eastunder
24 hours ago
Shouldn't be upsetting, Jet. Not in the big picture
https://www.sec.gov/Archives/edgar/data/1045810/000104581025000069/xslF345X05/wk-form4_1742604148.xml
Explanation of Responses:
1. Represents shares withheld by the Issuer to satisfy taxes due by the Reporting Person in connection with the vesting of restricted stock units previously reported on a Form 4.
2. Includes 93,615 shares issued upon the vesting of restricted stock units previously reported on a Form 4.
3. The reported transaction was effected pursuant to a Rule 10b5-1 trading plan adopted by the Reporting Person on March 22, 2024.
4. Represents weighted average sales price. The shares were sold at prices ranging from $115.59 to $116.58. The Reporting Person will provide upon request, to the Securities and Exchange Commission (the "SEC"), the Issuer or security holder of the Issuer, full information regarding the number of shares sold at each separate price.
5. Represents weighted average sales price. The shares were sold at prices ranging from $116.61 to $117.57. The Reporting Person will provide upon request, to the SEC, the Issuer or security holder of the Issuer, full information regarding the number of shares sold at each separate price.
6. Represents weighted average sales price. The shares were sold at prices ranging from $117.61 to $117.96. The Reporting Person will provide upon request, to the SEC, the Issuer or security holder of the Issuer, full information regarding the number of shares sold at each separate price.
She sold 22,950 shares and 39,963 shares and 3,747 shares according to that filing
so 66,660 shares total for apx 7.8 million dollars or 117.01 average if you do the math.
BUT she still owns over 3 million shares. Direct.
3,085,765 shares X 117 cpps = 361 million dollars
So selling 7.8 million dollars worth - Not much in the big picture...at least not for her.
Indirect - she owns another 2.4m shares (another what 280m?)
Jetmek_03052
2 days ago
Nvidia's Disconnect: An Improving Business With a Cheaper Stock -- Barrons.com
Dow Jones Newswires March 21, 2025 12:37:00 PM ET
Nvidia CEO Jensen Huang was resolute. At his company's annual GTC developers conference this past week in San Jose, Calif., he laid out a compelling vision for the artificial-intelligence industry while presenting an aggressive road map of coming products from his company. The announcements could leave chip rivals racing to catch up for years to come.
As I walked around the GTC exhibit floor, there was a palpable sense of excitement, with hundreds of people lining up for sessions and panels to hear about the latest AI advances in everything from robotics and healthcare to cutting- edge water-cooled server designs.
Yet, there is a disconnect. Despite the enthusiasm for the future of AI and how Nvidia semiconductors are central to it all, Nvidia shares have treaded water, trading at just 26 times forward price-to-earnings. That's an undemanding valuation for a company projected to boost revenue by 57% this year.
It's driven by three concerns: that AI chip demand could soften after the release of Chinese start-up DeepSeek's efficient models; rising chip competition from Broadcom; and uncertainty over President Donald Trump's threats to put tariffs on chip imports.
At GTC, Huang confidently addressed all three issues, arguing that none of them would impede Nvidia's bright prospects.
With respect to DeepSeek, Huang was particularly defiant, pushing back on the notion that DeepSeek would hurt demand for graphics processing units, or GPUs. During his GTC keynote address on Tuesday, he said the reasoning capability in DeepSeek's AI model, which takes more time to reflect before arriving at a higher-quality answer, is driving a substantial increase in demand for compute resources. That type of reasoning is increasingly used in most of the top AI models.
"Almost the entire world got it wrong," Huang said. "The amount of computation we need at this point as a result of agentic AI, as a result of reasoning, is easily 100 times more than we thought we needed this time last year."
It's a stunning point: One hundred times more compute needed than Nvidia expected just 12 months ago should put to rest questions about near-term demand.
The noise has grown louder when it comes to AI chip competition, as Broadcom CEO Hock Tan frequently tells Wall Street that his company will gain its "fair share" of the AI chip market by 2027 by helping large technology companies design their own AI semiconductors called application-specific integrated circuits, or ASICs.
At GTC, Huang pushed back. "A lot of ASICs get canceled," he replied when I asked him about Broadcom following his Tuesday GTC keynote. "The ASIC still has to be better than the best. How do they know it's going to be the best, so that it will be deployed in volume?"
The clear subtext? Broadcom's offerings won't be competitive with Nvidia.
Broadcom didn't respond to a request for comment about Huang's remarks.
On the question of tariffs, Huang said at a press event Wednesday that he isn't expecting a significant impact on the company's financials or outlook. He said Nvidia has an agile network of suppliers and can move orders to lower- tariff countries as needed, adding that Nvidia plans to bring more manufacturing to the U.S. over time.
In general, Nvidia made the case that the overall market opportunities for AI and AI data center infrastructure are expanding rapidly. Huang expects the industry will spend roughly $500 billion on data center capital expenditures this year, rising to more than $1 trillion by 2028, with Nvidia's GPU chip business gaining a larger share of the spending in the coming years.
