GPU forward curve flips to contango, signaling rising AI compute pricing

Posts cited

1. [42] Nebulizer · @smasimho · 03:41

   $NBIS just got a tailwind from the compute forward curve. Per Silicon Data CEO Carmen Li, the GPU forward curve has flipped to contango, confirming market expectations that compute pricing keeps rising. In futures markets, contango means longer-dated contracts price higher than near-term ones. Last year the curve sloped down. The longer you locked in, the cheaper your GPU-hour. That's no longer the case. Locking in long-term barely gets you a discount anymore. Meanwhile, implied forward rates point to compute prices rising over the next 36 months. For $NBIS and the AI infra industry, this means: ◆ Renewals and new contracts reprice higher ◆ More customers looking to lock in capacity early ◆ Every new MW comes online into a rising price curve

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2. [52] APRO 🟩 AI Oracle · @apro_oracle · 02:43

   📅 APRO Weekly Update APRO is powering top AI Agents , #RWA & #DeFi projects with rock-solid data feeds. 🚀 Key update: RWA Data Scaling 🌐 +40 blockchains @ethereum @BNBCHAIN @base @solana @Aptos @arbitrum @monad @plumenetwork @ZetaChain @arc @GoKiteAI @SuiNetwork and more. 🛡️ +114k Data Validations 🚨 +111k AI Oracle Calls To be A PRO! To be Multi PRO! 🟩

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3. [63] Sawyer Merritt · @sawyermerritt · 02:10

   I think AI compute cost-per-watt prices are going to stay elevated a lot longer than many people expect. Less than 5% of U.S. consumers even pay a subscription for an AI product, with some putting the estimate <2%. People are clearly finding Grok Bot to be very useful because @SpaceX just had to significantly cut back usage capacity due to overwhelming demand. But we're still so early in the AI adoption curve. Existing users are going to eat up significantly more compute as models get better and agents start handling increasingly complex tasks and jobs. Inference will increasingly become a larger and larger share of compute capacity. People are seriously underestimating how much demand is still ahead of us and how long it'll take supply to catch up. I think this is partly why Elon thinks SpaceX could exit 2027 with an annual recurring revenue rate of $500 billion to $1 trillion. They can deploy the compute faster than anyone else, and the demand for that compute is insatiable, and likely will be for a long time to come.

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4. [70] Peggy · @0xpeggy_ · 01:25

   Good morning🔆 Happy Monday to X fam!!! When a reputation score doesn’t require a "visit" Most products aim to bring users back to a single destination: their own app. Infrastructure, however, takes the opposite approach. This is why distribution may well be the most critical long-term test for ACS the reputation layer developed by @agenticscredit. The problem with the "single-destination" model Currently, if you want to check your reputation score, you have to step away from your current task, open the Agentics app, review your profile, and then return to what you were doing. Every extra step creates friction, and users rarely change their habits just for the sake of a new tool. The solution: let the score follow the activity Imagine you are using a familiar trading platform. Right within that interface, your ACS score appears; you can instantly gauge your reputation level and initiate a credit process all without needing to open another tab. By embedding ACS as a widget or making it accessible via an API, any DeFi application can serve as a gateway to the same underlying reputation and credit infrastructure. For instance, a lending protocol might want to evaluate borrowers without building a scoring system from scratch. By embedding an ACS widget, they allow users to see their score directly on the loan screen, where the credit journey can begin. Similarly, a marketplace for AI agents could display a reputation score next to each agent, helping users choose more reliable options. Why this is especially crucial for AI agents In the future, AI agents will operate across diverse environments from trading platforms and capital-raising venues to strategy deployment hubs and portfolio management tools. If a reputation score is locked inside a single application, every new integration becomes cumbersome. By making the score portable via APIs and widgets, it follows the activity, rather than forcing the activity to revolve around it. Applications vs. Infrastructure A typical application tries to draw all its users to a single destination. Infrastructure, by contrast, provides value wherever the user happens to be. Agentics does not need to own every interface; instead, it must ensure its reputation layer is valuable enough that other interfaces choose to integrate it on their own. The Real Test The key metric to track is not just how many people visit the application, but how many other applications decide to incorporate ACS into their own products. Each new integration serves as a new access channel, creating a cumulative effect on distribution. @agenticscredit In this scenario, ACS is no longer something you must visit a specific place to access it becomes present exactly where financial decisions are made.

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5. [71] DMT🐐 · @dmtland_ · 01:24

   A new innovation every day? I remain equally impressed by the data analysis capabilities @origin_trail provides for AI agents. The example below is crucial and demonstrates its role in major incidents such as the Binance hack; it’s going to make so many things easier in future when it comes to cross-referencing wallets, tracking malicious users and much more besides. The video I am referring to offers a strong way to visualise my point.

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