NVIDIA is taking the wraps off a new compact generative AI supercomputer, offering increased performance at a lower price with a software upgrade. The new NVIDIA Jetson Orin Nano Super Developer Kit, which fits in the palm of a hand, provides everyone from commercial AI developers to hobbyists ...

NVIDIA Unveils Its Most Affordable Generative AI Supercomputer | NVIDIA Blog

Skip to content · Gamingdeputy Japan · NVIDIA アプリは PC ゲームのパフォーマンスを低下させますか · December 16, 2024 by Lee Michaelis · 物語 浮上した 今週末、NVIDIA アプリが PC ゲームのパフォーマンスを低下させる可能性があること...

NVIDIA アプリは PC ゲームのパフォーマンスを低下させますか? - Gamingdeputy Japan

So, can you really get over 20FPS by simply uninstalling the NVIDIA App from your PC? Let's find out, shall we?

Does the NVIDIA App cripple your PC gaming performance?

Rigetti Computing has rallied over 300% last year and has established great partnerships and made interesting breakthroughs. Find out why RGTI stock is a Buy.

Rigetti Computing: The NVIDIA Of Quantum Computing (NASDAQ:RGTI) | Seeking Alpha

Infleqtion published groundbreaking work that used the NVIDIA CUDA-Q platform to both design and demonstrate an experiment with two of them.

Turn Down the Noise: CUDA-Q Enables Industry-First Quantum Computing Demo With Logical Qubits

Chinese regulators are investigating NVIDIA over a potential antitrust violation related to its acquisition of Mellanox Technologies in 2020.

Chinese regulators are investigating NVIDIA for potential antitrust violations

Trend Micro (TSE:4704) has recently demonstrated significant improvement in its operating margin, climbing from 18% to 24%, thanks to strategic cost management and a focus on high-margin areas like the Vision One platform. However, challenges remain, particularly in the consumer and SMB segments, ...

Trend Micro (TSE:4704) Enhances AI and Cybersecurity with NVIDIA and Google Alliances for Growth - Simply Wall St News

At AWS re:Invent, NVIDIA and Amazon Web Services are expanding what’s possible for developers and enterprises in the cloud.

Latest NVIDIA AI, Robotics and Quantum Computing Software Comes to AWS | NVIDIA Blog

