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🟢 NVIDIA is preparing for a new phase of the AI boom
🚀 Demand for AI chips is so high that NVIDIA is expanding not only processor production, but its entire supplier network.
🏭 On October 21, the company announced new agreements with partners to help increase production capacity. In particular, capacity for manufacturing chip substrates is expected to grow 2.5 times over the next three years, while advanced packaging capacity is set to more than triple by the end of 2028.
💡 Why does this matter? Developing AI takes more than simply creating a powerful chip. It also requires memory, complex packaging, cooling systems, electricity, and data centers. If even one link in the chain can’t keep up with demand, scaling slows down.
📈 For NVIDIA, this is an opportunity to grow its business, but an important question remains for investors: will AI demand be enough to justify the industry’s enormous spending over the long term?
🤔 What do you think: will NVIDIA remain the leader in the AI market for much longer, or will competitors gradually start taking market share?
#NVIDIA #AI #TechNews
🟢 NVIDIA is preparing for a new phase of the AI boom
🚀 Demand for AI chips is so high that NVIDIA is expanding not only processor production, but its entire supplier network.
🏭 On October 21, the company announced new agreements with partners to help increase production capacity. In particular, capacity for manufacturing chip substrates is expected to grow 2.5 times over the next three years, while advanced packaging capacity is set to more than triple by the end of 2028.
💡 Why does this matter? Developing AI takes more than simply creating a powerful chip. It also requires memory, complex packaging, cooling systems, electricity, and data centers. If even one link in the chain can’t keep up with demand, scaling slows down.
📈 For NVIDIA, this is an opportunity to grow its business, but an important question remains for investors: will AI demand be enough to justify the industry’s enormous spending over the long term?
🤔 What do you think: will NVIDIA remain the leader in the AI market for much longer, or will competitors gradually start taking market share?
#NVIDIA #AI #TechNews
🚀 Demand for AI chips is so high that NVIDIA is expanding not only processor production, but its entire supplier network.
🏭 On October 21, the company announced new agreements with partners to help increase production capacity. In particular, capacity for manufacturing chip substrates is expected to grow 2.5 times over the next three years, while advanced packaging capacity is set to more than triple by the end of 2028.
💡 Why does this matter? Developing AI takes more than simply creating a powerful chip. It also requires memory, complex packaging, cooling systems, electricity, and data centers. If even one link in the chain can’t keep up with demand, scaling slows down.
📈 For NVIDIA, this is an opportunity to grow its business, but an important question remains for investors: will AI demand be enough to justify the industry’s enormous spending over the long term?
🤔 What do you think: will NVIDIA remain the leader in the AI market for much longer, or will competitors gradually start taking market share?
#NVIDIA #AI #TechNews
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🚨 #NVIDIA Could Be More Than a Chipmaker in Meta’s $95 Billion Plan!
CNBC reports that Meta Platforms plans to raise up to $95 billion through public equity offerings and an at-the-market program. NVIDIA, AMD, and Broadcom were named as potential cornerstone investors, with the group potentially contributing up to $5 billion. In the supplied market data, $NVDA gained 2.85% to $217.03.
{stock_us}(NVDA.US)
📊 The bigger story is how AI infrastructure is being financed. NVIDIA could benefit if this strengthens its relationship with major AI customers, but investors will also question whether financing arrangements create circular exposure across the AI supply chain.
🎯 Watch for NVIDIA’s confirmed participation, hyperscaler spending plans, order growth, and margins. Financing headlines can spark momentum, but sustainable demand must support valuations.
Is NVIDIA becoming both an AI supplier and a key player in funding the AI boom?
$NVDAB $METAB $AMDB #CoinVahini #NVIDIA #ArtificialIntelligence #StockMarket
🚨 #NVIDIA Could Be More Than a Chipmaker in Meta’s $95 Billion Plan!
CNBC reports that Meta Platforms plans to raise up to $95 billion through public equity offerings and an at-the-market program. NVIDIA, AMD, and Broadcom were named as potential cornerstone investors, with the group potentially contributing up to $5 billion. In the supplied market data, $NVDA gained 2.85% to $217.03.
