DiscoverGold
7 hours ago
Fri’s Big Selloff Appears Before NVDA’s Earnings Results Due Wed, With Stock Suffering Rejection In Jan At Nov High
By: Hedgopia | February 24, 2025
• Last Friday’s sudden selloff in equities speaks of heightened investor nerves. Amidst this, NVDA, the poster child of the AI revolution and the associated tech rally, reports this Wednesday; ahead of this, there are subtle signs of distribution. An adverse reaction to its results will reverberate through the stock market.
Friday’s sellers could be vindicated if Nvidia’s (NVDA) results draw an adverse reaction. The $3.3-trillion company – second only to Apple’s (AAPL) leading $3.7-trillion market cap – reports its January quarter on Wednesday.
NVDA is expected to bring home $0.85 in earnings per share, with the estimates remaining unchanged for at least the past three months. Its shares peaked three months ago at $152.88 on November 21. That high was unsuccessfully tested with a fresh high of $153.13 on January 7, with a massive reversal ending the session at $140.14. The subsequent selloff ended on the 3rd this month with a low of $113.01. Last Tuesday, the stock ticked $143.44 but finished the week lower 3.3 percent to $134.43. Tuesday’s high was rejected at a falling trendline from last November’s high (Chart 2).
This is taking place at a time when the 50-day ($134.56), which went sideways for five weeks before trending lower, seems to want to drop toward the 200-day at $125.82.
For the bulls, even if Wednesday’s results are received well, and the stock rallies, $153 likely offers strong resistance, as those that did not sell previously treat this as an opportunity to unload.
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Jetmek_03052
7 hours ago
Analyst reworks Nvidia stock price target with Q4 earnings on deck
https://www.msn.com/en-us/money/topstocks/analyst-reworks-nvidia-stock-price-target-with-q4-earnings-on-deck/ar-AA1zGAbH?ocid=msedgntp&pc=U531&cvid=47de2b16e8684e93a7613e277c74dcbe&ei=9
Mosesmann, who reiterated his buy rating and $220 price target on Nvidia stock in a note published Monday, expects a "modest beat and raise for Nvidia's January quarter and March quarter outlook versus consensus estimates."
LSEG data suggest analysts expect April-quarter revenue in the region of $41.75 billion, a tally that suggests a slower, but still impressive, 60% growth rate. Data-center sales are expected to rise 65% to $37.21 billion.
Nvidia is set up well for 2025 - Rosenblatt analyst
"We continue to view the setup in (calendar year 2025) positively for Nvidia, with a strong Blackwell ramp that is resilient to unit share losses to GPU and ASIC accelerator players," Mosesmann said.
"Nvidia's roadmap ([for] which we expect an update at GTC in March) is one of increasing value that is highly complex with multiple configurations," he added. GTC is Nvidia's Global Technology Conference in San Jose, Calif., March 17 to 21.
doc2016
2 days ago
can they create cuprates on the old twister copper insitu? chatgpt says, "
Copper, in its pure form, is not a superconductor. Even at extremely low temperatures, it retains electrical resistance and does not exhibit superconducting properties. This is because copper lacks certain characteristics necessary for superconductivity, such as hole conductivity and appropriate electron pairing mechanisms.
PHYSICSFORUMS.COM
However, certain copper-oxide compounds, known as cuprates, do exhibit superconductivity at higher temperatures compared to traditional superconductors. These high-temperature superconductors, discovered in 1986, are ceramics composed of layers of copper and oxygen atoms. The superconducting behavior in these materials is believed to be driven by interactions between electrons and the magnetic fields of nearby atoms, leading to the formation of Cooper pairs that can move without resistance.
ENERGY.GOV
NEWS.CORNELL.EDU"
Regarding the magnetization of copper, applying a magnetic field to pure copper does not induce superconductivity. Superconductors inherently expel magnetic fields—a phenomenon known as the Meissner effect—whereas copper does not exhibit this behavior.
ANL.GOV
In summary, while pure copper is not a superconductor and magnetizing it does not confer superconducting properties, certain copper-based compounds, specifically cuprates, are known to be high-temperature superconductors due to their unique structural and electronic characteristics.
rolvram
3 days ago
NVIDIA’s CEO Jensen Huang Addresses The “DeepSeek Fiasco” For The First Time; Says Investors “Overreacted” & “Got It All Wrong”
Muhammad Zuhair
Feb 21, 2025 at 08:31am EST
NVIDIA's CEO Jensen Huang has publicly addressed China's DeepSeek for the first time, claiming that the investors overreacted and got the "paradigm wrong."
