#Unraid Pricing

Consensus is already pricing in dominance: roughly $65 billion in quarterly revenue, EPS near $1.50 and gross margins around 74 to 75 percent. Data center revenue is expected to exceed $55 billion, meaning more than 80 percent of total revenue is now tied directly to AI infrastructure. The debate isn’t whether Nvidia beats estimates. It’s whether the models themselves are using the wrong framework. Traditional semiconductor cycles peak when inventories build and demand cools. Infrastructure cycles operate differently. When hyperscalers like Microsoft, Alphabet, Amazon and Meta commit tens of billions in multi-year AI capex, demand visibility extends beyond a single quarter. This is not a restocking phase. It is capacity expansion. The Blackwell transition also supports higher system-level pricing and tighter ecosystem integration. Margins near 75 percent suggest structural pricing power, not just temporary supply constraints. Nvidia is monetizing the core of the AI stack, not just riding a cyclical upswing. If sovereign and enterprise AI investment continues globally, normalization may take longer than current models assume. Forward guidance, backlog visibility, and hyperscaler capex commentary will determine whether estimates move higher again. 💡 Principle: Infrastructure cycles don’t peak on inventory. They peak on capital discipline. Follow @thefinancebase for daily financial news.

Consensus is already pricing in dominance: roughly $65 billion in quarterly revenue, EPS near $1.50 and gross margins around 74 to 75 percent. Data center revenue is expected to exceed $55 billion, meaning more than 80 percent of total revenue is now tied directly to AI infrastructure. The debate isn’t whether Nvidia beats estimates. It’s whether the models themselves are using the wrong framework. Traditional semiconductor cycles peak when inventories build and demand cools. Infrastructure cycles operate differently. When hyperscalers like Microsoft, Alphabet, Amazon and Meta commit tens of billions in multi-year AI capex, demand visibility extends beyond a single quarter. This is not a restocking phase. It is capacity expansion. The Blackwell transition also supports higher system-level pricing and tighter ecosystem integration. Margins near 75 percent suggest structural pricing power, not just temporary supply constraints. Nvidia is monetizing the core of the AI stack, not just riding a cyclical upswing. If sovereign and enterprise AI investment continues globally, normalization may take longer than current models assume. Forward guidance, backlog visibility, and hyperscaler capex commentary will determine whether estimates move higher again. 💡 Principle: Infrastructure cycles don’t peak on inventory. They peak on capital discipline. Follow @thefinancebase for daily financial news.

🚀 Nvidia’s AI Architecture Is Rewriting the Internet Nvidia is not just building faster chips, it is rebuilding how data moves. With its AI focused architecture and ultra high speed switches, information now flows at a scale and speed traditional internet infrastructure was never designed for. This is about machines talking to machines in real time, without delay. The world’s fastest AI switches allow massive data centers to think like one system. Training large AI models now depends less on raw compute and more on how quickly GPUs can communicate. This shift is quietly changing cloud computing, enterprise AI, and the future of the internet itself. As AI becomes the backbone of digital systems, companies controlling this infrastructure gain a huge advantage. Nvidia is positioning itself not just as a chip maker, but as the foundation layer of the AI era. Are we entering a future where the internet as we know it feels outdated 🤔 Follow @buisness.brief [keywords: Nvidia, AI architecture, data centers, GPU communication, AI infrastructure, high speed switches, future of internet]

📰 🔥 The AI infrastructure race just escalated. Meta has secured a multibillion-dollar, multi-year chip agreement with Nvidia — reinforcing its long-term commitment to AI compute dominance. This isn’t just another tech partnership. It signals: • Massive capital allocation toward AI data centers • Long-term demand for high-performance GPUs • Continued consolidation of AI power among mega-cap firms • Increasing barriers to entry for smaller competitors AI isn’t slowing down — it’s scaling. When companies commit billions upfront to secure compute supply, it tells you one thing: They expect demand to explode. The question isn’t whether AI grows. It’s who controls the infrastructure. 👇 Do you think Nvidia remains the backbone of AI — or will new chip rivals emerge? Follow @chartzwithlivz for clean, factual breakdowns before they hit mainstream headlines. #ai #nvidia #meta #chartzwithlivz

NVDA Crushes Q4: Networking Is A Major New Catalyst NVIDIA’s data center business is up nearly 13x since ChatGPT emerged in 2023 and networking is now a real growth catalyst. They reported $11B of networking revenue in Q4 and $31B for the full year, driven by the “AI factory” buildout. Next wave: agentic AI, physical AI, and autonomy. $ORCL $NVDA $LLY $AMD $CAT $AMD $GS $AMZN #Nvidia #OpenClaw #Codex #claude #Stocks #Investing #WallStreetGameNotes #WSGN #Markets #Technology #FutureTech #AV #Autonomous #PhysicalAI #AgenticAI #AIAgents #Robotics #AIBoom #AIRevolution #DataCenters #Space #SpaceTech #Compute #Chips @nvidia NVIDIA @nvidiaai @nvidianewsroom Bloomberg Businessweek @bloombergtv Bloomberg Technology @bloombergbusiness @yahoofinance Yahoo Finance @openai OpenAI @cnbc CNBC @wsj @wsj The Wall Street Journal @claudeai @ai_anthropic @caterpillarinc Caterpillar Mercedes-Benz @mercedesbenz Business Insider @businessinsider Oracle @oracle @fortunemag Fortune

AI Is Growing Faster Than the Systems Supporting It: Who Fills the Gap? AI needs energy, chips, data centers, networks — and right now, there isn't enough of any of it. Computing capacity remains scarce. Rental prices keep rising. Even with over $100 billion in VC investment in 2025, demand is still outpacing supply.