📊 The bigger story is how AI infrastructure is being financed. NVIDIA could benefit if this strengthens its relationship with major AI customers, but investors will also question whether financing arrangements create circular exposure across the AI supply chain.
🎯 Watch for NVIDIA’s confirmed participation, hyperscaler spending plans, order growth, and margins. Financing headlines can spark momentum, but sustainable demand must support valuations.
Is NVIDIA becoming both an AI supplier and a key player in funding the AI boom?
$NVDAB $METAB $AMDB #CoinVahini #NVIDIA #ArtificialIntelligence #StockMarket
CNBC reports that Meta Platforms plans to raise up to $95 billion through public equity offerings and an at-the-market program. NVIDIA, AMD, and Broadcom were named as potential cornerstone investors, with the group potentially contributing up to $5 billion. In the supplied market data, $NVDA gained 2.85% to $217.03.
📊 The bigger story is how AI infrastructure is being financed. NVIDIA could benefit if this strengthens its relationship with major AI customers, but investors will also question whether financing arrangements create circular exposure across the AI supply chain.
🎯 Watch for NVIDIA’s confirmed participation, hyperscaler spending plans, order growth, and margins. Financing headlines can spark momentum, but sustainable demand must support valuations.
Is NVIDIA becoming both an AI supplier and a key player in funding the AI boom?
$NVDAB $METAB $AMDB #CoinVahini #NVIDIA #ArtificialIntelligence #StockMarket
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Article
NVIDIA Stock: Can AI Growth Drive the Next Rally $NVDAB 🚀
NVIDIA (NVDA) remains a major company to watch in the artificial intelligence (AI) industry. Its GPUs power AI models, data centers, and advanced computing systems.
Growing demand for AI infrastructure could support NVIDIA’s long-term growth. However, competition, market volatility, and high stock valuations remain important risks for investors.
My view: NVIDIA has strong AI potential, but investors should research current prices and company results before making any decision. No stock guarantees profit.
💬 Question: Do you think NVIDIA can continue leading the AI revolution?
#NVIDIA #NVDA #Aİ #stockmarket #Investing
— Miraj Misu
{spot}(NVDABUSDT)
NVIDIA Stock: Can AI Growth Drive the Next Rally
$NVDAB 🚀
NVIDIA (NVDA) remains a major company to watch in the artificial intelligence (AI) industry. Its GPUs power AI models, data centers, and advanced computing systems.
Growing demand for AI infrastructure could support NVIDIA’s long-term growth. However, competition, market volatility, and high stock valuations remain important risks for investors.
My view: NVIDIA has strong AI potential, but investors should research current prices and company results before making any decision. No stock guarantees profit.
💬 Question: Do you think NVIDIA can continue leading the AI revolution?
#NVIDIA #NVDA #Aİ #stockmarket #Investing
— Miraj Misu
NVIDIA (NVDA) remains a major company to watch in the artificial intelligence (AI) industry. Its GPUs power AI models, data centers, and advanced computing systems.
Growing demand for AI infrastructure could support NVIDIA’s long-term growth. However, competition, market volatility, and high stock valuations remain important risks for investors.
My view: NVIDIA has strong AI potential, but investors should research current prices and company results before making any decision. No stock guarantees profit.
💬 Question: Do you think NVIDIA can continue leading the AI revolution?
#NVIDIA #NVDA #Aİ #stockmarket #Investing
— Miraj Misu
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Article
Nvidia Has Lost The China AI Accelerator MarketNvidia has lost its AI accelerator market in China, according to coverage of the company's position in the region.
The loss follows export controls that restrict the sale of advanced AI chips to Chinese customers, pushing buyers toward domestic alternatives.
China was historically a significant revenue pool. Losing it changes the shape of the addressable market even as demand elsewhere keeps growing.
The competitive consequence is the more important part: a restricted market is where domestic chipmakers iterate fastest, with guaranteed volume and no foreign competitor at the high end.
Nvidia has not framed this as permanent, and the policy environment is the variable that would determine any reversal.
What is harder to rebuild: market share or supply chain? $NVDA #Nvidia #AI #Chips #BinanceSquare
Nvidia Has Lost The China AI Accelerator Market
Nvidia has lost its AI accelerator market in China, according to coverage of the company's position in the region.
