doc2016
6 hours ago
the quantum computer techs combined qubits applied to the same job are said to impart an improvement in qubit reliability. it would therefore be necessary to have an ip which allows collaborate work/entanglement of their work/platform/algo.........enter nvidia cuda-q. i think this is jensen's genius. of course you need nvidia to manage the collaborative efforts of the distributed quantum computers, supercomputers, asics, gpu, sensors, etc. a global network with off world assets as well/scalable and flexible and secure. usa has stargate, japan has their, china has alibaba, eu has theirs, each node can be a node of nodes for collaborative work as our world spins on it's axis. wags.
doc2016
12 hours ago
this am articles on google and softbank investing into quera, neutral atoms, but are they losing faith in other quantum ip , like ionq? but now i asked ai about hybrid quantum computing and so:
"You're absolutely right. A hybrid quantum computing approach, using different types of QPUs in the same environment, has the potential to significantly enhance qubit informational state and function. It's a very promising direction in quantum computing research. Here's a breakdown of why:
Advantages of a Hybrid Approach:
Leveraging Strengths: Different QPU technologies have different strengths. Some might excel at maintaining coherence (how long qubits retain their quantum properties), while others might be better at performing specific types of quantum operations or have a higher connectivity between qubits. A hybrid approach allows you to use the best tool for the job. For example:
Trapped Ions: Excellent coherence, but can be slower for some operations.
Superconducting Qubits: Faster gate speeds, but more susceptible to decoherence.
Photonic Qubits: Good for long-distance communication and some specialized algorithms.
Mitigating Weaknesses: Each QPU technology also has weaknesses. By combining them, you can potentially compensate for these limitations. For instance, if one type of qubit has low connectivity, you might use another type with higher connectivity to facilitate communication within the quantum circuit.
Fault Tolerance: A hybrid approach could be crucial for achieving fault-tolerant quantum computing. Different qubit types might have different error characteristics. By combining them, it might be possible to develop more robust error correction strategies.
Expanding Algorithm Capabilities: Some quantum algorithms are better suited to certain types of qubits. A hybrid system could allow researchers to explore a wider range of algorithms and potentially develop new ones that are tailored to the specific strengths of the combined QPUs.
Modular Design: A hybrid approach lends itself to a modular design. You can add or upgrade different QPUs as the technology advances, creating a more flexible and scalable quantum computing system.
Challenges of a Hybrid Approach:
Interfacing Different Technologies: One of the biggest challenges is developing efficient interfaces between different QPU types. You need to be able to transfer quantum information reliably between them, which can be technically complex.
Control and Orchestration: Managing and controlling a hybrid system with multiple QPU technologies is a significant engineering challenge. You need sophisticated control systems to coordinate the operations of the different QPUs.
Error Correction: Developing error correction strategies for a hybrid system can be more complex than for a single-technology system.
Cost and Complexity: Building and maintaining a hybrid quantum computing system is likely to be more expensive and complex than building a single-technology system.
Examples of Hybrid Approaches:
Combining Trapped Ions and Superconducting Qubits: This combination could leverage the high coherence of trapped ions with the fast gate speeds of superconducting qubits.
Integrating Photonic Qubits for Communication: Photonic qubits could be used to connect different quantum processors, enabling the creation of larger, distributed quantum computers.
In summary:
The hybrid quantum computing approach is a promising path toward building more powerful and versatile quantum computers. While there are significant challenges to overcome, the potential benefits in terms of enhanced qubit performance and expanded algorithm capabilities make it a very active area of research. It's likely that future quantum computers will incorporate elements of multiple QPU technologies to achieve their full potential."
doc2016
1 day ago
how to use quantum/ai supercomputer........manage a tokamak reactor to make plasma from mining substrates and then use electrolysis to separate the desired metals sequentially, including gold, silver, al, iron for steel, copper, etc? if the alcoa elysis process/electrode ip is used, it's patented and uses no carbon and produces o2 instead of co2. the reason this would work where previous trials failed is electromagnetic plasma confinement developed for fusion reactor work, wags.
ever see gold rush and parker's trail? if this could be done within a money making margins and better, no more taxes need to be collected. it'd be like the citizens of the state of alaska enjoy? and then some. but you could live in az/nv/fld/ca/txs/or wherever you desired.
liberal media's are all complaining about the potential inflation usa will experience, but no one is mentioning the potential gain from developing the ip which can be used to make purer aluminum/iron/steel/etc. metamaterils and quantum effects and advancement from the integration of classical and quantum physics.
Jetmek_03052
1 day ago
Investment Alert
News Story for NVIDIA Corp
Semtech Stock Sinks After Nvidia Configuration Change
Dow Jones Newswires February 10, 2025 01:55:00 PM ET
Shares of Semtech are on track for their worst day in decades after a change at Nvidia that prompted the company to reduce its guidance.