NVIDIA

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Artificial Intelligence (AI) has reshaped industries, revolutionized workflows, and sparked innovation on a global scale. Recognizing the need to democratize AI knowledge and empower the next wave of tech innovators, NVIDIA, a global leader in GPU technology and AI research, has made a groundbreaking announcement. For a limited time only, NVIDIA is offering its premium AI courses for free. These courses, typically ranging between $30 and $90 each, cover cutting-edge topics in AI and accelerated computing. Whether you’re a beginner looking to take your first step into AI or an experienced professional eager to deepen your expertise, this is an opportunity you can’t afford to miss. What’s Included in NVIDIA’s Free AI Courses? NVIDIA, in collaboration with Evolving AI, has unlocked its treasure trove of educational resources. Let’s explore some of the courses that are now accessible for free: Accelerating End-to-End Data Science Workflows Original Price: $90 Duration: 6 hours What You’ll Learn: Learn how to prepare, analyze, and accelerate workflows using GPUs. This course dives into advanced machine learning techniques, clear visualizations, and how to make data-driven decisions faster. Deploying a Model for Inference at Production Scale Original Price: $30 Duration: 4 hours What You’ll Learn: Master techniques to scale machine learning models for large workloads, measure and optimize production throughput, and streamline deployments using NVIDIA Triton Inference Server. Fundamentals of Accelerated Computing with CUDA Python Original Price: $90 Duration: 8 hours What You’ll Learn: Learn to use Python and CUDA for accelerating code on GPUs. This course focuses on parallel computing, memory optimization, and custom program creation. Generative AI with Diffusion Models Original Price: $90 Duration: 8 hours What You’ll Learn: Delve into the exciting world of diffusion models for generative AI. Build models to generate images, simulate content, and explore applications in anomaly detection, recommendations, and more. Introduction to Transformer-Based Natural Language Processing Original Price: $30 Duration: 6 hours What You’ll Learn: Explore the transformers powering modern AI applications like chatbots. Use pre-trained models for text classification, question answering, and more. Prompt Engineering with LLaMA-2 Original Price: $30 Duration: 3 hours What You’ll Learn: Learn the art of prompt engineering to customize AI behavior effectively. Create chatbots, interactive tools, and leverage advanced prompt techniques. Getting Started with Deep Learning Original Price: $90 Duration: 8 hours What You’ll Learn: Train models for vision and language processing, improve accuracy with data augmentation, and apply transfer learning techniques. Getting Started with Accelerated Computing in CUDA C/C++ Original Price: $90 Duration: 8 hours What You’ll Learn: Use CUDA tools to speed up applications on GPUs, optimize performance, and resolve bottlenecks in complex computations. Why This Matters Education is the backbone of innovation, and NVIDIA’s initiative democratizes access to AI knowledge that was previously behind a paywall. As AI continues to permeate every industry, gaining expertise in GPU acceleration, deep learning, and natural language processing can unlock new career opportunities and enable groundbreaking projects. Whether you’re building generative AI models, optimizing GPU workflows, or diving into the world of transformers, these courses provide hands-on experience and a solid foundation. How to Enroll Getting started is simple: Visit this link.
Enroll in the courses of your choice.
Start learning immediately and take advantage of the free access before the offer expires. Final Thoughts In an era where AI expertise is becoming the most sought-after skill, NVIDIA’s initiative is a breath of fresh air. By breaking financial barriers, they’re opening the doors to an inclusive, AI-driven future. Whether you’re a student, researcher, or industry professional, this is your chance to leverage NVIDIA’s premium training and stay ahead of the curve. Act fast, as the offer is time-limited! Embrace the AI revolution and become a part of the next wave of innovation. Artificial Intelligence (AI) has reshaped industries, revolutionized workflows, and sparked innovation on a global scale. Recognizing the need to democratize AI knowledge and empower the next wave of tech innovators, NVIDIA , a global leader in GPU technology and AI research, has made a groundbreaking announcement. For a limited time only , NVIDIA is offering its premium AI courses for free . These courses, typically ranging between $30 and $90 each, cover cutting-edge topics in AI and accelerated computing. NVIDIA limited time only premium AI courses for free Whether you’re a beginner looking to take your first step into AI or an experienced professional eager to deepen your expertise, this is an opportunity you can’t afford to miss. What’s Included in NVIDIA’s Free AI Courses? NVIDIA, in collaboration with Evolving AI, has unlocked its treasure trove of educational resources. Let’s explore some of the courses that are now accessible for free: Accelerating End-to-End Data Science Workflows Accelerating End-to-End Data Science Workflows Original Price : $90 Original Price Duration : 6 hours Duration What You’ll Learn : Learn how to prepare, analyze, and accelerate workflows using GPUs . This course dives into advanced machine learning techniques, clear visualizations, and how to make data-driven decisions faster. What You’ll Learn GPUs Deploying a Model for Inference at Production Scale Deploying a Model for Inference at Production Scale Original Price : $30 Original Price Duration : 4 hours Duration What You’ll Learn : Master techniques to scale machine learning models for large workloads, measure and optimize production throughput, and streamline deployments using NVIDIA Triton Inference Server . What You’ll Learn NVIDIA Triton Inference Server Fundamentals of Accelerated Computing with CUDA Python Fundamentals of Accelerated Computing with CUDA Python Original Price : $90 Original Price Duration : 8 hours Duration What You’ll Learn : Learn to use Python and CUDA for accelerating code on GPUs. This course focuses on parallel computing, memory optimization, and custom program creation. What You’ll Learn Python Generative AI with Diffusion Models Generative AI with Diffusion Models Original Price : $90 Original Price Duration : 8 hours Duration What You’ll Learn : Delve into the exciting world of diffusion models for generative AI. Build models to generate images, simulate content, and explore applications in anomaly detection, recommendations, and more. What You’ll Learn diffusion models Introduction to Transformer-Based Natural Language Processing Introduction to Transformer-Based Natural Language Processing Original Price : $30 Original Price Duration : 6 hours Duration What You’ll Learn : Explore the transformers powering modern AI applications like chatbots. Use pre-trained models for text classification, question answering, and more. What You’ll Learn transformers Prompt Engineering with LLaMA-2 Prompt Engineering with LLaMA-2 Original Price : $30 Original Price Duration : 3 hours Duration What You’ll Learn : Learn the art of prompt engineering to customize AI behavior effectively. Create chatbots, interactive tools, and leverage advanced prompt techniques. What You’ll Learn prompt engineering Getting Started with Deep Learning Getting Started with Deep Learning Original Price : $90 Original Price Duration : 8 hours Duration What You’ll Learn : Train models for vision and language processing, improve accuracy with data augmentation, and apply transfer learning techniques. What You’ll Learn transfer learning Getting Started with Accelerated Computing in CUDA C/C++ Getting Started with Accelerated Computing in CUDA C/C++ Original Price : $90 Original Price Duration : 8 hours Duration What You’ll Learn : Use CUDA tools to speed up applications on GPUs, optimize performance, and resolve bottlenecks in complex computations. What You’ll Learn Why This Matters Education is the backbone of innovation, and NVIDIA’s initiative democratizes access to AI knowledge that was previously behind a paywall. As AI continues to permeate every industry, gaining expertise in GPU acceleration, deep learning, and natural language processing can unlock new career opportunities and enable groundbreaking projects. Whether you’re building generative AI models, optimizing GPU workflows, or diving into the world of transformers, these courses provide hands-on experience and a solid foundation. hands-on experience How to Enroll Getting started is simple: Visit this link. Enroll in the courses of your choice. Start learning immediately and take advantage of the free access before the offer expires. Visit this link . this link Enroll in the courses of your choice. Start learning immediately and take advantage of the free access before the offer expires. free access Final Thoughts In an era where AI expertise is becoming the most sought-after skill, NVIDIA’s initiative is a breath of fresh air. By breaking financial barriers, they’re opening the doors to an inclusive, AI-driven future. Whether you’re a student, researcher, or industry professional, this is your chance to leverage NVIDIA’s premium training and stay ahead of the curve. Act fast, as the offer is time-limited ! Embrace the AI revolution and become a part of the next wave of innovation. time-limited