The loss follows export controls that restrict the sale of advanced AI chips to Chinese customers, pushing buyers toward domestic alternatives.
China was historically a significant revenue pool. Losing it changes the shape of the addressable market even as demand elsewhere keeps growing.
The competitive consequence is the more important part: a restricted market is where domestic chipmakers iterate fastest, with guaranteed volume and no foreign competitor at the high end.
Nvidia has not framed this as permanent, and the policy environment is the variable that would determine any reversal.
What is harder to rebuild: market share or supply chain? $NVDA #Nvidia #AI #Chips #BinanceSquare
The loss follows export controls that restrict the sale of advanced AI chips to Chinese customers, pushing buyers toward domestic alternatives.
China was historically a significant revenue pool. Losing it changes the shape of the addressable market even as demand elsewhere keeps growing.
The competitive consequence is the more important part: a restricted market is where domestic chipmakers iterate fastest, with guaranteed volume and no foreign competitor at the high end.
Nvidia has not framed this as permanent, and the policy environment is the variable that would determine any reversal.
What is harder to rebuild: market share or supply chain? $NVDA #Nvidia #AI #Chips #BinanceSquare
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Nvidia’s backing faces a credit test: neoclouds take the first hitThe sharpest chill in this week’s AI narrative didn’t come from model evaluations, but from credit markets. Nvidia’s disclosures point to roughly $36 billion in off-balance-sheet backing for neoclouds, while stories are also circulating about guarantees of up to around $105 billion for large data center projects. In normal times, it looks like “free insurance.” When the weather turns, people start putting a price on that insurance.
CoreWeave, Nebius, and IREN have all fallen by more than 30% in October. For CoreWeave, bond prices have dropped to a discount and CDS spreads have widened to levels suggesting roughly a 60% five-year probability of default. The exact figure depends on the model, but the direction is clear: credit markets are getting skeptical about the “customers who sell the shovels.”
Nvidia’s backing faces a credit test: neoclouds take the first hit
The sharpest chill in this week’s AI narrative didn’t come from model evaluations, but from credit markets. Nvidia’s disclosures point to roughly $36 billion in off-balance-sheet backing for neoclouds, while stories are also circulating about guarantees of up to around $105 billion for large data center projects. In normal times, it looks like “free insurance.” When the weather turns, people start putting a price on that insurance.
CoreWeave, Nebius, and IREN have all fallen by more than 30% in October. For CoreWeave, bond prices have dropped to a discount and CDS spreads have widened to levels suggesting roughly a 60% five-year probability of default. The exact figure depends on the model, but the direction is clear: credit markets are getting skeptical about the “customers who sell the shovels.”
CoreWeave, Nebius, and IREN have all fallen by more than 30% in October. For CoreWeave, bond prices have dropped to a discount and CDS spreads have widened to levels suggesting roughly a 60% five-year probability of default. The exact figure depends on the model, but the direction is clear: credit markets are getting skeptical about the “customers who sell the shovels.”
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NVIDIA (NVDA) is around $210.96, down about 0.6% today and nearly 7.5% this month.
The AI trade is cooling, but the business behind it still has momentum: NVIDIA reported $96.2B in quarterly revenue, up 106% year over year. The question is whether demand can keep outpacing rising expectations.
My lean: cautiously bullish on the pullback, while watching for signs that AI spending is translating into continued growth.
Is this a buying opportunity—or a warning that the AI trade is crowded?
#NVDA #NVIDIA #Aİ
NVIDIA (NVDA) is around $210.96, down about 0.6% today and nearly 7.5% this month.
The AI trade is cooling, but the business behind it still has momentum: NVIDIA reported $96.2B in quarterly revenue, up 106% year over year. The question is whether demand can keep outpacing rising expectations.
My lean: cautiously bullish on the pullback, while watching for signs that AI spending is translating into continued growth.
Is this a buying opportunity—or a warning that the AI trade is crowded?
#NVDA #NVIDIA #Aİ
The AI trade is cooling, but the business behind it still has momentum: NVIDIA reported $96.2B in quarterly revenue, up 106% year over year. The question is whether demand can keep outpacing rising expectations.