The stock dropped 31% to $37.67 in the morning trading session, putting it on pace for its biggest single-day decrease since 1986.
The chipmaker said after the bell on Friday that it expects sales of its CopperEdge products, used in active copper cables, to be lower than the $50 million floor it previously targeted for fiscal 2026 based on feedback from a major customer.
Benchmark analyst Cody Acree said that customer is Nvidia, which is likely pulling back support for a server rack configuration that used Semtech's cable products. Nvidia is coming out with a new processing unit and may be making the change to address heating issues, he said.
"We believe this decision was made as Nvidia needed to prioritize its resources to ensure a smooth generational transition to a system that we have heard has been struggling with overheating issues," Acree said in a research note.
While this reduces the total addressable market for Semtech's active copper cable-based designs, Nvidia is still ramping its current GPU with servers that use the active copper cables, he said. And Meta Platforms continues to use the configuration that requires the cables, the analyst said. He maintains a buy rating on the stock.
"While today's announcement is disappointing, we don't believe it is as devastating to the company's business as initially indicated in the soft after-market trading," Acree said on Friday.
4retire
1 day ago
NVDA
The practical implications are that if you want to host a basic website for instance, you can sign up for a Cloudflare (NET) account, pay for the domain registration fees, and then connect to your Github repository. This repository would host all your website files, served at blazingly fast speeds, with no database request overhead or security risks that come from managing your own hardware. This approach, in addition to being more secure and more cost-effective to traditional web hosting for some applications, is also highly scalable as users pay for their usage.
As DeepSeek has shown, the cost of running AI models can be reduced dramatically, as more companies can now experiment with and deploy AI models without being held back by prohibitive capital outlays. Nvidia's DGX cloud dovetails with this emergence by further abstracting away the hardware complexities.
Although Nvidia has an established dominance in hardware, it also has an overwhelming presence in the cloud. 93% of GPU-accelerated instances are powered by Nvidia hardware. The main cause for Nvidia's dominance in this area is that cloud service providers such as Microsoft (MSFT) Azure and Google Cloud (GOOG) offer Nvidia-powered instances.
rolvram
1 day ago
Benchmark Adjusts Price Target on NVIDIA to $195 From $190, Maintains Buy Rating
09:55:26 AM ET, 02/10/2025 - MT Newswires
09:55 AM EST, 02/10/2025 (MT Newswires) -- NVIDIA (NVDA) has an average rating of buy and mean price target of $174.75, according to analysts polled by FactSet.
(MT Newswires covers equity, commodity and economic research from major banks and research firms in North America, Asia and Europe. Research providers may contact us here: https://www.mtnewswires.com/contact-us)
Price: 134.03, Change: +4.19, Percent Change: +3.22
rolvram
2 days ago
Prediction: Nvidia Stock Is Going to Soar After Feb. 26
By Harsh Chauhan – Feb 5, 2025 at 7:43AM
Key Points
Nvidia stock has started 2025 badly, but it may be able to regain its mojo later this month.
The chipmaker's earnings report is due on Feb. 26, and recent developments in the AI infrastructure space suggest that it could overcome the negativity that has been surrounding it of late.
10 stocks we like better than Nvidia
NASDAQ: NVDA
Nvidia
Nvidia Stock Quote
Market Cap
$3.2T
Today's Change
(0.90%) $1.16
Current Price
$129.84
Price as of February 7, 2025, 4:00 p.m. ET
Nvidia (NVDA 0.90%) has gotten off to a bad start on the stock market in 2025, losing more than 10% of its value as of this writing, with Chinese artificial intelligence (AI) start-up DeepSeek's launch of a low-cost but capable AI model playing a key role in the semiconductor giant's troubles.
When DeepSeek claimed that it spent just $6 million to train its R1 reasoning model that's capable of competing with OpenAI's o1 reasoning model, AI stocks in the U.S. took a big beating. Nvidia stock was one of the biggest victims of the sell-off, dropping 17% on Jan. 27 after it emerged that DeepSeek overtook ChatGPT's downloads on the Apple app store in the U.S.
Collapse
NASDAQ: NVDA
Nvidia
Today's Change
(0.90%) $1.16
Current Price
$129.84
YTD
1w
1m
3m
6m
1y
5y
Price
VS S&P
NVDA
Key Data Points
Market Cap
$3.2T
Day's Range
$125.00 - $130.37
52wk Range
$66.25 - $153.13
Volume
228,186,298
Avg Vol
244,276,423
Gross Margin
75.86%
Dividend Yield
0.03%
DeepSeek's low-cost model sparked concerns about major cloud computing companies and governments reducing their demand for the AI chips Nvidia sells. However, a closer look at recent developments in the AI space suggests that the spending on AI chips could continue to head higher, opening the possibility of Nvidia stock regaining its mojo once it releases its fiscal 2025 fourth-quarter results on Feb. 26.