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পিএসএ: এনভিডিয়ার এআই প্রশিক্ষণ কোর্সগুলি এখন শুধুমাত্র সীমিত সময়ের জন্য বিনামূল্যে

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They’re two of the world’s largest stocks by market capitalization, but could the might of Nvidia (NASDAQ:NVDA) and Microsoft (NASDAQ:MSFT) come under new strain in 2025 as fresh challenges emerge? The news that London-based investment firm Findlay Park, which counts $10.7 billion in assets under management, has been cutting its holdings of both Nvidia and Microsoft has raised eyebrows throughout US markets. Findlay Park’s pedigree for success can be found in the performance of its sole fund, the American Fund, which has outperformed 86% of its peers, making its decision to lower exposure to two of the world’s largest stocks particularly curious. The fund’s CEO Simon Pryke highlighted tepid earnings and growth expectations, as well as misaligned valuations with this slower rate of growth as a fundamental reason for trimming holdings in the two tech giants. But could we see the likes of Nvidia and Microsoft struggle to win over institutional investors in the new year? The future growth of the stocks will depend on managing hype and sustainable growth. Could Nvidia Struggle as Growth Slows? Being one of the ‘Magnificent Seven’ stocks, there’s little doubt about Nvidia’s pedigree, the stock has rallied amid the ongoing generative AI boom to become one of the world’s most valuable stocks. Nvidia’s Q3 2024 earnings reports were impressive, posting 94% year-over-year growth and sales of $35 billion. Nvidia’s data center business also posted growth of 112% thanks to increasing AI demand, while net profit doubled to $20 billion. However, there are concerns over Nvidia’s long-term growth prospects. The company’s forecasted revenue of $37.5 billion for the fourth quarter, slightly above analyst estimates of $37.09 billion, is healthy but far behind its previous quarterly growth rates. Should Nvidia’s fourth-quarter forecast be met, it indicates a year-to-year growth of around 70% from 2023. This would be impressive for most firms, but for a company that recorded 265% annual growth in the year-ago period? Not so much. Despite this, it’s worth looking at Nvidia’s advantageous position at the forefront of an AI market that’s ripe for growth. With Nvidia holding around 90% of the GPU market and 98% of the GPU training market, buying into NVDA is tantamount to betting on the growth of generative AI, which is a market forecasted to be worth $1.3 trillion by 2032. There’s also more hope that Nvidia can sustain its growth rates through innovations like the CUDA platform, which is a software framework designed to accelerate the capabilities of GPU software. “Forecasts suggest that Nvidia could continue its upward trajectory, potentially reaching a valuation of $10 trillion by 2030,” suggests Maxim Manturov, head of investment research at Freedom24. “This ambitious target reflects expectations of sustained growth in both the hardware and software segments, with CUDA playing a key role in expanding market reach and strengthening its presence. competitive advantage.” Can Microsoft Out-Innovate its Falling Market Share? Microsoft’s slipping grip on the global desktop market will be a cause for concern as Windows 11’s market share fell from 35.6% in October 2024 to 34.9% by December. Although Windows 10 made subtle gains, MSFT’s struggle to win new consumers for its more recent release could point to trouble ahead. In addition to these problems, the company has been hit with a class action lawsuit in the UK over the price of its software. If successful, Microsoft could be liable to pay a fine exceeding £1 billion ($1.27bn). MSFT has been making steady progress on Wall Street, posting growth of nearly 15% for the calendar year up to the beginning of December, but investors will want to see more ground covered in selling newer software to consumers. However, solace can be taken from Microsoft’s wins elsewhere. Although Windows 11 has struggled for dominance in the global desktop market, the system has achieved a new high market share of 53% throughout Steam’s gaming market. This highlights the firm’s long-term focus on building into the lucrative video game landscape, which is forecasted to grow at a CAGR of 13.1% towards 2030. Microsoft can also secure more Wall Street growth through its various environmental initiatives. Having committed $1 billion to its Climate Innovation Fund, the tech leader’s investments in climate change-focused technologies are likely to gain new resonance in the coming years as global warming continues to climb international priority lists. Already, Microsoft has provided 850 grants to organizations in 110 countries as part of its AI for Earth scheme, and these initiatives can be crucial to the stock’s sustainability credentials. What’s Next for NVDA and MSFT? The challenges facing Nvidia and Microsoft revolve around their ability to build on their impressive performance in recent years. The scale of the AI boom is such that retaining their seismic market share across key industries is essential, and this will require a commitment to R&D, and outpacing a growing network of competitors. However, with strong innovation pipelines and commitments to sustainability, both stocks appear set to maintain strong growth rates into the future. Determining the scale of this growth is likely to be the $1 trillion question for key institutional investors. They’re two of the world’s largest stocks by market capitalization, but could the might of Nvidia (NASDAQ:NVDA) and Microsoft (NASDAQ:MSFT) come under new strain in 2025 as fresh challenges emerge? The news that London-based investment firm Findlay Park, which counts $10.7 billion in assets under management, has been cutting its holdings of both Nvidia and Microsoft has raised eyebrows throughout US markets. Findlay Park’s pedigree for success can be found in the performance of its sole fund, the American Fund, which has outperformed 86% of its peers, making its decision to lower exposure to two of the world’s largest stocks particularly curious. The fund’s CEO Simon Pryke highlighted tepid earnings and growth expectations , as well as misaligned valuations with this slower rate of growth as a fundamental reason for trimming holdings in the two tech giants. tepid earnings and growth expectations tepid earnings and growth expectations But could we see the likes of Nvidia and Microsoft struggle to win over institutional investors in the new year? The future growth of the stocks will depend on managing hype and sustainable growth. likes of Nvidia Could Nvidia Struggle as Growth Slows? Being one of the ‘ Magnificent Seven ’ stocks, there’s little doubt about Nvidia’s pedigree, the stock has rallied amid the ongoing generative AI boom to become one of the world’s most valuable stocks. Nvidia’s Q3 2024 earnings reports were impressive, posting 94% year-over-year growth and sales of $35 billion. Magnificent Seven Magnificent Seven Nvidia’s data center business also posted growth of 112% thanks to increasing AI demand, while net profit doubled to $20 billion. However, there are concerns over Nvidia’s long-term growth prospects. The company’s forecasted revenue of $37.5 billion for the fourth quarter, slightly above analyst estimates of $37.09 billion, is healthy but far behind its previous quarterly growth rates. Should Nvidia’s fourth-quarter forecast be met, it indicates a year-to-year growth of around 70% from 2023. This would be impressive for most firms, but for a company that recorded 265% annual growth in the year-ago period? Not so much. year-to-year growth of around 70% year-to-year growth of around 70% Despite this, it’s worth looking at Nvidia’s advantageous position at the forefront of an AI market that’s ripe for growth. With Nvidia holding around 90% of the GPU market and 98% of the GPU training market, buying into NVDA is tantamount to betting on the growth of generative AI, which is a market forecasted to be worth $1.3 trillion by 2032 . 90% of the GPU market 90% of the GPU market worth $1.3 trillion by 2032 worth $1.3 trillion by 2032 There’s also more hope that Nvidia can sustain its growth rates through innovations like the CUDA platform, which is a software framework designed to accelerate the capabilities of GPU software. “Forecasts suggest that Nvidia could continue its upward trajectory, potentially reaching a valuation of $10 trillion by 2030,” suggests Maxim Manturov, head of investment research at Freedom24. “This ambitious target reflects expectations of sustained growth in both the hardware and software segments, with CUDA playing a key role in expanding market reach and strengthening its presence. competitive advantage.” Can Microsoft Out-Innovate its Falling Market Share? Microsoft’s slipping grip on the global desktop market will be a cause for concern as Windows 11’s market share fell from 35.6% in October 2024 to 34.9% by December. Although Windows 10 made subtle gains, MSFT’s struggle to win new consumers for its more recent release could point to trouble ahead. market share fell from 35.6% market share fell from 35.6% In addition to these problems, the company has been hit with a class action lawsuit in the UK over the price of its software. If successful, Microsoft could be liable to pay a fine exceeding £1 billion ($1.27bn). MSFT has been making steady progress on Wall Street , posting growth of nearly 15% for the calendar year up to the beginning of December, but investors will want to see more ground covered in selling newer software to consumers. MSFT has been making steady progress on Wall Street However, solace can be taken from Microsoft’s wins elsewhere. Although Windows 11 has struggled for dominance in the global desktop market, the system has achieved a new high market share of 53% throughout Steam’s gaming market. This highlights the firm’s long-term focus on building into the lucrative video game landscape, which is forecasted to grow at a CAGR of 13.1% towards 2030. market share of 53% market share of 53% Microsoft can also secure more Wall Street growth through its various environmental initiatives. Having committed $1 billion to its Climate Innovation Fund, the tech leader’s investments in climate change-focused technologies are likely to gain new resonance in the coming years as global warming continues to climb international priority lists. Already, Microsoft has provided 850 grants to organizations in 110 countries as part of its AI for Earth scheme, and these initiatives can be crucial to the stock’s sustainability credentials. What’s Next for NVDA and MSFT? The challenges facing Nvidia and Microsoft revolve around their ability to build on their impressive performance in recent years. The scale of the AI boom is such that retaining their seismic market share across key industries is essential, and this will require a commitment to R&D, and outpacing a growing network of competitors. However, with strong innovation pipelines and commitments to sustainability, both stocks appear set to maintain strong growth rates into the future. Determining the scale of this growth is likely to be the $1 trillion question for key institutional investors.