My lean: cautiously bullish on the pullback, while watching for signs that AI spending is translating into continued growth.
Is this a buying opportunity—or a warning that the AI trade is crowded?
#NVDA #NVIDIA #Aİ
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The $NVDA conference in Berlin featured some rather unusual scenes.
Beyond the frenzy surrounding Jensen Huang, people stopped to watch robotic ducks in action.
There was also time to talk about the pressure the neocloud sector is feeling as artificial intelligence advances.
It’s curious to see how they mix technical presentations with robots that look like toys.
Did you imagine an event like this would have an atmosphere like that?
#Nvidia #IA #GTC
The $NVDA conference in Berlin featured some rather unusual scenes.
Beyond the frenzy surrounding Jensen Huang, people stopped to watch robotic ducks in action.
There was also time to talk about the pressure the neocloud sector is feeling as artificial intelligence advances.
It’s curious to see how they mix technical presentations with robots that look like toys.
Did you imagine an event like this would have an atmosphere like that?
#Nvidia #IA #GTC
Beyond the frenzy surrounding Jensen Huang, people stopped to watch robotic ducks in action.
There was also time to talk about the pressure the neocloud sector is feeling as artificial intelligence advances.
It’s curious to see how they mix technical presentations with robots that look like toys.
Did you imagine an event like this would have an atmosphere like that?
#Nvidia #IA #GTC
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#NVDA 👀CEO #NVIDIA Jensen Huang is ready to pay $8 billion because of a new tax on billionaires. “The more you earn, the more you pay,” he said. 💰
Such calmness from a CEO about enormous expenses is the best indicator of confidence in his business.
From here, everyone can draw their own conclusions and do their own analysis. I’m just showing what I see in the market.
Maybe we’ll have to wait a while, or maybe they’ll pump it as soon as tomorrow. 😂
$NVDAB
#NVDA 👀CEO #NVIDIA Jensen Huang is ready to pay $8 billion because of a new tax on billionaires. “The more you earn, the more you pay,” he said. 💰
Such calmness from a CEO about enormous expenses is the best indicator of confidence in his business.
From here, everyone can draw their own conclusions and do their own analysis. I’m just showing what I see in the market.
Maybe we’ll have to wait a while, or maybe they’ll pump it as soon as tomorrow. 😂
$NVDAB
Such calmness from a CEO about enormous expenses is the best indicator of confidence in his business.
From here, everyone can draw their own conclusions and do their own analysis. I’m just showing what I see in the market.
Maybe we’ll have to wait a while, or maybe they’ll pump it as soon as tomorrow. 😂
$NVDAB
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Article
Jensen Huang Reaffirms His $4 Trillion AI Spending ProjectionNvidia CEO Jensen Huang has reaffirmed his projection that AI spending will reach $4 trillion, according to coverage of his recent remarks.
The number is a cumulative view of the infrastructure build-out needed to run AI at scale, not a revenue forecast for any single company.
The figure matters because it sets the bar for what chipmakers, data center operators and power providers are planning against. If the build-out tracks that path, the demand for accelerators and memory stays elevated.
It also sets up a wide gap between the projection and what is actually being spent today, which is where the debate lives.
Huang has made versions of this argument repeatedly, and the market has learned to treat it as a directional signal rather than a forecast.
Is $4 trillion realistic for AI infrastructure, or aspirational framing? $NVDA #Nvidia #AI #JensenHuang #BinanceSquare
Jensen Huang Reaffirms His $4 Trillion AI Spending Projection
Nvidia CEO Jensen Huang has reaffirmed his projection that AI spending will reach $4 trillion, according to coverage of his recent remarks.
The number is a cumulative view of the infrastructure build-out needed to run AI at scale, not a revenue forecast for any single company.
The figure matters because it sets the bar for what chipmakers, data center operators and power providers are planning against. If the build-out tracks that path, the demand for accelerators and memory stays elevated.
It also sets up a wide gap between the projection and what is actually being spent today, which is where the debate lives.
Huang has made versions of this argument repeatedly, and the market has learned to treat it as a directional signal rather than a forecast.