Let's look at why Nvidia could offer a bright update about the state of AI spending later this month along with its quarterly report.
Nvidia could win big from this project thanks to its solid share of AI chips
Over the last few years, tech giants and governments around the world have poured a lot of money into the development of AI infrastructure, and President Donald Trump gave AI spending prospects a massive boost last month.
On Tuesday, Jan. 21, Trump announced at the White House that SoftBank, OpenAI, and Oracle (ORCL 1.22%) are forming a joint venture that plans to invest $100 billion in AI infrastructure. The joint venture, known as Stargate, is eventually planning to spend up to a whopping $500 billion on building AI infrastructure in the U.S. over the next four years.
Stargate's first AI data center is already under construction in Texas, according to Oracle chairman Larry Ellison. The joint venture is expected to construct 20 data centers, creating an estimated 100,000 jobs.
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In a post announcing the Stargate project, OpenAI pointed out that the initial funding will be provided by SoftBank, OpenAI, Oracle, and Abu Dhabi's AI-focused investment company, MGX. The post further highlighted that Nvidia is going to be among the "initial technology partners" in Stargate.
Nvidia has been at the forefront of the AI revolution with its powerful graphics processing units (GPUs) based on the Ampere architecture that helped OpenAI train ChatGPT. It has kept pushing the envelope in the AI accelerator market, churning out more powerful chips in the past three years based on its Hopper and Blackwell architectures.
This explains why Nvidia has maintained a solid grip on the AI chip market with an estimated share of 90%. Given that Nvidia has created a technology advantage over rivals in the AI chip market, it could remain the dominant force in this space. As Nvidia's GPUs are the basic building blocks of AI data centers given their ability to perform massive calculations simultaneously, allowing companies to train and deploy AI models quickly, Stargate's ambitious investment plan should ideally help improve the chipmaker's addressable market.
For instance, Oracle has been relying on Nvidia's GPUs to create AI infrastructure to rent out to customers so that they can train AI models in the cloud. In September last year, Ellison remarked that one of Oracle's largest data centers "is 800 megawatts, and it will contain acres of NVIDIA GP clusters able to train the world's largest AI models." This was followed by a remark from Oracle CEO Safra Catz on the December 2024 earnings conference call that the company "delivered the world's largest and fastest AI supercomputer, scaling up to 65,000 Nvidia H200 GPUs."
Oracle is planning to deploy an additional 35 cloud regions around the globe in addition to the 17 it already has. It won't be surprising to see the company's appetite for Nvidia's GPUs increasing. More importantly, as Nvidia has been working with its supply chain partners to increase the output of its AI GPUs in 2025, it should be in a position to meet the higher demand for its chips that's likely to arise following Stargate.
Meanwhile, the likes of Meta Platforms and Microsoft aren't going to curtail their spending on AI infrastructure following DeepSeek's breakthrough. Both companies believe that heavy AI investments are required to support the growing demand for AI applications, thanks to the potential arrival of more efficient models as demonstrated by DeepSeek. Dutch semiconductor equipment giant ASML suggested something similar after the company witnessed solid growth in orders and received way more bookings than Wall Street was anticipating.
All this suggests that the AI spending environment could remain robust, and that could help Nvidia deliver solid results and guidance later this month.
Stronger-than-expected growth could lead to more upside
Analysts are currently expecting Nvidia's revenue in fiscal 2026 (which has just begun) to increase 52% to just over $196 billion, followed by a 21% increase in fiscal 2027.
NVDA Revenue Estimates for Current Fiscal Year Chart
NVDA Revenue Estimates for Current Fiscal Year data by YCharts
However, expect to see those estimates head higher in light of the above discussion, paving the way for more upside in Nvidia stock. It is worth noting that Nvidia's 12-month price target of $175, according to 66 analysts covering the stock, points toward 46% gains from current levels.
Nvidia's revenue estimates for both fiscal years 2026 and 2027 have jumped higher of late, a trend that could continue thanks to continued investments in AI. As a result, Nvidia's price target could also witness upward revisions.
So, investors who have been on the sidelines and are wondering if it is a good idea to buy shares of Nvidia following the stellar returns that the stock has delivered in the past couple of years can consider buying it right away as it can regain its mojo. The stock's forward earnings multiple of 23 is very attractive considering that the tech-laden Nasdaq-100 index has a forward earnings multiple of 27. That's why buying Nvidia right now could turn out to be a smart move as its healthy earnings growth momentum is likely to continue.
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