NVIDIA's CEO Believes DeepSeek's AI Achievement Is Massive For The Markets, Appreciating Their Open-Source Models
The release of DeepSeek's R1 AI models was a massive milestone for the AI markets, but for Team Green, it was an ugly day. The firm saw a whopping $600 billion decline in market value, with Jensen losing over 20% of his net worth, clearly showing investors weren't happy with DeepSeek's achievement. However, in the latest interview with DDN, NVIDIA's CEO Jensen Huang has expressed excitement towards DeepSeek's milestone and, at the same time, believes that investors' perception of AI markets went wrong.
From an investor perspective, there was a mental model that the world was pre-training and then inference. And inference was: you ask an AI a question, and you instantly got an answer. I don't know whose fault it is, but obviously that paradigm is wrong.
It is so incredibly exciting. The energy around the world as a result of R1 becoming open-sourced, incredible.
For those who still aren't aware of why the stock sell-off got triggered, the news around DeepSeek's R1 being trained for around $5 million raised the perception that the demand for AI computing power is artificial in the markets. However, DeepSeek's "low-training" costs were only a FUD, and it was reported that DeepSeek employs well over $1 billion in AI hardware, showing that the firm, too, needs massive computing power.
NVIDIA Blackwell GB200 Powers The Latest A4 VMs At Microsoft Azure, 2.25x Higher Compute & HBM Capacity 1
However, one area where DeepSeek managed to tap into is having robust "open-sourced" AI models, which means that developers can join in to enhance the product further, and it allows organizations and individuals to fine-tune the AI model however they like, allowing it to run on localized AI environments and tapping into hardware resources with the best efficiency. Prior to DeepSeek, the perception was general against open-sourcing models, mainly due to the fact that OpenAI drove the hype.
All eyes are on NVIDIA's upcoming earnings call, which is slated for February 26. The call will likely give us insight into how big of a hit the firm has seen on profitability rates following the DeepSeek fiasco and recent Blackwell AI product issues. However, it is safe to say that with competition from DeepSeek, it is certain that demand for computing power is all around NVIDIA.
rolvram
3 days ago
Michael Del Monte4.37K Followers
Play(9min)
SummaryNvidia's q4'25 earnings have a strong potential to outperform driven by strong data center growth and hyperscalers' continued investment in compute capacity.Hyperscalers' total capital investments may grow by nearly 40% in CY25 to $313b; investments will primarily go towards compute and data centers.The release of DeepSeek-V3 models emphasizes the need for AI model optimization; I do not believe this will directly translate to lower demand for GPUs.Enterprises are expected to bring GenAI into production in CY25, driving the need for data center computing capacity.
J StudiosNvidia (NASDAQ:NVDA) is set to report q4’25 earnings on February 26, 2025, after market close. With the recent news of the release of the DeepSeek-V3 models emerging, the market has been questioning the viability of the growth trajectory for compute capacity, potentially leading to a paradigm shift in investments for Nvidia’s GPUs. Despite the narrative, I believe two important factors emerged from this. The first is that we are in the phase of model optimization, leading to more efficient compute. The second is that compute capacity still needs to scale to meet enterprise demand, as denoted by the hyperscalers’ investment outlays. Given the optimistic spend outlay, I am reiterating my BUY rating for NVDA shares with a price target of $234/share at 28x eFY26 price/sales.The Case For NvidiaThe recent release of DeepSeek-V3 GenAI models took the market by storm, leading the investment community to question the viability of the high level of compute costs associated with running existing models. Though DeepSeek may not be the gold standard of AI models in terms of performance, the application advanced down the cost curve beyond any competing model, pushing the cost of compute to a new low.One of the factors that might need to be considered is scalability. The theme across the hyperscalers’ earnings performance has slightly changed from: “Demand continues to outstrip supply.” The new theme is that growth is constrained by their ability to build data centers and deliver compute capacity. Though these two statements are similar, they are somewhat different.Each of the hyperscalers addresses the concern that DeepSeek (DEEPSEEK) brought to the market and welcomed the model with open arms. In fact, Microsoft and Amazon are all hosting DeepSeek R1 on their respective platforms. Though it may have been a positive spin on disruptive news, the general theme across the hyperscalers was that DeepSeek isn’t necessarily going to disrupt the need for additional compute capacity. The primary conclusion was that DeepSeek’s models are seen as the next phase in AI inferencing, in which models will need to be optimized to function more efficiently. Though the release of DeepSeek’s models may bring