Tech Giants Nvidia and Microsoft Face Fresh Challenges as Investment Firms Think Twice About Holding

Технологичните гиганти Nvidia и Microsoft са изправени пред нови предизвикателства, тъй като инвестиционните дружества обмислят два пъти да задържат

Techničtí giganti Nvidia a Microsoft čelí novým výzvám, protože investiční společnosti dvakrát přemýšlejí o holdingu

Tech Giants Nvidia og Microsoft står over for nye udfordringer, mens investeringsselskaber tænker to gange om at holde

Die Technologiegiganten Nvidia und Microsoft stehen vor neuen Herausforderungen, da Investmentfirmen zweimal überlegen, ob sie ihre Aktien halten sollen.

Los gigantes tecnológicos Nvidia y Microsoft enfrentan nuevos desafíos mientras las firmas de inversión piensan dos veces antes de mantener su posición

Les géants de la technologie Nvidia et Microsoft font face à de nouveaux défis alors que les sociétés d'investissement réfléchissent à deux fois avant de détenir

I giganti della tecnologia Nvidia e Microsoft affrontano nuove sfide mentre le società di investimento ci pensano due volte prima di detenere azioni

Techgiganten Nvidia en Microsoft staan voor nieuwe uitdagingen, aangezien investeringsmaatschappijen twee keer nadenken over het aanhouden van

Giganci technologiczni Nvidia i Microsoft stają przed nowymi wyzwaniami, ponieważ firmy inwestycyjne dwa razy zastanawiają się nad posiadaniem

Giganții tehnologici Nvidia și Microsoft se confruntă cu noi provocări, deoarece firmele de investiții se gândesc de două ori la holding

Technologickí giganti Nvidia a Microsoft čelia novým výzvam, keďže investičné spoločnosti dvakrát premýšľajú o holdingu

Techjättarna Nvidia och Microsoft står inför nya utmaningar när värdepappersföretag tänker två gånger på innehav