From gaming giant to AI leader. NVIDIA's data center revenue is crushing its gaming revenue. The future is here. #NVIDIA #AIRevolution #DataCenter #TechNews #ArtificialIntelligence #FutureIsNow #TechTrends

Three billion-dollar moves this week. You probably missed all of them. Nvidia $20B into OpenAI. Cerebras at $23B. OpenAI going open-source. Silicon is the new oil. #WeeklyIntel #AI #Nvidia #Cerebras #TechInvesting #7wData

Nvidia’s AI dominance isn’t just about faster GPUs — it’s about architectural decisions around high-bandwidth memory (HBM) and securing constrained supply before competitors could scale around it. When a company designs its entire chip strategy around scarce components — and then effectively locks in upstream capacity — alternative architectures may look viable on paper, but they face structural limits in manufacturing, sourcing, and deployment speed. This is the real “innovator’s dilemma” in AI hardware: you can design a different chip, but you can’t instantly replicate memory supply, optical throughput infrastructure, or ecosystem standardization once it’s been absorbed. In AI infrastructure, scale is not just engineering — it’s supply chain control. Follow @TechSignalClips for more. Video: All-In Podcast — “Nvidia’s Dilemma: AI Learning vs Inference” [NVIDIA, All-In Podcast, AI Infrastructure, HBM, AI Chips, Semiconductors, Inference, Data Centers, Supply Chain, Chip Architecture] #nvidia #allinpodcast #aiinfrastructure #aichips

AI traffic isn’t just bigger - it’s fundamentally different. Scott Raynovich, Founder & Principal Analyst at Futuriom, sits down with Thomas Scheibe, CPO at Aviz, to break down what’s really changing as AI clusters and “AI factories” scale fast. From east-west heavy GPU traffic to front-end vs. back-end AI fabrics, they unpack: ✔ Why AI workloads demand multiple networks ✔ How open networking + SONiC reduce cost and complexity ✔ What network observability means in AI environments ✔ How NVIDIA Spectrum-X and automation accelerate deployments If you're building or operating AI infrastructure, this is a must-watch. Full episode covers speed to deploy, operational simplicity, and performance at scale, watch now- https://lnkd.in/g5Fh9Mj5 #AINetworking #SONiC #OpenNetworking #NetworkAutomation #AIOps #NetworkObservability #NVIDIA #SpectrumX #AIFactory #GPUClusters #DataCenterNetworking #Futurum #Aviz

$100B WTF👇follow @tech.unicorn for tech news 😅 we are in a bubble within a bubble (we will discuss tomorrow 👀) but seriously Nvidia may have just created the ultimate AI growth loop..🤯 (Had to repost since insta removed the music lol…) Here’s what’s happening: 🔹 OpenAI’s demand is off the charts- training frontier AI could require up to 10 gigawatts of compute capacity, which is basically Nvidia’s entire annual GPU output feeding into hyperscale datacenters. 🔹 The $100B cycle: OpenAI spends tens of billions buying Nvidia chips and infrastructure. Instead of pocketing the revenue, Nvidia reinvests much of it back into OpenAI as equity. The result: a self-reinforcing cycle (recursive loop, if you may..) OpenAI fuels Nvidia’s sales, Nvidia fuels OpenAI’s growth. 🔹 Why it matters: this isn’t just a supplier–customer deal. Nvidia is embedding itself in OpenAI’s future valuations, transforming hardware sales into long-term returns. It’s a way of securing both demand for its GPUs and equity upside in AI’s most ambitious player. The big picture: • OpenAI burning ~$5B yearly to scale 🚀 • Targeting $200B valuation by 2030 📈 • Nvidia capturing not just margin, but a stake in the AI endgame 💰 Brilliant synergy or risky financial loop? 👇🔥 What do YOU think? Are we heading toward digital utopia or should we all start prepping for the AI apocalypse? Drop your hottest takes below! 👇 Join the community for more tech news! 👩🏻‍💻 ~~~~~~~~~~~~~~~~~~~ 🦄 Follow @tech.unicorn 🗞 Share your thoughts👇 🔖 Leave any questions 😀 ~~~~~~~~~~~~~~~~~~~ Tags 🏷 #technews # #womenintech #techgirls #AI Nvidia OpenAI TechNews BusinessStrategy AINews techtok

Georgia is hitting the brakes on new data centers until 2027 to protect residents from skyrocketing utility costs. Can "community-first" AI infrastructure actually work, or is it just tech-giant PR? Ed and Stefano weigh in on the battle between Big Tech and the local power grid in the latest episode of Ed & Stefano Unleashed! 🔗 Click the link in our bio to watch the full episode! 👉 Check our Stories for a direct link! #Unraid #AIDataCenters #TechNews #HomeLab #EdAndStefanoUnleashed #SelfHosted