forward some concerns relating to scaling compute capacity, I do not believe the existing data center footprint is developed to the point of turning to economies of scope. If anything, I expect that the emergence of these models will ignite the necessity of domestic AI developers to accelerate growth and development to maintain their leadership in AI.As for building a case for investing in Nvidia, not a single hyperscaler reduced its capital outlay for compute and data centers. Borrowing a chart from my recent report covering Alphabet, growth in cloud computing remains strong across the hyperscalers.Corporate ReportsWhat’s most impressive is the capital outlay. On a trailing twelve-month basis, the 3 CSPs invested $186b in expanding their compute capacity.Looking ahead to eCY25, I’m forecasting the capital outlay to grow by nearly 40% on a year-over-year basis, up from $225b. Beyond eCY25, I’m anticipating that growth will normalize and level out at this heightened rate.Corporate ReportsIt should be noted that these figures are my expectations alone. Beyond eCY25, the estimates are based on the 24% CAGR estimate for data centers through 2028. Meta Platforms (META) has suggested a range of $60-65b for eFY25, Microsoft (MSFT) guided that q2’25 set the tone for the e2h25 capital outlay, Amazon (AMZN) set the pace of at least $100b for eFY25, and Alphabet (GOOG) (GOOGL) is expecting to deploy $75b in eFY25.Unless demand for compute capacity softens, the hyperscalers have no plans to slow down investing in new capacity. Management has made clear that capital deployed will remain dependent on the demand environment.Driving this further, Oracle Corp. (ORCL) is partnering with OpenAI in Project Stargate, a $500b project for advancing AI in the US. Oracle alone has pinned 100 data centers for future development, with a site as large as 1.60GW in capacity.In the physical AI space, Tesla recently completed its 50,000 H100 cluster at its Gigafactory Texas facility in Austin that will be utilized for autonomous driving. Elon Musk suggested that the compute capacity for developing its Optimus humanoid robot will need to be 10x larger in order to properly develop a fully autonomous, general-purpose robot.One major factor that must be considered is the infancy of AI at the workplace. Gartner is forecasting GenAI to move beyond the proof-of-concept phase and into production in 2025. Gartner is also forecasting server sales to triple from 2023 to 2028. Though much of the growth may be tied to the CPU server refresh cycle, I anticipate that a good proportion of the growth will be tied to GPUs.Nvidia Financial PositionCorporate ReportsI’m forecasting top-line growth to remain strong at 73% on a year-over-year basis, bringing total revenue to $38b with an adjusted EPS of $0.85/share. This will be driven by an 84% year-over-year growth rate for its Data Center segment following the ramp-up realized in FY24. Though I’m forecasting growth to begin tapering in eFY26 relative to rates experienced in 2h24-1h25, I believe growth will remain durable given the high levels of investment anticipated by the hyperscalers and enterprises.Advanced Micro Devices (AMD) reported exceptional strength in its Client segment, growing by 58% in q4'24 on a year-over-year basis. This may potentially act as a precursor for Nvidia going into eq4’25.Risks Related To NvidiaBull CaseCapital investments by the hyperscalers geared towards growing compute capacity remain durable and growing for eCY25. Enterprise use of GenAI remains a novel experience, potentially leading to a larger upswing in demand for compute capacity to support AI inferencing. Nvidia may also realize growth in its Gaming segment as more workloads are executed at the edge.Bear CaseGrowth may begin to taper sooner than expected if demand for Nvidia’s GPUs doesn’t remain as robust as anticipated. If the hyperscalers begin pulling back on their capital outlay, Nvidia’s growth may slow.Valuation & Shareholder ValueCorporate ReportsNVDA shares continue to trade at a significant premium to its peer semiconductor designers.Seeking AlphaI believe NVDA shares’ trading premium is justified given the company’s high-growth trajectory as well as its industry-leading profitability.Seeking AlphaSeeking AlphaUsing an internal valuation model based on my revenue forecast and NVDA shares’ historical trading premiums, I am reiterating my BUY rating for NVDA shares with a price target of $234/share at 28x eFY26 price/sales.Corporate ReportsUsing the model: the valuation table above references my financial forecast in the firm’s “financial position” section and ties it to the stock’s historical trading premiums. The trading premium array is derived through the normal operating cycle, with the blue-sky scenario being the stock’s peak multiple and the gray-sky scenario being the lowest point. The target multiple aims for the midpoint, or the most likely trading range for the company’s stock. The trading multiples from there are set to a probability factor based on the likelihood of the stock trading at that premium based on its historical presence. From there, the trading multiple is tied to the probability factor to derive its relative market cap and relative multiple.