Thanks in major part to its strategic play inside the generative AI space, it’s safe to say that Nvidia's (NASDAQ: NVDA) stock performance in 2024 was, in the worst case, amazing. In just the first quarter of 2024, Nvidia's stock price increased by 82.5%, making it one of the best performers on the S&P 500 as the AI boom drove unprecedented growth. This gain was supported by a staggering 265% rise in annual revenue, proving the company's leadership in the AI-driven industry. As expected, Nvidia's potential has captured the attention of both analysts and investors. This is due in part to the growing need for its GPUs, which are essential for AI applications in a wide range of industries. Due to this demand, Nvidia has been able to surpass earnings forecasts and greatly increase its market valuation. Surprisingly, in mid-2024, it temporarily reached a valuation of $3.34 trillion. Source: ycharts.com. Nvidia's market cap throughout the time Going forward, Nvidia's strategic future initiatives and current success are the main sources of enthusiasm surrounding the company. Nvidia is in a strong position to continue its current growth trajectory and could emerge as the most valuable stock in the world thanks to new products and technologies that aim to improve AI capabilities. Nvidia Carries On Innovating and Expanding Its Offers Moreover, the company's latest presentations and product releases demonstrate its significant focus on incorporating artificial intelligence (AI) into various applications and industries. For instance, Nvidia showcased a range of cutting-edge products, including RTX AI laptops and Project G-Assist, an AI assistant designed for PC games and applications, at events like Computex 2024. Nvidia is also making significant progress in the implementation of AI in enterprise settings. Having said that, businesses are expected to increasingly utilize generative AI to extract valuable information from unstructured data. Ultimately, this will involve constructing customized large language models (LLMs) that offer actionable insights and improve decision-making in various industries. In addition, Nvidia is partnering with leading industry partners to develop AI-enhanced virtual humans and advanced AI-powered systems. This encompasses collaborations to seamlessly incorporate AI capabilities directly into commonly utilized operating systems and applications. Maxim Manturov, head of investment research at Freedom24, says, “Nvidia's recent reaching of a market capitalization of $3 trillion has sparked a heated debate over its valuation and prospects. Nvidia's rapid growth, up more than 210% over the year, underlines its key role in the technology sector, particularly in graphics processors and artificial intelligence technologies. The company's strategic achievements in hardware, highlighted by the Hopper, Blackwell, and Rubin series, are seen as contributing to a significant increase in market share in key segments. This success has contributed significantly to its current valuation. According to the analysis, Nvidia's future growth depends not only on hardware sales, but also more on the software business, especially the CUDA platform. CUDA enjoys widespread adoption among developers using Nvidia's artificial intelligence-enabled GPUs, making it a critical tool in the development of large-scale AI models and applications. The software segment offers the potential for recurring revenue streams, thereby potentially stabilizing Nvidia's revenue profile. Looking ahead, forecasts suggest that Nvidia could continue its upward trajectory, potentially reaching a valuation of $10 trillion by 2030. This ambitious target reflects expectations of sustained growth in both the hardware and software segments, with CUDA playing a key role in expanding market reach and strengthening its presence. competitive advantage.” Most Analysts Agree That Nvidia is a Right Buy Case With multiple upgrades and upbeat price targets, analysts' predictions for Nvidia's stock performance in the future are largely positive. For example, Goldman Sachs and Loop Capital analysts continue to maintain strong buy ratings with large price targets raised, indicating their confidence in Nvidia's development trajectory, especially with regard to sales of data centers and AI applications. More precisely, the average 12-month price target among Wall Street analysts is around $130.88, with projections ranging as high as $200. Source: stockanalysis.com. Nvidia stock forecast. Since large language models (LLMs) and other AI-driven applications depend on Nvidia's GPUs for training, analysts predict that demand for the company's GPUs will remain strong. This is particularly true for the data center and AI industries, which, in the upcoming years, will probably increase Nvidia's profitability and revenue growth dramatically. All in all, we may safely say that the consensus is clear. Because of its continuous innovation, robust market demand for GPUs, and growing software ecosystem — especially related to its CUDA platform — Nvidia has indeed the potential to become the most valuable stock in the world. With an expected steady revenue growth and profitability, especially from AI-driven applications and data centers, the company's future valuation will mostly follow its great prospects. Thanks in major part to its strategic play inside the generative AI space, it’s safe to say that Nvidia's (NASDAQ: NVDA) stock performance in 2024 was, in the worst case, amazing. In just the first quarter of 2024, Nvidia's stock price increased by 82.5% , making it one of the best performers on the S&P 500 as the AI boom drove unprecedented