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Wall St Engine

@wallstengine • 204,795 subscribers

Fast, accurate, consistent stock market news, earnings highlights & more. By Brillinsight. Not financial advice.

Shorts

NVIDIA & VERTIV TARGET UP TO 30% MORE AI TOKENS WITH THE SAME CAPACITY $NVDA and $VRT announced a new AI factory deployment approach at GTC Berlin that could cut the time from project kickoff to productive capacity from 120 days to just 48 days. According to Vertiv's modeled estimates, this could result in up to 30% more cumulative AI token output in the first 12 months, without increasing installed computing capacity. Here's how the new approach works: • 10x Faster Design: NVIDIA's Vera Rubin DSX AI Factory reference design, Omniverse DSX Blueprint, and Vertiv's SimReady assets integrate with Dassault Systèmes' 3DEXPERIENCE platform to reduce configuration and validation time from 30 days to just 3 days. • 50% Faster Deployment: Vertiv's prefabricated OneCore and SmartRun infrastructure could reduce on-site power and cooling deployment from 90 days to 45 days. • 72 Days Saved: Combined, the approach could bring AI factories online approximately 10 weeks earlier, providing 317 productive days in the first year compared with 245 using conventional methods. • Real-World Deployment: Polar Data Centers is applying Vertiv's factory-built approach to the first 41 MW phase of its AI data center in Herøya, Norway 🇳🇴, with plans to scale the facility to 100 MW. • Factory-Built Infrastructure: Power, cooling, networking, and supporting systems can be designed and virtually validated before construction, with more assembly and testing completed off-site.

NVIDIA & VERTIV TARGET UP TO 30% MORE AI TOKENS WITH THE SAME CAPACITY $NVDA and $VRT announced a new AI factory deployment approach at GTC Berlin that could cut the time from project kickoff to productive capacity from 120 days to just 48 days. According to Vertiv's modeled estimates, this could result in up to 30% more cumulative AI token output in the first 12 months, without increasing installed computing capacity. Here's how the new approach works: • 10x Faster Design: NVIDIA's Vera Rubin DSX AI Factory reference design, Omniverse DSX Blueprint, and Vertiv's SimReady assets integrate with Dassault Systèmes' 3DEXPERIENCE platform to reduce configuration and validation time from 30 days to just 3 days. • 50% Faster Deployment: Vertiv's prefabricated OneCore and SmartRun infrastructure could reduce on-site power and cooling deployment from 90 days to 45 days. • 72 Days Saved: Combined, the approach could bring AI factories online approximately 10 weeks earlier, providing 317 productive days in the first year compared with 245 using conventional methods. • Real-World Deployment: Polar Data Centers is applying Vertiv's factory-built approach to the first 41 MW phase of its AI data center in Herøya, Norway 🇳🇴, with plans to scale the facility to 100 MW. • Factory-Built Infrastructure: Power, cooling, networking, and supporting systems can be designed and virtually validated before construction, with more assembly and testing completed off-site.

40,114 Aufrufe

Wow 😂 Coinbase $COIN CEO Brian literally got distracted during the earnings call to check a prediction market on what he was gonna say… then went ahead and said every single word people were betting on.

Wow 😂 Coinbase $COIN CEO Brian literally got distracted during the earnings call to check a prediction market on what he was gonna say… then went ahead and said every single word people were betting on.

1,284,811 Aufrufe

Tesla $TSLA just showed its new Roadster driving up a curved ramp and staying attached while fully inverted.

Tesla $TSLA just showed its new Roadster driving up a curved ramp and staying attached while fully inverted.

26,128 Aufrufe

$NVDA CEO Jensen Huang reacting to the audience showing how their NVIDIA stock has performed: Jensen: Look at that… Look at that… 😂

$NVDA CEO Jensen Huang reacting to the audience showing how their NVIDIA stock has performed: Jensen: Look at that… Look at that… 😂

1,029,718 Aufrufe

Andrew Ross Sorkin on Stock Market Crash: “We will have a crash, I just can't tell you when, and I can't tell you how deep. But I can assure you, unfortunately, I wish I wasn't saying this, we will have a crash”

Andrew Ross Sorkin on Stock Market Crash: “We will have a crash, I just can't tell you when, and I can't tell you how deep. But I can assure you, unfortunately, I wish I wasn't saying this, we will have a crash”

466,107 Aufrufe

Trump on Iran: By the way, the Iran war will end after the midterms. A lot of people think if we lose [midterm], I’ll just be more angry and I’ll just take care of business, you know? Either way they lose.

Trump on Iran: By the way, the Iran war will end after the midterms. A lot of people think if we lose [midterm], I’ll just be more angry and I’ll just take care of business, you know? Either way they lose.

53,961 Aufrufe

Jensen: "We're going up, up, up, it's our moment!"

Jensen: "We're going up, up, up, it's our moment!"

124,144 Aufrufe

$META CEO Mark Zuckerberg leaving Speaker Mike Johnson’s office

$META CEO Mark Zuckerberg leaving Speaker Mike Johnson’s office

75,640 Aufrufe

Google it Ask ChatGpt & now… “Check Polymarket” is a thing!

Google it Ask ChatGpt & now… “Check Polymarket” is a thing!

15,574 Aufrufe

Videos

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$GOOGL JUST PUT ITS AI CHIPS INTO ORBIT FOR THE FIRST TIME Google and Planet Labs $PL have successfully launched Project Suncatcher M1 aboard SpaceX’s Transporter-18 mission. Planet says it has already made contact with the spacecraft and begun commissioning. This is the first-ever in-orbit test of Google’s Tensor Processing Units, or TPUs. The refrigerator-sized prototype carries four Trillium TPUs, Google’s custom AI accelerators. This is not yet an orbital data center. The goal is to see whether the same type of AI hardware Google uses on Earth can survive launch and reliably run machine-learning workloads in low Earth orbit. There are three major engineering problems Google is testing: RADIATION: cosmic radiation can corrupt calculations or damage electronics. Google previously tested Trillium TPUs with proton radiation and found they could withstand more total radiation than expected over a five-year mission. COOLING: there is no air in space, so fans cannot cool the chips. Heat has to be moved through heat pipes into radiators and then emitted away from the spacecraft. The current prototype is expected to run AI workloads in roughly 15-minute bursts before allowing the system to cool. NETWORKING: Google’s long-term plan is not one satellite, but clusters of satellites carrying dozens of TPUs each and connected through high-speed laser links. Google estimates future AI workloads could require tens of terabits per second between satellites. Its ground prototype has already demonstrated 800 Gbps in each direction. Why put AI compute in space at all? In the right low-Earth orbit, solar panels can generate up to 8x more power than on Earth because satellites can receive near-continuous sunlight, reducing one of the biggest constraints facing AI data centers: electricity. The economics: Google estimates that if launch costs eventually fall below roughly $200 per kilogram by the mid-2030s, the cost of operating compute in space could begin approaching the energy cost of comparable terrestrial data centers.

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105,446 Aufrufe • vor 21 Tagen