4retire
4 days ago
Nvidia's Growth Is Supported By Hyperscalers' Capital Investments
Feb. 18, 2025 6:52 AM ETNVIDIA Corporation (NVDA) Stock, NVDA:CA StockNVDA, NVDA:CA19 Comments
Michael Del Monte
4.36K Followers
Play
(9min)
Summary
Nvidia's q4'25 earnings have a strong potential to outperform driven by strong data center growth and hyperscalers' continued investment in compute capacity.
Hyperscalers' total capital investments may grow by nearly 40% in CY25 to $313b; investments will primarily go towards compute and data centers.
The release of DeepSeek-V3 models emphasizes the need for AI model optimization; I do not believe this will directly translate to lower demand for GPUs.
Enterprises are expected to bring GenAI into production in CY25, driving the need for data center computing capacity.
Powering Intelligence: AI Over a Grid of Technology
J Studios
Nvidia (NASDAQ:NVDA) is set to report q4’25 earnings on February 26, 2025, after market close. With the recent news of the release of the DeepSeek-V3 models emerging, the market has been questioning the viability of the growth trajectory for compute capacity, potentially leading to a paradigm shift in investments for Nvidia’s GPUs. Despite the narrative, I believe two important factors emerged from this. The first is that we are in the phase of model optimization, leading to more efficient compute. The second is that compute capacity still needs to scale to meet enterprise demand, as denoted by the hyperscalers’ investment outlays. Given the optimistic spend outlay, I am reiterating my BUY rating for NVDA shares with a price target of $234/share at 28x eFY26 price/sales.
The Case For Nvidia
The recent release of DeepSeek-V3 GenAI models took the market by storm, leading the investment community to question the viability of the high level of compute costs associated with running existing models. Though DeepSeek may not be the gold standard of AI models in terms of performance, the application advanced down the cost curve beyond any competing model, pushing the cost of compute to a new low.
One of the factors that might need to be considered is scalability. The theme across the hyperscalers’ earnings performance has slightly changed from: “Demand continues to outstrip supply.” The new theme is that growth is constrained by their ability to build data centers and deliver compute capacity. Though these two statements are similar, they are somewhat different.
Each of the hyperscalers addresses the concern that DeepSeek (DEEPSEEK) brought to the market and welcomed the model with open arms. In fact, Microsoft and Amazon are all hosting DeepSeek R1 on their respective platforms. Though it may have been a positive spin on disruptive news, the general theme across the hyperscalers was that DeepSeek isn’t necessarily going to disrupt the need for additional compute capacity. The primary conclusion was that DeepSeek’s models are seen as the next phase in AI inferencing, in which models will need to be optimized to function more efficiently. Though the release of DeepSeek’s models may bring forward some concerns relating to scaling compute capacity, I do not believe the existing data center footprint is developed to the point of turning to economies of scope. If anything, I expect that the emergence of these models will ignite the necessity of domestic AI developers to accelerate growth and development to maintain their leadership in AI.
As for building a case for investing in Nvidia, not a single hyperscaler reduced its capital outlay for compute and data centers. Borrowing a chart from my recent report covering Alphabet, growth in cloud computing remains strong across the hyperscalers.
Corporate Reports
Corporate Reports
What’s most impressive is the capital outlay. On a trailing twelve-month basis, the 3 CSPs invested $186b in expanding their compute capacity.
Looking ahead to eCY25, I’m forecasting the capital outlay to grow by nearly 40% on a year-over-year basis, up from $225b. Beyond eCY25, I’m anticipating that growth will normalize and level out at this heightened rate.
Corporate Reports
Corporate Reports
It should be noted that these figures are my expectations alone. Beyond eCY25, the estimates are based on the 24% CAGR estimate for data centers through 2028. Meta Platforms (META) has suggested a range of $60-65b for eFY25, Microsoft (MSFT) guided that q2’25 set the tone for the e2h25 capital outlay, Amazon (AMZN) set the pace of at least $100b for eFY25, and Alphabet (GOOG) (GOOGL) is expecting to deploy $75b in eFY25.
Unless demand for compute capacity softens, the hyperscalers have no plans to slow down investing in new capacity. Management has made clear that capital deployed will remain dependent on the demand environment.
Driving this further, Oracle Corp. (ORCL) is partnering with OpenAI in Project Stargate, a $500b project for advancing AI in the US. Oracle alone has pinned 100 data centers for future development, with a site as large as 1.60GW in capacity.