Part of that will come from the growing number of Nvidia GPUs inside data centers. These so-called superclusters have grown from 16,000 GPUs to over 100,000 GPUs during the past year. Huang told me he's confident that several million GPU clusters would be built by 2027.
Then there's robotics. Nvidia executive Rev Lebaredian told me we're just at the beginning of an exponential ramp- up in the development of AI robotics. The combination of rising computing power and smarter AI models is making large advances in robotics possible. He believes there will be millions of humanoid robots in use, especially by industrial companies, within five years. I have no particular insight into whether robots are, in fact, imminent. But if it happens, it's one more degree of upside for Nvidia, which makes the hardware brains for robots.
Ultimately, the biggest development from GTC was Nvidia's aggressive product road map. During his keynote, Huang announced that the company's Blackwell Ultra AI server, available later this year, would outperform the current model by 50%. Then he said that the Vera Rubin AI server, scheduled for the second half of 2026, would be 3.3 times faster than Blackwell Ultra. The showstopper was the unveiling of the Rubin Ultra AI server -- set for late 2027 -- with 14 times the performance of Blackwell Ultra. That figure drew gasps from the audience.
Somehow, Nvidia stock barely moved on the news and closed lower on Tuesday amid a general market decline. As a longtime Nvidia watcher, I'm confounded by the lack of enthusiasm from Wall Street. The tech crowd understood the significance; eventually investors will, too.
JJ8
4 days ago
Trend Analysis
NVDA appears to be improving within a longer-term upwards trend. Although it is presently below its 200-day moving average, that average is rising, due to prior gains in NVDA shares. Additionally, the MACD histogram, which is used to measure the near-term trend, is above 0. Comparative Relative Strength analysis shows that this issue is lagging the S&P 500.
Momentum for NVDA is improving. The 14-period Slow Stochastic Oscillator is rising as investors begin to purchase shares.
Today's volume is on track to be lighter than usual, with 200,253,557 shares having traded so far. The On Balance Volume indicator (OBV) shows that longer term selling pressure has given way to near term accumulation by traders.
As of 3:17 PM ET Wednesday, 03/19/2025
PS: Although the Daily MACD Histogram in the chart is in the positive, the Weekly is still in the negative as of now.
DiscoverGold
4 days ago
GPU Gold Rush: Data Centers Charging Toward a $1 Trillion AI Boom
By: Cheddar Flow | March 19, 2025
Key Takeaways
• $1 Trillion Spend: Nvidia CEO Jensen Huang projects global data center construction spending to hit $1 trillion by 2028, driven by rapid AI adoption.
• Massive GPU Orders: The top four cloud service providers have ordered 3.6 million Nvidia Blackwell GPUs, signaling unprecedented demand for AI compute.
• Industry Transformation: These trends underline a shift in tech infrastructure, with hyperscale cloud providers investing heavily in specialized AI hardware.
The Data Center Spending Surge
Nvidia CEO Jensen Huang recently forecast that global spending on data center construction is set to reach $1 trillion by 2028. This projection reflects an inflection point in computing—where traditional software gives way to machine-learning and AI-powered systems. The rapid adoption of generative AI, which underpins applications ranging from language models to image generators, has accelerated capital investments in cloud infrastructure. As enterprises worldwide integrate AI into their products and services, hyperscalers are responding with aggressive data center expansions. This growth is not only boosting server capacity but also driving innovation in cooling, power efficiency, and facility design to support the heavy compute loads.
The Demand for Blackwell GPUs
Alongside the trillion-dollar data center spending, Nvidia’s latest Blackwell GPUs have seen extraordinary demand. Huang revealed that the top four cloud service providers have collectively placed orders for 3.6 million Blackwell GPUs—a staggering figure that highlights the industry’s appetite for cutting-edge AI hardware. These GPUs, designed to handle complex AI workloads, provide the computing power necessary for training and deploying large-scale machine learning models. While this number only reflects orders from the major cloud players, it excludes additional demand from companies like Meta and numerous AI startups. In essence, the true demand for advanced GPUs is even higher, emphasizing Nvidia’s central role in powering the next generation of AI.
Impact on the Tech and Cloud Landscape
The dual trends of surging data center investments and massive GPU orders are reshaping the broader tech landscape. For cloud service providers such as Amazon, Microsoft, and Google, the need to offer robust AI-as-a-service capabilities is driving significant capital allocation. These companies are in a race to build advanced infrastructure, with AI performance now a key differentiator in attracting enterprise customers. Enhanced compute capabilities translate to more efficient training and faster model inference, positioning these cloud platforms at the forefront of digital transformation.
Furthermore, this boom is stimulating a broader industry shift. While Nvidia’s market dominance remains strong, competitors are scrambling to innovate. Companies like AMD and Intel are accelerating their own AI chip development, and cloud giants are exploring in-house solutions to reduce reliance on external suppliers. Yet, Nvidia’s integrated ecosystem—combining hardware prowess with supportive software like CUDA—continues to offer a compelling value proposition.
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