Is $4 trillion realistic for AI infrastructure, or aspirational framing? $NVDA #Nvidia #AI #JensenHuang #BinanceSquare
The number is a cumulative view of the infrastructure build-out needed to run AI at scale, not a revenue forecast for any single company.
The figure matters because it sets the bar for what chipmakers, data center operators and power providers are planning against. If the build-out tracks that path, the demand for accelerators and memory stays elevated.
It also sets up a wide gap between the projection and what is actually being spent today, which is where the debate lives.
Huang has made versions of this argument repeatedly, and the market has learned to treat it as a directional signal rather than a forecast.
Is $4 trillion realistic for AI infrastructure, or aspirational framing? $NVDA #Nvidia #AI #JensenHuang #BinanceSquare
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Article
Nvidia's Next Business May Be A $2,000 Per-GPU Annual FeeNvidia has discussed charging around $2,000 per GPU per year for software that runs AI agents on what it calls AI factories.
Details remain unclear about exactly which workloads and deployments the fee would apply to, and whether existing customers would be grandfathered in.
If it holds, this would shift part of Nvidia's revenue from one-time hardware sales toward recurring software revenue tied to the installed base of chips.
For customers, the calculus changes: the GPU becomes the entry ticket and the software becomes the ongoing subscription.
Nvidia has not confirmed the pricing publicly, so treat the $2,000 figure as reported rather than official.
Would you pay a per-GPU annual fee if it meant your agents ran reliably at scale? $NVDA #Nvidia #AI #Semiconductors #BinanceSquare
Nvidia's Next Business May Be A $2,000 Per-GPU Annual Fee
Nvidia has discussed charging around $2,000 per GPU per year for software that runs AI agents on what it calls AI factories.
Details remain unclear about exactly which workloads and deployments the fee would apply to, and whether existing customers would be grandfathered in.
If it holds, this would shift part of Nvidia's revenue from one-time hardware sales toward recurring software revenue tied to the installed base of chips.
For customers, the calculus changes: the GPU becomes the entry ticket and the software becomes the ongoing subscription.
Nvidia has not confirmed the pricing publicly, so treat the $2,000 figure as reported rather than official.
Would you pay a per-GPU annual fee if it meant your agents ran reliably at scale? $NVDA #Nvidia #AI #Semiconductors #BinanceSquare
Details remain unclear about exactly which workloads and deployments the fee would apply to, and whether existing customers would be grandfathered in.
If it holds, this would shift part of Nvidia's revenue from one-time hardware sales toward recurring software revenue tied to the installed base of chips.
For customers, the calculus changes: the GPU becomes the entry ticket and the software becomes the ongoing subscription.
Nvidia has not confirmed the pricing publicly, so treat the $2,000 figure as reported rather than official.
Would you pay a per-GPU annual fee if it meant your agents ran reliably at scale? $NVDA #Nvidia #AI #Semiconductors #BinanceSquare
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🚨 $NVDA
{future}(NVDAUSDT)
Tomorrow’s Market Analysis: The $210 Defense Battle! Will AI Chip Stocks Rebound or Keep Falling?
📊 Nvidia closed at $210.96 last Friday, down 0.59%. Tomorrow’s key question isn’t just AI demand—it’s whether the market is still willing to pay for high AI growth!
🔥 A Look at Three Key Developments
1️⃣ AI demand remains strong, supporting Nvidia’s fundamentals
Nvidia’s Blackwell and next-generation Rubin platforms remain important growth drivers for the expansion of AI data centers. The market is also closely watching the AI investment plans of major cloud companies, which will affect expectations for Nvidia’s future orders and revenue.
2️⃣ Concerns over AI capital spending are growing, putting tech stocks under pressure
Last Thursday, the Nasdaq fell about 2.6%, and semiconductor stocks faced significant selling pressure. Meta’s AI investment costs have raised concerns in the market, and investors are paying closer attention to the returns on AI spending—not just revenue growth.
3️⃣ Oil prices and interest rates pose additional risks
Recently, rising oil prices have fueled inflation concerns, while the yield on 10-year U.S. Treasury bonds is nearing 5%. If interest rates continue to rise, high-valuation tech stocks could face greater valuation pressure.
