$NVIDIA (NVDA.US)$ Towards Quantum Day at GTC, the transition from GPU to quantum is being explored.
The transition from GPU to Computer in AI development holds great potential, but there are several important challenges.
Main challenges:
* Adaptation of algorithms:
* Quantum Computers cannot directly use GPU-based AI Algorithms due to their different computational principles.
* Specifically, the redesign of gradient descent, which is the basis of deep learning, is required.
* Hardware constraints:
* Current Quantum Computers are noisy, and large-scale calculations are unstable.
The number of qubits is limited and is insufficient for training large-scale neural networks.
The development of error correction technology is essential.
* Software and development environment:
Compared to the development environment for GPUs (such as CUDA), the environment for quantum computers is still developing.
Integration with existing AI frameworks has not progressed.
* Cost and Accessibility:
* Quantum Computers are very expensive, and the available environments are limited.
* Cloud services also have costs and limitations, ...
The transition from GPU to Computer in AI development holds great potential, but there are several important challenges.
Main challenges:
* Adaptation of algorithms:
* Quantum Computers cannot directly use GPU-based AI Algorithms due to their different computational principles.
* Specifically, the redesign of gradient descent, which is the basis of deep learning, is required.
* Hardware constraints:
* Current Quantum Computers are noisy, and large-scale calculations are unstable.
The number of qubits is limited and is insufficient for training large-scale neural networks.
The development of error correction technology is essential.
* Software and development environment:
Compared to the development environment for GPUs (such as CUDA), the environment for quantum computers is still developing.
Integration with existing AI frameworks has not progressed.
* Cost and Accessibility:
* Quantum Computers are very expensive, and the available environments are limited.
* Cloud services also have costs and limitations, ...
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$NVIDIA (NVDA.US)$ Consideration on the future of LLM's popularization by Datacenter.
1. Acceleration of business automation and changes in the labor market.
As LLM penetrates into companies, automation will progress in areas such as customer support, programming, content creation, and data analysis. This will lead to a decrease in some occupations, while increasing the demand for individuals with skills to utilize AI.
2. The extreme personalization
LLMs will learn individual preferences and behaviors, allowing them to provide optimized information and services for each user. More personalized experiences will become possible in areas like Mainland Education, healthcare, entertainment, and ETC.
3. The agentification of LLMs
Current LLMs are interactive tools, but in the future, they may function as "agents" that handle decision-making and execution on behalf of users. For example, it may become commonplace for AI to autonomously process emails or summarize meetings.
4. Monetization of AI and expansion of the economic sphere.
New business models utilizing LLMs are increasing, and the economic sphere centered around AI is expanding. For instance, AI-driven advertising optimization and subscription-based AI assistants...
1. Acceleration of business automation and changes in the labor market.
As LLM penetrates into companies, automation will progress in areas such as customer support, programming, content creation, and data analysis. This will lead to a decrease in some occupations, while increasing the demand for individuals with skills to utilize AI.
2. The extreme personalization
LLMs will learn individual preferences and behaviors, allowing them to provide optimized information and services for each user. More personalized experiences will become possible in areas like Mainland Education, healthcare, entertainment, and ETC.
3. The agentification of LLMs
Current LLMs are interactive tools, but in the future, they may function as "agents" that handle decision-making and execution on behalf of users. For example, it may become commonplace for AI to autonomously process emails or summarize meetings.
4. Monetization of AI and expansion of the economic sphere.
New business models utilizing LLMs are increasing, and the economic sphere centered around AI is expanding. For instance, AI-driven advertising optimization and subscription-based AI assistants...
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$NVIDIA (NVDA.US)$ First, to all the holders. I apologize for saying not to worry in the previous Post. I believe there are still no factors in NVDA's Q4 earnings report that would cause a decline. This drop is due to external factors from the market environment, and it is undeniable that the growth of AI will continue, with strong demand ahead. Each person's stance is different, and I think for those who have simply seen a decrease in unrealized gains, holding firmly is the correct approach. It has been tough since the beginning of this year with a drop greater than expected, but I believe that if the instability of external factors is resolved, the declines will definitely recover.
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Improvement of gross margin.
This guidance is amazing. The incredible gross margin slightly decreased in this financial report, but it will improve in the latter half of the year.
This guidance is amazing. The incredible gross margin slightly decreased in this financial report, but it will improve in the latter half of the year.
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$NVIDIA (NVDA.US)$ Overview of the financial results
Revenue: $39.33 billion (exceeding market estimates of $37.21 billion)
Adjusted EPS: $5.16 (exceeding market estimates of $4.64)
Datacenter segment revenue: $35.6 billion (significantly exceeding estimates of $32 billion)
Sales Financial Estimates for Q1 of 2026 (next quarter): $43 billion (a Bullish outlook exceeding market expectations).
