Iris Energy WKN: A3C7R6 ISIN: AU0000185993 Forum: Aktien User: nanoli2001

Welcher Investor?

$IREN schloss nicht unterhalb der Goldzone. Wir sollten morgen direkt nach der Unterstützungslinie eine Erholung sehen. Es ist allerdings unklar, wie stark diese Erholung ausfallen wird. Das trägt definitiv dazu bei, dass sich Bitcoin "gut" bewegt. Der Tageschart sieht auch gar nicht so schlecht aus. Das dürfte eine interessante Woche werden!

Das hat erstmal nichts direkt mit Iren zu tun, zeigt aber, dass es eine riesige Nachfrage gibt. Google ist nur einer von vielen.

$GOOGL MUSS AI-RECHENLEISTUNG ALLE 6 MONATE VERDOPPELN, UM NACHFRAGE ZU DECKEN, TEILT AI-INFRASTRUKTUR-CHEF MITARBEITERN MIT Optimistisch für $IREN

Wow,.BTC 3% heute..Da kann ja nächste Woche nichts mehr schief gehen...Guten Start morgen

Ja, das habe ich gelesen und verstanden.. Mir fehlt bei dem ganzen Thema der Gesamtüberblick bzgl. Infrastrukturmarkt... Es gibt doch noch andere Infrastrukturfirmen die auch mit Google in der Vergangenheit eher "verbunden" waren.. Da geht es um Speicherzentren..

Oder der Satz:" The lack of chips and other infrastructure constraints affects Googles ability to deploy new Ai features"

Weil sie nicht genug Kapazität haben und was ist mit dem Satz: "It wont be easy but trough collaboration and co design we will get there" Das spricht doch förmluch dafür das sie den Rechenzentrumsausbau nicht alleine durchziehen können, einen gewissen teil bestimmt aber nicht alles

Grund passt, aber warum sollte Google was mit Iren machen ?? Google hat doch auch eigene Möglichkeiten....

Das wäre ein genialer Schachzug

Ich rieche da ein Deal zwischen Google und Iren, vielleicht auch mit google Chips, da Iren die kapazität ja verfügbar hätte, denn warum nur von Nvidia Chips abhängig machen lassen

https://arstechnica.com/ai/2025/11/google-tells-employees-it-must-double-capacity-every-6-months-to-meet-ai-demand/

Using its own chips means Google does not need to completely rely on Nvidia hardware to build out its AI capabilities. Earlier this month, for example, Google announced the general availability of its seventh-generation Tensor Processing Unit (TPU) called Ironwood. Google claims it is “nearly 30x more power efficient” than its first Cloud TPU from 2018. Given widespread acknowledgment of a potential AI industry bubble, including extended remarks by Pichai in a recent BBC interview, the aggressive plans for AI data center expansion reflect Google’s calculation that the risk of underinvesting exceeds the risk of overcapacity. But it’s a bet that could prove costly if demand doesn’t continue to increase as expected. At the all-hands meeting, Pichai told employees that 2026 will be “intense,” citing both AI competition and pressure to meet cloud and compute demand. Pichai directly addressed employee concerns about a potential AI bubble, acknowledging the topic has been “definitely in the zeitgeist.”

The thousandfold scaling challenge One major bottleneck for meeting AI demand has been Nvidia’s lack of capacity to produce enough GPUs that accelerate AI computations. Just a few days ago during a quarterly earnings report, Nvidia said its AI chips are “sold out” as it races to meet demand that grew its data center revenue by $10 billion in a single quarter. The lack of chips and other infrastructure constraints affects Google’s ability to deploy new AI features. During the all-hands meeting on November 6, Google CEO Sundar Pichai cited the example of Veo, Google’s video generation tool that received an upgrade last month. “When Veo launched, how exciting it was,” Pichai said. “If we could’ve given it to more people in the Gemini app, I think we would have gotten more users but we just couldn’t because we are at a compute constraint.” At the same meeting, Vahdat’s presentation outlined how Google plans to achieve its massive scaling targets without simply throwing money at the problem. The company plans to rely on three main strategies: building physical infrastructure, developing more efficient AI models, and designing custom silicon chips.

Major tech companies are in a race to build out data centers. Google competitor OpenAI is planning to build six massive data centers across the US through its Stargate partnership project with SoftBank and Oracle, committing over $400 billion in the next three years to reach nearly 7 gigawatts of capacity. The company faces similar constraints serving its 800 million weekly ChatGPT users, with even paid subscribers regularly hitting usage limits for features like video synthesis and simulated reasoning models. “The competition in AI infrastructure is the most critical and also the most expensive part of the AI race,” Vahdat said at the meeting, according to CNBC’s viewing of the presentation. The infrastructure executive explained that Google’s challenge goes beyond simply outspending competitors. “We’re going to spend a lot,” he said, but noted the real objective is building infrastructure that is “more reliable, more performant and more scalable than what’s available anywhere else.”