📈 10/26 NVDA Long/Short Trading Plan
🟢 Long Strategy
Support to watch: $210–211
Entry condition: Break above $214 with rising volume
First target: $217
Second target: $220
Reference stop-loss: Below $211
🔴 Short Strategy
Entry condition: Break decisively below $210 and fail to reclaim it on a rebound
First target: $207
Second target: $204
Reference stop-loss: Above $213
But if $210 fails to hold while the Nasdaq and semiconductor sector weaken at the same time, beware of a pullback to $207 or even lower.
⚠️ This week, the market will also be watching earnings from major tech companies and the Fed’s interest rate decision. Intraday volatility may increase around these announcements, so avoid blindly chasing prices with oversized positions.
👇 Click below to trade, follow me, and stay up to date on more NVDA, SOXL, and semiconductor market analysis!
#NVDA #NVIDIA #Aİ
🚨 $NVDA
Tomorrow’s Market Analysis: The $210 Defense Battle! Will AI Chip Stocks Rebound or Keep Falling?
📊 Nvidia closed at $210.96 last Friday, down 0.59%. Tomorrow’s key question isn’t just AI demand—it’s whether the market is still willing to pay for high AI growth!
🔥 A Look at Three Key Developments
1️⃣ AI demand remains strong, supporting Nvidia’s fundamentals
Nvidia’s Blackwell and next-generation Rubin platforms remain important growth drivers for the expansion of AI data centers. The market is also closely watching the AI investment plans of major cloud companies, which will affect expectations for Nvidia’s future orders and revenue.
2️⃣ Concerns over AI capital spending are growing, putting tech stocks under pressure
Last Thursday, the Nasdaq fell about 2.6%, and semiconductor stocks faced significant selling pressure. Meta’s AI investment costs have raised concerns in the market, and investors are paying closer attention to the returns on AI spending—not just revenue growth.
3️⃣ Oil prices and interest rates pose additional risks
Recently, rising oil prices have fueled inflation concerns, while the yield on 10-year U.S. Treasury bonds is nearing 5%. If interest rates continue to rise, high-valuation tech stocks could face greater valuation pressure.
📈 10/26 NVDA Long/Short Trading Plan
🟢 Long Strategy
Support to watch: $210–211
Entry condition: Break above $214 with rising volume
First target: $217
Second target: $220
Reference stop-loss: Below $211
🔴 Short Strategy
Entry condition: Break decisively below $210 and fail to reclaim it on a rebound
First target: $207
Second target: $204
Reference stop-loss: Above $213
But if $210 fails to hold while the Nasdaq and semiconductor sector weaken at the same time, beware of a pullback to $207 or even lower.
⚠️ This week, the market will also be watching earnings from major tech companies and the Fed’s interest rate decision. Intraday volatility may increase around these announcements, so avoid blindly chasing prices with oversized positions.
👇 Click below to trade, follow me, and stay up to date on more NVDA, SOXL, and semiconductor market analysis!
#NVDA #NVIDIA #Aİ
Tomorrow’s Market Analysis: The $210 Defense Battle! Will AI Chip Stocks Rebound or Keep Falling?
📊 Nvidia closed at $210.96 last Friday, down 0.59%. Tomorrow’s key question isn’t just AI demand—it’s whether the market is still willing to pay for high AI growth!
🔥 A Look at Three Key Developments
1️⃣ AI demand remains strong, supporting Nvidia’s fundamentals
Nvidia’s Blackwell and next-generation Rubin platforms remain important growth drivers for the expansion of AI data centers. The market is also closely watching the AI investment plans of major cloud companies, which will affect expectations for Nvidia’s future orders and revenue.
2️⃣ Concerns over AI capital spending are growing, putting tech stocks under pressure
Last Thursday, the Nasdaq fell about 2.6%, and semiconductor stocks faced significant selling pressure. Meta’s AI investment costs have raised concerns in the market, and investors are paying closer attention to the returns on AI spending—not just revenue growth.
3️⃣ Oil prices and interest rates pose additional risks
Recently, rising oil prices have fueled inflation concerns, while the yield on 10-year U.S. Treasury bonds is nearing 5%. If interest rates continue to rise, high-valuation tech stocks could face greater valuation pressure.