growth. This gain was supported by a staggering 265% rise in annual revenue , proving the company's leadership in the AI-driven industry. Nvidia's stock price increased by 82.5% Nvidia's stock price increased by 82.5% staggering 265% rise in annual revenue staggering 265% rise in annual revenue As expected, Nvidia's potential has captured the attention of both analysts and investors. This is due in part to the growing need for its GPUs, which are essential for AI applications in a wide range of industries. Due to this demand, Nvidia has been able to surpass earnings forecasts and greatly increase its market valuation. Surprisingly, in mid-2024, it temporarily reached a valuation of $3.34 trillion . reached a valuation of $3.34 trillion reached a valuation of $3.34 trillion Source: ycharts.com. Nvidia's market cap throughout the time Source: ycharts.com . Nvidia's market cap throughout the time ycharts.com ycharts.com Going forward, Nvidia's strategic future initiatives and current success are the main sources of enthusiasm surrounding the company. Nvidia is in a strong position to continue its current growth trajectory and could emerge as the most valuable stock in the world thanks to new products and technologies that aim to improve AI capabilities. Nvidia Carries On Innovating and Expanding Its Offers Moreover, the company's latest presentations and product releases demonstrate its significant focus on incorporating artificial intelligence (AI) into various applications and industries. For instance, Nvidia showcased a range of cutting-edge products, including RTX AI laptops and Project G-Assist, an AI assistant designed for PC games and applications, at events like Computex 2024 . events like Computex 2024 events like Computex 2024 Nvidia is also making significant progress in the implementation of AI in enterprise settings. Having said that, businesses are expected to increasingly utilize generative AI to extract valuable information from unstructured data. Ultimately, this will involve constructing customized large language models (LLMs) that offer actionable insights and improve decision-making in various industries. constructing customized large language models (LLMs) constructing customized large language models (LLMs) In addition, Nvidia is partnering with leading industry partners to develop AI-enhanced virtual humans and advanced AI-powered systems. This encompasses collaborations to seamlessly incorporate AI capabilities directly into commonly utilized operating systems and applications. Maxim Manturov, head of investment research at Freedom24, says, “Nvidia's recent reaching of a market capitalization of $3 trillion has sparked a heated debate over its valuation and prospects. Nvidia's rapid growth, up more than 210% over the year, underlines its key role in the technology sector, particularly in graphics processors and artificial intelligence technologies. The company's strategic achievements in hardware, highlighted by the Hopper, Blackwell, and Rubin series, are seen as contributing to a significant increase in market share in key segments. This success has contributed significantly to its current valuation. According to the analysis, Nvidia's future growth depends not only on hardware sales, but also more on the software business, especially the CUDA platform. CUDA enjoys widespread adoption among developers using Nvidia's artificial intelligence-enabled GPUs, making it a critical tool in the development of large-scale AI models and applications. The software segment offers the potential for recurring revenue streams, thereby potentially stabilizing Nvidia's revenue profile. Looking ahead, forecasts suggest that Nvidia could continue its upward trajectory, potentially reaching a valuation of $10 trillion by 2030. This ambitious target reflects expectations of sustained growth in both the hardware and software segments, with CUDA playing a key role in expanding market reach and strengthening its presence. competitive advantage.” Most Analysts Agree That Nvidia is a Right Buy Case With multiple upgrades and upbeat price targets, analysts' predictions for Nvidia's stock performance in the future are largely positive. For example, Goldman Sachs and Loop Capital analysts continue to maintain strong buy ratings with large price targets raised, indicating their confidence in Nvidia's development trajectory, especially with regard to sales of data centers and AI applications. maintain strong buy ratings maintain strong buy ratings More precisely, the average 12-month price target among Wall Street analysts is around $130.88, with projections ranging as high as $200. Source: stockanalysis.com. Nvidia stock forecast. Source: stockanalysis.com . Nvidia stock forecast. stockanalysis.com stockanalysis.com Since large language models (LLMs) and other AI-driven applications depend on Nvidia's GPUs for training, analysts predict that demand for the company's GPUs will remain strong. demand for the company's GPUs demand for the company's GPUs This is particularly true for the data center and AI industries, which, in the upcoming years, will probably increase Nvidia's profitability and revenue growth dramatically. All in all, we may safely say that the consensus is clear. Because of its continuous innovation, robust market demand for GPUs, and growing software ecosystem — especially related to its CUDA platform — Nvidia has indeed the potential to become the most valuable stock in the world. With an expected steady revenue growth and profitability, especially from AI-driven applications and data centers, the company's future valuation will mostly follow its great prospects.

