Nscale IPO: Nvidia 지원 네오클라우드의 상장 준비가 의미하는 것
Introduction TL;DR Nscale IPO는 상장 확정이 아니라 Goldman Sachs와 JPMorgan을 고용해 IPO를 준비 중이라는 의미이며, 일정은 미정입니다. 이 글에서는 “네오클라우드” 모델을 정의하고, 실제로 확인된 사실과 IPO 헤드라인을 실무 리스크 체크리스트로 정리합니다. 1) Definition: What is a “Neocloud”? One-sentence definition **네오클라우드(Neocloud)**는 범용 하이퍼스케일러가 아닌 GPU 중심 AI 훈련/추론에 특화된 클라우드 제공업체입니다. Scope (what it is / isn’t) Is: GPU 용량 + 데이터센터 운영을 AI 컴퓨팅 인프라로 판매 Isn’t: 모델 IP가 핵심 가치인 “AI 모델 회사” Common misconception “Nvidia-backed” ≠ “Nvidia 자회사”. 이는 보통 투자/파트너십/생태계 연계를 의미하며, 지배권을 뜻하지 않습니다. ...
SpaceX xAI 합병: 1.25조 달러 딜과 궤도 데이터센터 팩트체크
Introduction TL;DR SpaceX xAI 합병이 2026-02-02에 발표되었으며, 보도에 따르면 SpaceX(1조 달러) + xAI(2,500억 달러) 합산 가치평가가 언급됩니다. SpaceX의 태양광 기반 궤도 데이터센터 추진(FCC 제출)이 로켓/위성/AI 컴퓨팅을 연결하는 핵심 서사입니다. Grok 관련 규제 조사가 현재 진행 중이며, 영국 ICO가 2026-02-03에 X와 xAI에 대한 공식 조사를 개시했습니다. Context SpaceX xAI 합병은 “단순한 AI 인수"가 아닙니다. 이 거래는 AI 경쟁을 지상과 궤도를 아우르는 인프라 경쟁으로 재정의하면서, 동시에 거버넌스와 컴플라이언스 리스크를 증폭시킵니다. Why it matters: 이것은 제품 출시 뉴스가 아니라 실제 규제 노출이 있는 공급망(데이터 - 모델 - 컴퓨팅 - 배포) 이야기입니다. ...
vibe coding과 ADHD: 생산성 올리고 사고 줄이는 운영법
vibe coding과 ADHD: 생산성 올리고 사고 줄이는 운영법 Introduction TL;DR: Vibe coding means letting an AI generate code without deeply caring about what it produced. That can feel frictionless—especially if you struggle with planning and organization—but it can also amplify risk unless you add structure. In this post, vibe coding is treated as a prototype-first technique, and the goal is a production-safe operating model using gates, small diffs, and accountability. Prerequisites Definitions, scope, and one common misconception Vibe coding (1 sentence): Telling an AI what you want and letting it generate the product, often without fully understanding the code. Not the same as AI-assisted programming: If you review, test, and understand the output, many practitioners argue that is not vibe coding. ADHD (1 sentence): A neurodevelopmental disorder with persistent patterns of inattention and/or hyperactivity-impulsivity affecting functioning. Misconception: “AI always makes developers faster.” A randomized trial with experienced OSS devs found AI use took longer in that setting. Why it matters: You can’t run safe operations if your team mixes “prototype vibes” with “production responsibility.” ...
vibe coding과 ADHD: 속도와 검증의 균형—실무 가드레일
Introduction TL;DR: vibe coding은 자연어로 “빠르게 만들고 돌리는” 방식이라 쓰기보다 검증에 부담이 쏠립니다. ADHD는 “집중력 문제”만이 아니라 성인에서 집행 기능(계획·조직화·시간관리) 부담으로 나타납니다. “Accept All”에 의존하면 특히 보안 리스크가 커지므로 테스트·리뷰·스캔 같은 하드 게이트가 필요합니다. (karpathy) What vibe coding is vibe coding is a workflow where you describe intent in plain language and iterate based on run results, often with minimal code reading. (X) Why it matters: speed without verification becomes “verification debt,” which is worse than normal tech debt. (NIST SP 800-218) ...
