IREN, 비트코인 채굴에서 MS 13조 계약사로 — $50 돌파 운명의 일주일

IREN, 비트코인 채굴에서 MS 13조 계약사로 — $50 돌파 운명의 일주일 IREN, 비트코인 채굴에서 MS 13조 계약사로 — $50 돌파 운명의 일주일 필자가 키움증권 상위 랭킹에서 우연히 발견한 종목, IREN(아이리스 에너지) 입니다. "왜 이 종목이 갑자기 위에 떠 있지?" 궁금해서 차트를 열었더니, 긴 하락 채널 상단에 정확히 맞닿아 있는 자리 였어요. 이번 주 안에 거래량 동반 돌파가 나오면 단숨에 $59~$62까지 슈팅, 실패하면 채널 안으로 회귀해 $45 일목 구름까지 밀릴 수 있는 구간. 그런데 차트 너머로 더 흥미로운 게 보입니다 — 마이크로소프트와 약 13조 6천억원($9.7B) AI 인프라 계약 을 체결한 회사라는 사실이에요. 📌 키움증권 상위 랭킹에서 발견 — "왜 이 종목이?" 안녕하세요, 30대 진도리에 취미생활 의 미니도리몽입니다. 📋 필자 발견 경로 + 현재 포지션 · "자리 괜찮은 종목 좀 골라보자"하고 키움증권 상위 랭킹 살피던 중 IREN 발견 · 차트 열어보니 $50 부근, 하락 채널 상단 에 정확히 도달 · 현재 미보유 , 차트 돌파 여부 확인 후 본주 분할매수 검토 중 국내 투자자분들도 비슷한 경험 있으실 거예요. 증권앱 상위 랭킹에 갑자기 올라온 종목, 무심코 넘기기보단 한번 들여다봅시다. 상위 랭킹에 뜨는 데는 보통 거래량·등락률·유입자금 같은 시그널 이 있거든요. 이번 글의 흐름은 다음과 같습니다. ① 빅테크 AI 투자비 812조원의 진짜 종착지 — 왜 NVDA가 아니라 IREN 같은 데이터센터 운영사인가 ② 마이크로소프트 약 13조원 계약 — 변신의 결정적 증거 ③...

AMD vs NVIDIA 2025: AI Semiconductor War, Custom Chip Era & Big Tech Strategies

📌 Top 3 Takeaways

  • AMD is rising as a contender in AI/data center GPUs but still falls short of being a true NVIDIA alternative, due to ROCm ecosystem limitations and lack of large-scale production references.
  • Big Tech (Google, Amazon, Meta, etc.) is doubling down on custom AI chip development, aiming to reduce dependency on NVIDIA and AMD, rather than just seeking price competitiveness.
  • AMD stock rebounded on NVIDIA FOMO and valuation fatigue, but investors should remain cautious about fundamentals, ecosystem maturity, and institutional flows.
📌 AI Use Notice
This post uses ChatGPT’s summarization and public data as a base, with the author's analysis and views incorporated.
Graphs and scores are based on publicly available sources and reflect subjective analysis, **not investment advice**. All insights from AI are for reference only, and investment decisions remain solely with the reader.

📌 Beyond the Hype: Is AMD Really the Next NVIDIA – Or Just a Transitional Play?


🧾 Author’s Perspective

NVIDIA is testing all-time highs again—too late to get in?
So who’s next in the AI hardware race? Some say “NVIDIA’s peaked, time to buy AMD.”
But whenever tech progress hits a ceiling, fast-moving followers with value pricing can shake up the market.
Is this AMD’s big moment, or is NVIDIA’s dominance only getting stronger?
Now’s the time to break it down.


📌 Executive Summary

AMD is in the spotlight as a latecomer to the GPU/AI chip game. Yet global tech giants are moving away from price wars—opting instead for custom AI chip development. This piece breaks down AMD’s strengths and weaknesses, and what’s really happening in the field.


🔍 1️⃣ Why AMD Is Gaining Traction

  • Pricing Power: MI300X offers over 50% savings versus NVIDIA H100, with comparable memory specs.
  • Energy Efficiency: Lower power draw per computation—good for large-scale servers.
  • Integrated Architecture: Expertise combining CPU (EPYC) and GPU (MI series) for optimized performance.
  • ROCm Ecosystem: An open alternative for firms wanting to break free from CUDA lock-in.
  • Faster Delivery: More flexible GPU supply, a plus during global chip shortages.

🧩 To simplify:

  • 💰 AMD is like buying a Tesla Model 3 over a Rolls-Royce: enough speed, way less cost.
  • 🧠 If NVIDIA is a supercar built for the racetrack, AMD is a practical hybrid for every road.
  • 🧳 Same data load, but AMD offers a bigger “trunk” (HBM3 memory).
  • 🔌 Lower power, easier setup—less ongoing expense for enterprises.