Trends in gross profit margin.
Adjusted gross profit margin (Non-GAAP): 75.1% (down from 78.4% in the previous quarter).
Gross profit declined by 3%, but it's still impressive as it maintains at 75%.
If one wants to sell shorts, feel free to do so, but there is no need to worry about longs. It was a good financial result.
Revenue: $39.33 billion (exceeding market estimates of $37.21 billion)
Adjusted EPS: $5.16 (exceeding market estimates of $4.64)
Datacenter segment revenue: $35.6 billion (significantly exceeding estimates of $32 billion)
Sales Financial Estimates for Q1 of 2026 (next quarter): $43 billion (a Bullish outlook exceeding market expectations).
Trends in gross profit margin.
Adjusted gross profit margin (Non-GAAP): 75.1% (down from 78.4% in the previous quarter).
Gross profit declined by 3%, but it's still impressive as it maintains at 75%.
If one wants to sell shorts, feel free to do so, but there is no need to worry about longs. It was a good financial result.
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$NVIDIA (NVDA.US)$ I always lower it too much due to “concern.” The cancellation of a Microsoft data center lease agreement is also a change in the direction carried out due to a change in the lease destination or the enormous development of data centers in-house by Microsoft. In fact, there is also information that Microsoft itself denies that it is not a reduction in investment in data centers. The market is currently unstable due to inflationary trends due to Trump tariffs. After a few days at DeepSeek, demand for NVDA GPUs was huge, and the opinion that huge investment was not necessary disappeared. If the quarterly results and guidance are not mistaken, the stock price will move to ↑. If you don't see what's true, you'll be left behind in the market. The important thing is to stay.
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$Tesla (TSLA.US)$ The other day, I watched a video on YouTube about TSLA's road impression and was surprised by its high level of completeness. Since it doesn't have an internal combustion engine as a BEV, the barriers to entry are low, and I had only thought of it as a good toy for those who love new things, so it was shocking.
I live in Aichi Prefecture, the home of Toyota, so Toyota is definitely number one when it comes to Autos. It seems certain that the partnership with NVDA will accelerate the push towards Self-Driving Cars, but TSLA appears to have already reached a high level in body rigidity due to gigacast technology, chassis, and suspension, while the Software is evolving with updates.
The following advantages are listed below.
Self-Driving Car technology (FSD: Full Self-Driving).
Equipping with XAI's Grok.
Satellite Communications network via Starlink.
Infrastructure development for superchargers.
The combination of these elements creates an 'ecosystem' which is TSLA's greatest Weapon.
If these function comprehensively, then only the Battery remains.
Although Toyota leads in Solid State Battery technology, other companies are also developing Solid State Batteries, and whether Toyota can make a comeback in mass production is by no means easy...
I live in Aichi Prefecture, the home of Toyota, so Toyota is definitely number one when it comes to Autos. It seems certain that the partnership with NVDA will accelerate the push towards Self-Driving Cars, but TSLA appears to have already reached a high level in body rigidity due to gigacast technology, chassis, and suspension, while the Software is evolving with updates.
The following advantages are listed below.
Self-Driving Car technology (FSD: Full Self-Driving).
Equipping with XAI's Grok.
Satellite Communications network via Starlink.
Infrastructure development for superchargers.
The combination of these elements creates an 'ecosystem' which is TSLA's greatest Weapon.
If these function comprehensively, then only the Battery remains.
Although Toyota leads in Solid State Battery technology, other companies are also developing Solid State Batteries, and whether Toyota can make a comeback in mass production is by no means easy...
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$NVIDIA (NVDA.US)$ Since last year, Big Tech has invested heavily in LLM data centers, starting with the question of whether returns can be obtained, and there have also been fever issues and yield issues that have arisen many times. Also, comparisons between GPUs and ASICs mean that AVGO is the favorite over NVDA, and DeepSeek shock and concerns about the future potential of NVDA have come up many times, but in the end, it's safe to say that it was all an overreaction? I think so. It's still a bit high, but since there are no fundamentals issues, I think it's like a test because NVDA won alone. Feelings may be shaken when stock prices are sluggish, but let's all holders firmly hold NVDA and form assets 👍
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$NVIDIA (NVDA.US)$ It seems that AAPL is using BABA's AI for the iPhone in China, but thinking about whether the responses will be favorable to the Chinese Communist Party is a bit frightening. This kind of move likely has a negative impact on creating AI that is free from ideological bias. It was a thought-provoking case. I wonder what kind of GPU BABA uses and which company provides it.
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$NVIDIA (NVDA.US)$ There was a monthly sales announcement from TSMC. It's ideal for confirming the demand for cutting-edge semiconductors. It's good news for NVDA.
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