latency to choose optimizations that provide a net benefit.

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• Reducing token use from lengthy tool outputs
• Improving prompt cache reuse
• Planning context budgets for long conversations

Learn how instructions, documents, tool results, and conversation history form an AI model’s context. Understand attention limits, why information in the middle can be missed, and how relevance and placement inform decisions about what to include.

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• Learning the basics of context engineering
• Understanding why more input does not always help
• Explaining how instruction placement affects attention

Analyze ARIS usage logs to propose evidence-based changes to skill instructions, reviewer prompts, and workflow defaults. Receive a report and focused patch proposals, with selected patches staged for a separate application process.

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• Investigate recurring workflow failures
• Review defaults that users frequently override
• Identify the current workflow bottleneck

Guide language model training with SimPO using pairs of preferred and rejected answers. Covers configuration, learning rate tuning, and memory troubleshooting for preference alignment, which adjusts model responses toward human preferences without a separate reference model.

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• Training on preferred and rejected answer pairs
• Exploring an alternative to DPO without a reference model
• Tuning preference training for math and code tasks

Compress large language model weights to four bits with AWQ, a method that uses model activation patterns to limit quality loss. Follow workflows for quantization, loading compressed models, and serving them with vLLM using less GPU memory.

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• Running large language models with limited GPU memory
• Quantizing a model with domain-specific text
• Serving an AWQ model with vLLM

Helps reduce GPU memory use by loading large language models in 4-bit or 8-bit formats, a technique called quantization. Covers bitsandbytes configuration, memory checks, QLoRA fine-tuning, and training with memory-saving optimizers.

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• Load a larger model within available GPU memory
• Compare 4-bit and 8-bit quantization settings
• Fine-tune a quantized model with QLoRA

Configure machine learning training and batch jobs across multiple clouds with SkyPilot. The skill guides GPU selection, lower-cost cloud and region choices, and automatic recovery when discounted spot instances are interrupted.

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• Choose a lower-cost cloud for GPU training
• Run long training jobs with recovery after interruptions
• Configure distributed training across multiple machines

Compress large language models to 4-bit weights to reduce GPU memory needs and accelerate text generation. Covers loading compressed models, converting your own models, choosing settings, and preparing memory-efficient fine-tuning with transformers and PEFT.

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• Run language models with limited GPU memory
• Convert your own model to 4-bit weights
• Compare compression settings for quality and speed

Design cloud architectures and migration plans for AWS, Azure, and GCP. Produce service diagrams, selection rationale, security designs, cost estimates, and recovery strategies, with deployment and rollback plans that account for availability and operational monitoring.

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• Design a cloud architecture and explain service choices
• Plan a cloud migration and cutover checks
• Review cloud spending and resource sizes

Develop microcontroller firmware for STM32 or ESP32, including peripheral drivers and FreeRTOS tasks. The skill guides interrupt handling, memory and power optimization, and checks that time-sensitive operations meet their deadlines.

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• Implementing peripheral control on STM32 or ESP32
• Designing periodic tasks and synchronization with FreeRTOS
• Reducing firmware memory use and power consumption

Write and refactor C++20/23 applications, addressing memory management, concurrency, and performance bottlenecks. Produce interfaces, implementations, tests, and relevant CMake updates, then check runtime errors and measure performance before applying targeted optimizations.

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• Refactoring existing code with C++20/23 features
• Investigating memory errors and undefined behavior
• Improving performance through profiling and benchmarks

Diagnose paid advertising performance using account evidence, financial constraints, and experiments. Draft ranked changes to budgets, bids, or ad delivery, and apply supported operations only after approval and state checks, retaining a way to reverse them.

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• Reviewing budget allocation and bids
• Planning ad pauses and creative rotation
• Assessing search terms before adding negative keywords

Audit paid-ad landing pages for message consistency, mobile usability, accessibility, performance, forms, consent, tracking, and destination safety. Get evidence-based findings and recommendations ready for experiments to address obstacles to completing the intended action.

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• Checking consistency between ads and landing pages
• Reviewing mobile layouts and accessibility
• Finding form friction and error-state issues

Audit C/C++ and Rust code for secrets left in memory. It checks missing or incomplete wipes, examines compiler output for removed cleanup operations, and produces reports with evidence and suggested fixes.

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• Auditing cryptographic key cleanup
• Checking password and token memory wipes
• Investigating cleanup removed by compiler optimization

Screen an existing compound library against a protein target with Boltz. Rank candidates by binding confidence or lead optimization score, download predicted structures, and review solubility, permeability, and lipophilicity results alongside the ranked hits.

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• Screening an existing compound library against a protein
• Finding candidates with high binding confidence
• Comparing candidates for lead optimization

Apply Vercel Engineering’s performance guidelines when writing, reviewing, or refactoring React and Next.js code. Prioritize improvements to data fetching, downloaded code size, server processing, and unnecessary rendering using rules with explanations and code examples.

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• Review React components for performance issues
• Improve data fetching in Next.js pages
• Reduce downloaded code and loading time

Create, audit, and improve pages for AI search engines by checking crawl access, metadata, clear answers, sources, and structured data that describes page content. It produces prioritized fixes and citation-friendly pages without guaranteeing inclusion in AI answers.

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• Audit a blog for AI search visibility
• Create an article page with clear answers and supporting sources
• Fix metadata and structured data on existing pages

Improve how search engines discover and understand a website by reviewing titles, descriptions, links, and sitemaps. Add structured data, machine-readable descriptions of page content, and use checklists to identify technical and on-page SEO issues.

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• Review page titles and meta descriptions
• Check crawl settings and sitemaps
• Add structured data to articles or product pages

Write, review, and refactor React and Next.js code using performance guidelines from Vercel Engineering. Prioritize improvements to data fetching, downloaded code size, server processing, and unnecessary rendering, with rule files providing explanations and code examples.

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• Reviewing React code for performance issues
• Reducing delays in Next.js data fetching
• Reducing downloaded code size and load times

Improve website loading and responsiveness by optimizing images, fonts, scripts, and caching. Identify priorities, reduce JavaScript download size, split code into smaller loads, and verify changes through a structured performance improvement workflow.

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• Improving slow page loading
• Reducing JavaScript download size
• Reviewing image and font loading