NVIDIA’s $119B in supply commitments and AMD’s 155% year-to-date surge confirm AI compute demand is already contracted, not speculative. <\/p>\n<\/li>\n
Feldman cited a $25 billion Cerebras backlog, with OpenAI, Anthropic, Google, Microsoft, and AWS among buyers whose orders are already locked in. <\/p>\n<\/li>\n
Average individual data center power loads doubled from 150 to 300 megawatts in a single year, making electricity the next hard ceiling on AI buildout. <\/p>\n<\/li>\n
Don’t wait: the analyst who called NVIDIA in 2010 just revealed his top 10 AI stocks. See the full list FREE now<\/a>. <\/p>\n<\/li>\n<\/ul>\n Cerebras CEO and co-founder Andrew Feldman made an appearance on the All-In Podcast to describe an AI infrastructure buildout so lopsided that compute suppliers are still racing to catch up with orders placed months ago. Chamath framed the scale of the buildout bluntly: “We’ve never seen a buildout like this since the Great Wall of China.” Feldman’s response was that the industry didn’t have to build on speculation because much of the demand is already under contract. <\/p>\n “They’re not chasing sort of, if you build it, they will come. They’re chasing the demand that is booked<\/strong>,” Feldman said. He described a $25 billion backlog at Cerebras and argued the company is not alone. According to Feldman, compute supply cannot keep pace with existing, booked orders from OpenAI, Anthropic, Google, Microsoft, and AWS.<\/strong> As a result, data centers are rising across the US, Europe, the Middle East, and even countries like Kazakhstan, Tajikistan, Armenia, and Georgia, with individual buildings consuming more power than mid-sized cities. <\/p>\n The AI Buildout Is Being Compared to the Great Wall of China With Orders Already Booked <\/p>\n The data across the picks-and-shovels layer of the AI stack tells a similar story: bookings, backlog, and power commitments are outpacing what suppliers can deliver. <\/p>\n Readers looking to find the winning companies riding this AI build-out wave can dig into our Free Report: 7 Stocks Powering the AI Boom (That Aren’t Chipmakers)<\/strong>. <\/p>\n Don’t wait:<\/strong> the analyst who called NVIDIA in 2010 just revealed his top 10 AI stocks. See the full list FREE now<\/a>. <\/p>\n NVIDIA Has Committed $119 Billion to Meeting Future Demand <\/p>\n NVIDIA<\/strong> (NASDAQ:NVDA<\/a>) posted Q1 FY2027 revenue of $81.615 billion, up 85.23% year over year, with Data Center revenue of $75.246 billion and Data Center Networking growth of 199%. Guidance for Q2 calls for $91.0 billion in revenue, and total supply-related commitments have reached $119.0 billion<\/strong> to serve demand “beyond the next several quarters.” CEO Jensen Huang called the buildout “the largest infrastructure expansion in human history” in the company’s Q1 FY2027 release. Shares trade around $202.78, up 24.66% over the past year. <\/p>\n Story Continues <\/p>\n AMD’s Data Center Revenue Is Growing 57% <\/p>\n AMD<\/strong> (NASDAQ:AMD<\/a>) reported Q1 2026 revenue of $10.25B, with Data Center revenue up 57% to $5.78B. CEO Lisa Su said “leading customer forecasts exceeding our initial expectations” on the MI450 Series and Helios platforms, and the company disclosed a Meta partnership to deploy up to 6 gigawatts of AMD Instinct GPUs. AMD shares have run 155.29% year-to-date to $546.72, the clearest market vote that Feldman’s supply-tightness thesis is real. <\/p>\n AI Demand Is Driving 60% of Equinix’s Largest Deals <\/p>\n Equinix<\/strong> (NASDAQ:EQIX<\/a>) closed 2025 with record annualized gross bookings of $474M (+42% YoY), and roughly 60%<\/strong> of the largest Q4 deals were driven by AI workloads. Management flagged 52 major expansion projects and roughly 1 GW added to powered land-under-control. CEO Adaire Fox-Martin: “Demand for our solutions has never been higher.” The stock is up 36.46% year to date. <\/p>\n Digital Realty Just Signed the Biggest Hyperscale Lease in Its History <\/p>\n Digital Realty Trust<\/strong> (NYSE:DLR<\/a>) signed a 200-megawatt AI inference lease in Q1 2026, the largest hyperscale lease in company history, contributing to $707 million in annualized GAAP base rent bookings. It has roughly 1.2 GW under construction and 6.3 GW of buildable capacity in the pipeline, per its Q1 2026 release. <\/p>\n AI Experimentation Will Eventually Become More Efficient <\/p>\n Feldman did not dismiss the debate around whether the spending is creating real value. He conceded some wasteful spending exists, likening it to the experimentation phase of early AWS adoption. <\/p>\n He compared early AI token usage to shoppers wandering every aisle at Costco before learning to shop efficiently. His argument is that the net value created will be enormous<\/strong>, and consumption patterns will rationalize over time without undermining the buildout thesis. <\/p>\n What to Watch Next <\/p>\n The next constraint on AI is electricity and power. Individual data center loads have already doubled from approximately 150 megawatts to 300 megawatts, while the EIA estimates server electricity consumption could reach 818 billion kilowatt-hours by 2050<\/strong> in a high-demand scenario. <\/p>\n If Feldman is right that yesterday’s orders already exceed today’s available compute, the greatest operating leverage might belong to the companies that can pour concrete, secure power, and ship silicon fastest. <\/p>\n Don’t wait:<\/strong> the analyst who called NVIDIA in 2010 just revealed his top 10 AI stocks. See the full list FREE now<\/a>. <\/p>\n<\/a> 24\/7 Wall St. <\/p>\n