Gartner AI 지출 2.52조 달러 전망: 인프라 과반 시대의 예산·운영 가이드
Introduction TL;DR: Gartner는 2026년 전 세계 AI 지출을 **2.52조 달러(+44% YoY)**로 전망했으며, 인프라가 절반 이상을 차지합니다. 이 글은 Gartner의 “AI 지출” 정의, 인프라 비중이 큰 이유, 예산·거버넌스·아키텍처에서의 실무 대응을 정리합니다. Why it matters: AI를 작은 “프로젝트 예산”으로 보면, 실제 지출이 몰리는 인프라·서비스·내장형 소프트웨어 비용을 놓치기 쉽습니다. What Gartner means by “AI spending” Gartner 보도자료는 AI 지출을 8개 시장(서비스, 사이버보안, 소프트웨어, 모델, DS/ML 플랫폼, 앱 개발 플랫폼, 데이터, 인프라)의 합으로 정의합니다. ...
OpenClaw 보안 이슈 정리: Moltbook 노출·악성 스킬·안전 운영 체크리스트
Introduction TL;DR: OpenClaw is an open-source AI agent designed to run on a personal machine and execute real actions via chat-based commands. Reported incidents around Moltbook key exposure, malicious “skills,” and a published advisory show that agentic utility and agentic risk scale together. Use sandboxing, least privilege, secret hygiene, and tight input/tool controls before you grant it real accounts. Why it matters: “Agents” aren’t just chat—they’re delegated execution. Delegated execution without governance is a security incident waiting to happen. ...
DeepSeek H200 조건부 승인: 미국 수출허가와 중국 수입승인의 이중 관문 실무 가이드
Introduction TL;DR: Reuters reported on 2026-01-30 that DeepSeek received conditional approval from Chinese regulators to purchase Nvidia’s H200 chips, with conditions still being finalized. This does not automatically mean shipments are imminent. The same Reuters reporting highlights that approvals can be restrictive enough that buyers don’t convert them into actual purchase orders. The practical takeaway: treat DeepSeek H200 as a “two-gate” problem—US export licensing and China import/use approvals are separate gates that can each block execution. Why it matters: In regulated supply chains, headlines move sentiment, but conditions and documentation move shipments. ...
AI training data governance checklist: opt-out, purpose limitation, retention
Introduction TL;DR: This AI training data governance checklist turns opt-out, purpose limitation, and retention into enforceable controls across raw data, derived assets, and training snapshots. It focuses on audit-ready evidence: logs, lineage, and automated enforcement (TTL/deletion jobs). Why it matters: Governance that cannot be evidenced (logs + automation) typically fails during audits and incident response. Definition and scope One-sentence definition An AI training data governance checklist is a structured set of controls to ensure training data is used only for explicit purposes, retained only as long as necessary, and subject rights (including opt-out) are operationally enforceable and auditable. ...
LLM data lineage design: dataset manifest and reproducibility
Introduction LLM data lineage is the practice of proving which exact dataset snapshot (and transformations) produced a specific model artifact, with run metadata that makes the training reproducible. PROV provides a standard conceptual model for provenance (entities, activities, and agents). Why it matters: When incidents happen, you need evidence—not guesses—about what data and code produced the deployed model. Core building blocks Dataset manifest (the “snapshot contract”) A manifest should lock: ...
Nvidia OpenAI investment: what 'on ice' means and why Huang still says a 'huge' check is coming
Introduction TL;DR The 2025-09-22 announcement was a 10GW compute LOI with an “up to $100B” progressive investment framing. On 2026-01-31, reporting said the megadeal is “on ice,” while Jensen Huang publicly said Nvidia will still invest “a huge” amount—but “nothing like” $100B. The real question is deal structure (compute deployment + leasing + equity) and execution milestones (when 1GW actually goes live). Nvidia OpenAI investment is being reinterpreted in real time: a 10GW infrastructure LOI announced on 2025-09-22, followed by 2026-01-31 reports of a stalled “$100B” plan and Huang’s pushback that a “huge” investment is still planned. ...