📈 10/26 NVDA Long/Short Trading Plan
🟢 Long Strategy
Support to watch: $210–211
Entry condition: Break above $214 with rising volume
First target: $217
Second target: $220
Reference stop-loss: Below $211
🔴 Short Strategy
Entry condition: Break decisively below $210 and fail to reclaim it on a rebound
First target: $207
Second target: $204
Reference stop-loss: Above $213
But if $210 fails to hold while the Nasdaq and semiconductor sector weaken at the same time, beware of a pullback to $207 or even lower.
⚠️ This week, the market will also be watching earnings from major tech companies and the Fed’s interest rate decision. Intraday volatility may increase around these announcements, so avoid blindly chasing prices with oversized positions.
👇 Click below to trade, follow me, and stay up to date on more NVDA, SOXL, and semiconductor market analysis!
#NVDA #NVIDIA #Aİ
1
31
NVIDIA Unveils Vera Rubin Architecture to Accelerate AI Factory Expansion
At the OCP Global Summit, NVIDIA announced that the Vera Rubin architecture is now available worldwide and introduced new software components to support the DSX AI Factory platform.#AI #NVIDIA
NVIDIA Unveils Vera Rubin Architecture to Accelerate AI Factory Expansion
At the OCP Global Summit, NVIDIA announced that the Vera Rubin architecture is now available worldwide and introduced new software components to support the DSX AI Factory platform.#AI #NVIDIA
At the OCP Global Summit, NVIDIA announced that the Vera Rubin architecture is now available worldwide and introduced new software components to support the DSX AI Factory platform.#AI #NVIDIA
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The high cost of robot training data has taken another hit from Nvidia.
According to reports, Nvidia has open-sourced its data engine Flora, claiming it can bring the cost of annotating robot videos down from about $88 to around $0.72—roughly 125 times cheaper than the purported GPT-6 Astra approach. The process broadly involves segmenting time periods, describing actions, then evaluating execution and outcomes. It has reportedly been used to train GR00T, and can annotate up to around 200,000 hours of video per day across a large number of GPUs.
How to read this: An open-source entry point lowers the barrier to access, but real-world adoption will still depend on whether annotation quality and gains in downstream models live up to the claims. If the data bottleneck in robotics and embodied AI is eased, training cycles could speed up. Keep an eye on reproducible benchmarks first; don’t get carried away by the “125 times cheaper” headline.
#Nvidia #Flora #机器人 #OpenSource
The high cost of robot training data has taken another hit from Nvidia.
According to reports, Nvidia has open-sourced its data engine Flora, claiming it can bring the cost of annotating robot videos down from about $88 to around $0.72—roughly 125 times cheaper than the purported GPT-6 Astra approach. The process broadly involves segmenting time periods, describing actions, then evaluating execution and outcomes. It has reportedly been used to train GR00T, and can annotate up to around 200,000 hours of video per day across a large number of GPUs.
How to read this: An open-source entry point lowers the barrier to access, but real-world adoption will still depend on whether annotation quality and gains in downstream models live up to the claims. If the data bottleneck in robotics and embodied AI is eased, training cycles could speed up. Keep an eye on reproducible benchmarks first; don’t get carried away by the “125 times cheaper” headline.
#Nvidia #Flora #机器人 #OpenSource
According to reports, Nvidia has open-sourced its data engine Flora, claiming it can bring the cost of annotating robot videos down from about $88 to around $0.72—roughly 125 times cheaper than the purported GPT-6 Astra approach. The process broadly involves segmenting time periods, describing actions, then evaluating execution and outcomes. It has reportedly been used to train GR00T, and can annotate up to around 200,000 hours of video per day across a large number of GPUs.
How to read this: An open-source entry point lowers the barrier to access, but real-world adoption will still depend on whether annotation quality and gains in downstream models live up to the claims. If the data bottleneck in robotics and embodied AI is eased, training cycles could speed up. Keep an eye on reproducible benchmarks first; don’t get carried away by the “125 times cheaper” headline.