In the physical AI space, Tesla recently completed its 50,000 H100 cluster at its Gigafactory Texas facility in Austin that will be utilized for autonomous driving. Elon Musk suggested that the compute capacity for developing its Optimus humanoid robot will need to be 10x larger in order to properly develop a fully autonomous, general-purpose robot.
One major factor that must be considered is the infancy of AI at the workplace. Gartner is forecasting GenAI to move beyond the proof-of-concept phase and into production in 2025. Gartner is also forecasting server sales to triple from 2023 to 2028. Though much of the growth may be tied to the CPU server refresh cycle, I anticipate that a good proportion of the growth will be tied to GPUs.
Nvidia Financial Position
Corporate Reports
Corporate Reports
I’m forecasting top-line growth to remain strong at 73% on a year-over-year basis, bringing total revenue to $38b with an adjusted EPS of $0.85/share. This will be driven by an 84% year-over-year growth rate for its Data Center segment following the ramp-up realized in FY24. Though I’m forecasting growth to begin tapering in eFY26 relative to rates experienced in 2h24-1h25, I believe growth will remain durable given the high levels of investment anticipated by the hyperscalers and enterprises.
Advanced Micro Devices (AMD) reported exceptional strength in its Client segment, growing by 58% in q4'24 on a year-over-year basis. This may potentially act as a precursor for Nvidia going into eq4’25.
Risks Related To Nvidia
Bull Case
Capital investments by the hyperscalers geared towards growing compute capacity remain durable and growing for eCY25. Enterprise use of GenAI remains a novel experience, potentially leading to a larger upswing in demand for compute capacity to support AI inferencing. Nvidia may also realize growth in its Gaming segment as more workloads are executed at the edge.
Bear Case
Growth may begin to taper sooner than expected if demand for Nvidia’s GPUs doesn’t remain as robust as anticipated. If the hyperscalers begin pulling back on their capital outlay, Nvidia’s growth may slow.
Valuation & Shareholder Value
Corporate Reports
Corporate Reports
NVDA shares continue to trade at a significant premium to its peer semiconductor designers.
Seeking Alpha
Seeking Alpha
I believe NVDA shares’ trading premium is justified given the company’s high-growth trajectory as well as its industry-leading profitability.
Seeking Alpha
Seeking Alpha
Seeking Alpha
Seeking Alpha
Using an internal valuation model based on my revenue forecast and NVDA shares’ historical trading premiums, I am reiterating my BUY rating for NVDA shares with a price target of $234/share at 28x eFY26 price/sales.
Corporate Reports
Corporate Reports
Using the model: the valuation table above references my financial forecast in the firm’s “financial position” section and ties it to the stock’s historical trading premiums. The trading premium array is derived through the normal operating cycle, with the blue-sky scenario being the stock’s peak multiple and the gray-sky scenario being the lowest point. The target multiple aims for the midpoint, or the most likely trading range for the company’s stock. The trading multiples from there are set to a probability factor based on the likelihood of the stock trading at that premium based on its historical presence. From there, the trading multiple is tied to the probability factor to derive its relative market cap and relative multiple.
This article was written by
Michael Del Monte
4retire
4 days ago
Nvidia likely to offer up 'strong' results, guidance, despite GB200 NVL constraints: KeyBanc
Nvidia (NASDAQ:NVDA) is likely to offer up “strong” results and guidance when it reports quarterly results next week, despite the GB200 NVL constraints it has faced, KeyBanc Capital Markets said.
Nvidia shares rose 1% in premarket trading.
“Despite prior concerns regarding constraints associated with the ramp of GB200 NVL servers, we expect NVDA to report strong F4Q results, which we anticipate will solidly beat, and to guide F1Q conservatively and moderately higher than consensus,” KeyBanc analyst John Vinh wrote in a note to clients.
“While we do believe that manufacturing constraints are limiting shipments of GB200 NVL server racks, we believe this will be more than offset by the following: given the lower initial manufacturing yields of GB200 NVL, we believe customers have been able to push out orders of GB200 and backfill with HGX-based B200 servers with x86 head nodes; DeepSeek, as well as limited supply of Huawei's Ascend AI [application specific integrated circuits], has created a surge in demand for H20 GPUs from China [cloud service providers]; we believe NVDA's customers, esp CSPs, are financing its inventory at EMS providers, so effectively sell-in shipments from NVDA to EMS are recognized as revenues.”
In conjunction, Vinh reiterated his Overweight rating and upped his estimates and price target (to $190 from $180) ahead of the results.
Nvidia is slated to report its quarterly results after the close of trading on Feb. 26. A consensus of analysts expect the company to earn $0.61 per share on $26.044B in revenue.