PyTorch Day Korea 2026! 올해 슬로건과 일자를 공개합니다!
🌟 “Torch YAHO!” 🌟
2026.10.31 - 센터필드 이스트 18층 AWS 코리아 교육장
PyTorch를 사용하는 연구자, 엔지니어, 개발자들이 모여
모델 개발부터 최적화, 서빙, AI Application까지 이어지는 다양한 경험을 함께 나눕니다.
(1/3)
좋은 연구주제 잡는 법:
0. 우선 연구 목적을 명확히 한다. 논문만 나가면 되는지 (이때 어느 레벨로 논문이 나가야하는지), 공부만 하면 되는지, 자기만족인지, 진짜 연구인지 순으로 나뉜다.
순서가 이상해보일 수 있지만, 이 순서가 맞다는 게 (핵심1)이다.
우선 방법 1번부터 타래에 이어 씀.
AI agents without guardrails aren't powerful, but they're risky.
9 layers every team needs before going to production...
AI agents are only as reliable as the guardrails behind them.
This is no longer optional; it's the difference between scaling safely or failing fast.
Here are the essential guardrails every AI agent needs today:
1/ Content Filtering: Input + Output
Stops harmful, sensitive, or non-compliant data before it enters or leaves your system.
2/ Input Validation: Query Stage
Prevents prompt injection, enforces schema rules, and ensures structured inputs reach the agent clean.
3/ Intent Recognition
Understands what the user actually wants, critical for correct tool routing and planning decisions.
4/ Rule-Based Checks: Pre-Processing
Lightweight filters (regex, limits, constraints) that catch edge cases before reasoning even starts.
5/ Hallucination Detection: SLMs + Evaluators
Flags low-confidence or fabricated outputs before they ever reach a user.
6/ Safety Classification: Specialized Models
Classifies queries in real-time to block unsafe or restricted actions at the gate.
7/ Moderation Layers: APIs + Internal Models
Adds redundancy across input and output because one layer is never enough in production.
8/ Output + Format Validation
Ensures responses are usable (JSON, SQL, API-ready) and won't break downstream systems.
9/ Sensitive Data Detection: PII + Secrets
Prevents leakage during both retrieval and generation. Non-negotiable for any enterprise RAG pipeline.
📌 What's shifted from 2025 to 2026:
* Guardrails are now multi-layered systems, not single filters
* Real-time evaluators and agent monitoring frameworks are standard
* Policy-aware agents with compliance baked into logic, not bolted on
* SLMs handling safety tasks faster, cheaper, purpose-built
* "Defense-in-depth" is the architecture pattern enterprises are adopting
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