#Nvidia #Flora #机器人 #OpenSource
13
NVIDIA’s European strategy revealed: From digital discovery to physical operations
NVIDIA has launched a range of innovative applications in European retail, including Shopify’s post-training models, Zooplus’s product discovery stack, and Photoroom’s image-editing API, showcasing the power of open models and physical intelligence.#NVIDIA #TechAnalysis
NVIDIA’s European strategy revealed: From digital discovery to physical operations
NVIDIA has launched a range of innovative applications in European retail, including Shopify’s post-training models, Zooplus’s product discovery stack, and Photoroom’s image-editing API, showcasing the power of open models and physical intelligence.#NVIDIA #TechAnalysis
NVIDIA has launched a range of innovative applications in European retail, including Shopify’s post-training models, Zooplus’s product discovery stack, and Photoroom’s image-editing API, showcasing the power of open models and physical intelligence.#NVIDIA #TechAnalysis
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Bullish
$NVDAB
NVIDIA’s AI infrastructure is proving to be a durable, valuable asset with strong long-term investment potential. As new AI applications and workloads continue to emerge, more businesses rely on NVIDIA’s platform for computing power and productivity. This growing adoption increases demand for its GPUs and AI systems, potentially supporting sustainable revenue growth. The key takeaway is that #NVIDIA infrastructure is not just benefiting from today’s AI boom; its continued usefulness across multiple industries could help maintain its value and drive long-term business growth.
{spot}(NVDABUSDT)
$NVDAB
NVIDIA’s AI infrastructure is proving to be a durable, valuable asset with strong long-term investment potential. As new AI applications and workloads continue to emerge, more businesses rely on NVIDIA’s platform for computing power and productivity. This growing adoption increases demand for its GPUs and AI systems, potentially supporting sustainable revenue growth. The key takeaway is that #NVIDIA infrastructure is not just benefiting from today’s AI boom; its continued usefulness across multiple industries could help maintain its value and drive long-term business growth.
NVIDIA’s AI infrastructure is proving to be a durable, valuable asset with strong long-term investment potential. As new AI applications and workloads continue to emerge, more businesses rely on NVIDIA’s platform for computing power and productivity. This growing adoption increases demand for its GPUs and AI systems, potentially supporting sustainable revenue growth. The key takeaway is that #NVIDIA infrastructure is not just benefiting from today’s AI boom; its continued usefulness across multiple industries could help maintain its value and drive long-term business growth.
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NVIDIA Earth-2 model upgrade brings more accurate weather forecasts to Europe
NVIDIA Earth-2 adds the StormScope EU model for more accurate short-term weather forecasts. Widely used by organizations such as AXA and Vaisala Xweather, it supports regional hurricane risk assessment and air quality modeling.#技术分析派 #NVIDIA
NVIDIA Earth-2 model upgrade brings more accurate weather forecasts to Europe
NVIDIA Earth-2 adds the StormScope EU model for more accurate short-term weather forecasts. Widely used by organizations such as AXA and Vaisala Xweather, it supports regional hurricane risk assessment and air quality modeling.#技术分析派 #NVIDIA
NVIDIA Earth-2 adds the StormScope EU model for more accurate short-term weather forecasts. Widely used by organizations such as AXA and Vaisala Xweather, it supports regional hurricane risk assessment and air quality modeling.#技术分析派 #NVIDIA
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Jensen Huang has just pushed back against rumors of oversupply.
The CEO of $NVDA says he sees no signs of a saturated market by 2029.
According to him, demand for memory will remain so high that there will always be a need for more.
This comes just as stocks in the sector have suffered significant declines this week.
What do you think of his stance on future demand?
#Nvidia #Tech
Jensen Huang has just pushed back against rumors of oversupply.
The CEO of $NVDA says he sees no signs of a saturated market by 2029.
According to him, demand for memory will remain so high that there will always be a need for more.
This comes just as stocks in the sector have suffered significant declines this week.
What do you think of his stance on future demand?
#Nvidia #Tech
The CEO of $NVDA says he sees no signs of a saturated market by 2029.
According to him, demand for memory will remain so high that there will always be a need for more.
This comes just as stocks in the sector have suffered significant declines this week.
What do you think of his stance on future demand?
#Nvidia #Tech
22
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