#AMDLargestBondDeal

After $SNDK and $MU both had a rally, will the next round of AI money start looking at $AMD? The AI hardware sector has been quite interesting lately. Initially, the market was most excited about $NVDA, but then it became clear that GPUs aren't the only bottleneck. Capital began to spread into HBM, DRAM, and SSD, and both $MU and $SNDK benefited from this revaluation. After storage has been fully discussed by the market, I’ve started to look at $AMD again because its current position is somewhat awkward: AI demand is so strong, the biggest winner is $NVDA; storage shortages give $MU and $SNDK their own logic; $AMD clearly also stands at the core of AI computing power, yet it always has to answer one question—when will it truly be able to take a big enough piece of the pie from $NVDA?#CPIPPIEaseFedSplit #AIInfraEarningsWatch #SpaceX99%ValueFromAI

🚀 AI infrastructure is entering a new phase. Strong revenue growth alone is no longer enough—investors now want proof that massive AI investment is translating into sustainable profits. The latest numbers remain impressive: NVIDIA: $81.6B in revenue (+85% YoY), with Data Center revenue reaching $75.2B (+92% YoY). AMD: Data Center revenue climbed to $16.6B (+32%), driven by strong demand for EPYC CPUs and Instinct AI accelerators. But the AI ecosystem is now much broader than GPUs. It includes: AI accelerators & GPUs CPUs Networking Optical connectivity Memory Cooling systems Power infrastructure Data-center construction The next challenge is no longer just making faster chips—it's building the infrastructure around them. As earnings season continues, I'm focused on three key areas: 1️⃣ Revenue conversion – Are AI orders becoming real revenue? 2️⃣ Capex efficiency – How much investment is needed to generate each additional dollar of AI revenue? 3️⃣ Customer concentration – What happens if a handful of hyperscalers reduce their AI spending? The AI infrastructure story remains compelling, but the market is becoming more selective. The next big question isn't who spends the most on AI—it's who generates the strongest returns from that spending. #OKXOrbitTopics #OKXTraderVoices $XNVDA $NVDA $AMD #AIInfraEarningsWatch #CPIPPIEaseFedSplit #SpaceX99%ValueFromAI

#AIInfraEarningsWatch # AI Infra Earnings Watch: Can Spending Turn Into Profits? The **#AIInfraEarningsWatch** narrative keeps attention on earnings across the companies supplying the infrastructure behind the artificial-intelligence boom. Investors are increasingly looking beyond headline revenue and asking whether enormous AI spending is producing sustainable returns. The ecosystem spans GPUs, networking, memory, storage, cloud capacity, data centers, and power infrastructure. Companies such as **$NVDA**, **$AMD**, **$AVGO**, **$MU**, and **$TSM** provide different pieces of this supply chain, so their results can offer clues about where AI demand is strongest. Capital expenditure is one of the most important indicators. Hyperscalers continue committing substantial resources to AI data centers, but investors want evidence that these investments can generate sufficient revenue and productivity gains. Strong cloud demand and rising AI-related bookings could reinforce the spending cycle. Supply is another variable. Tight availability can support pricing and margins, while aggressive capacity expansion could eventually create pressure. Memory and semiconductor companies are particularly sensitive to this balance. For traders following **#AIInfraEarningsWatch**, the key metrics are AI-related revenue, data-center growth, gross margins, backlog, capital expenditure, free cash flow, and management guidance. High expectations create additional risk: even strong quarterly results may fail to satisfy investors if future guidance falls short of already-elevated forecasts. Ultimately, earnings will help determine whether AI infrastructure remains a durable multi-year growth cycle or begins moving toward a more mature phase where spending and valuations normalize. **$NVDA $AMD $AVGO $MU $TSM** **#AIInfraEarningsWatch #AI #DataCenters #Semiconductors #TechStocks**

$AI AGENTS COULD SUPERCHARGE CPU DEMAND BofA raised its 2030 server CPU market forecast to $210B+ from $170B, nearly 5x the estimated 2025 market. $AI agents are driving CPUs from supporting roles toward the orchestration control plane, potentially shifting the CPU-to-GPU ratio from 1:4 toward 1:1. BofA expects 36% annual growth through 2030. $AMD remains its top CPU pick, while $NVDA is the overall sector favorite.

$AMD just shared this video of the Cerebras $CBRS CEO talking about how the two companies work together

'The Broader Tell': Did Tencent's AI CapEx Shock Just Crush The Bull Case?

NEW: OpenAI is reportedly on track to surpass $40 billion in annualized revenue this year.

🚨 JUST IN: Nvidia lines up up to $500B for AI data centers with major Wall Street firms, while guaranteeing up to 25% of potential losses on GPU collateral to support a secondary market for used AI chips.

Sources: OpenAI is on track to generate annualized revenue of $40B+ based on its current performance, roughly doubling its run rate from the end of 2025 (Bloomberg) (Visit Techmeme dot com for the link and full context!)

JUST IN: OpenAI revenue run rate reportedly at $40 billion