📉 2️⃣ AMD's Drawbacks and Weaknesses

  • Weak CUDA Compatibility: Most AI models are still designed around NVIDIA.
  • Poor software tool adoption: Limited developer/researcher uptake.
  • Lack of real-world benchmarks: Not enough proven success in massive AI training.
  • NVIDIA’s tech speed: Blackwell, NVSwitch, Grace Hopper—next-gen innovation remains in NVIDIA’s camp.

🧭 3️⃣ The Market Is Betting on In-House Chips, Not Just AMD

Many investors look at AMD as a cheaper NVIDIA, but global tech titans are charting a different path.
Instead of just switching vendors, they’re designing their own AI chips to escape dependence.
This trend suggests custom ecosystem building, not simply slotting in AMD, is the deeper play.

📦 Companies Leading the Shift

Company Custom Chip Strategy
Google TPU (Tensor Processing Unit) Launched up to v5; in-house & partially public
Amazon (AWS) Trainium, Inferentia Used for cost-effective AI inference
Meta (Facebook) MTIA AI training chip; independence from suppliers
Microsoft Azure Maia 100 Adopted for some OpenAI server workloads
OpenAI Exploring custom chips Seeking independence from NVIDIA
Alibaba, Huawei, Tencent T-Head, Ascend, etc. Building unique AI stacks for geopolitical reasons
Tesla D1 chip (Dojo) Self-driving focus, less reliant on GPUs

So the real market trend isn’t AMD replacing NVIDIA, but each giant racing to own a self-sufficient AI stack.


💡 AI Semiconductor Is No Longer a Simple Comparison

In the past, chip wars were about raw speed. Now, it’s about who can build the right ecosystem.
AMD’s cost advantage and similar specs to H100 aren’t enough to unseat NVIDIA.
Big Tech is making custom silicon to match their models, workflows, and APIs—targeting performance, cost, and compatibility all at once.
The real battle is shifting from “NVIDIA vs AMD” to “NVIDIA vs Custom Silicon + Ecosystem Self-Reliance.”


📊 Stock Price Charts (TradingView)

AMD Daily Chart (May 2025)
Daily Chart
AMD Monthly Chart (May 2025)
Monthly Chart
AMD Yearly Chart (May 2025)
Yearly Chart

📊 AMD vs NVIDIA: 6 Key Metrics (May 2025)

Metric Description AMD Score NVIDIA Score
PER Lower = More undervalued 72 58
ROE Higher = More efficient 74 84
FCF Margin Cash flow generation 63 77
Dividend Yield Payout stability 20 64
Debt Ratio Financial soundness 78 70
Volume Change Technical momentum 81 91

Overall Scores:

  • AMD: 388 / 600 = 64.6
  • NVIDIA: 444 / 600 = 74.0

📈 Radar Chart Score

AMD, NVIDIA Key Metrics Radar Chart (May 2025)
Compares major metrics as 100-point normalized scores.
Data from Investing.com and Yahoo Finance.

AMD, NVIDIA Absolute vs Relative Value Chart (May 2025)
Visualizes both actual numbers and 100-point normalized scores.

👤 Leadership Insight: Can Lisa Su Lead AMD to the Top?

  • Ph.D. from MIT; CTO roles at IBM and Freescale Semiconductor.
  • Turned AMD profitable after becoming CEO in 2014.
  • Technician CEO—strengthened CPU/GPU lines, led TSMC collaborations, effective restructuring.
  • While Jensen Huang (NVIDIA CEO) is the showman, Lisa Su is the builder—and Wall Street knows it.
  • But strong leadership alone can’t guarantee AMD will surpass NVIDIA. The market is still watching both closely.

📈 Analyst Price Targets (as of May 2025)

Firm Target Price Recommendation
Morgan Stanley $205 Overweight
Goldman Sachs $198 Neutral
Citi $190 Hold
Bank of America $210 Buy
  • Current AMD price (as of May 27): $177.40
  • Upside to target average: about 14.7%

📊 Financial & Investment Score Summary (ChatGPT Assessment)


🎯 Key Takeaways

  • AMD is strong in pricing, integrated design, and ecosystem flexibility.
  • But the market is still CUDA-centric, with persistent tech and reliability gaps.
  • The real trend is Big Tech building their own AI chips, not just switching to AMD.
  • Don’t chase AMD just for FOMO—judge its role in the shifting market context.

⚠️ Investment Disclaimer

This article is an analysis, not investment advice.
The analysis is based on ChatGPT, TradingView, Investing.com, and Yahoo Finance data, not professional advice.
All investment decisions are solely the reader’s responsibility; use this content for informational purposes only.

📚 Sources & References

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