Why Nvidia Stands as a Sure-Fire Bet to Become The World's Most Valuable Stock

Nvidia (NASDAQ:NVDA) has shown breathtaking growth over the past 18 months, but with the stock becoming increasingly volatile in the third quarter, is it still the star of the ongoing generative AI boom? Q3 2024 has seen Nvidia ebb and flow on Wall Street, recording declines and rallies that have frequently exceeded 20% in a matter of days following the stock’s landmark $3 trillion market capitalization berth in June. Since its Q2 peak, NVDA has slipped more than 20%, falling back below its lofty $3 trillion cap. This newfound volatility doesn’t detract from Nvidia’s astounding performance of late. Between Q1 2023 and Q2 2024, the stock rallied 731.36%, and NVDA’s status as a key member of Wall Street’s Magnificent Seven appears to be assured. But the stock’s recent volatility has brought sharper and deeper losses than at any other stage of its bull run. Despite posting expectation-beating second-quarter earnings in recent weeks, Nvidia’s stock has continued to slide alongside wider market slowdowns in the US. With this in mind, should investors be worried? And is the stock really the same proposition today as it was during the heady days of the generative AI rally last year? Volatility is Common for NVDA Despite its significant levels of outperformance in recent months, Nvidia has a history of strong volatility. According to economist Hendrik Bessembinder, Nvidia’s stock price has fallen more than 50% repeatedly in the 21st Century. Notably, weak chip demand for the semiconductor firm brought a 60% decline from 2011 to 2012, and the arrival of crypto winter in 2018 saw NVDA fall 57% in the months that followed. Even in the months leading up to the launch of ChatGPT, the OpenAI innovation that heralded the start of the generative AI boom, Nvidia was on a 67% downturn due to widespread tech stock sell-offs on Wall Street. Historically, the semiconductor industry has been cyclical, so what’s stopping Nvidia from suffering from another heavy decline in the future? The answer is the firm’s gamble on generative AI. Nvidia’s Reliance on GenAI Growth Nvidia has bet big on the future of generative AI, and with the semiconductor firm well-positioned to drive the technology of the future using its powerful range of computer chips, there’s plenty of reason for the reliance on growing GenAI capabilities at an enterprise level. As a result, we’ve seen a steady innovation pipeline for generative AI initiatives from Nvidia. In recent weeks alone, the firm has announced an AI education program in association with the State of California, which will see college and adult education classes geared towards growing generative AI skills. August saw Nvidia launch a deep learning framework for generative physical AI, while July brought the announcement of generative AI models and NIM microservices that have the potential to grow artificial intelligence language, geometry, physics, and materials capabilities. Could this represent a gamble for Nvidia? According to Maxim Manturov, head of investment research at Freedom24, the strategy could help the firm diversify away from its old dependence on selling hardware. “Critics might argue that Nvidia's current market capitalization reflects overly optimistic expectations for the future, especially given its historical reliance on cyclical hardware sales,” Manturov explained. “However, its strategic pivot towards software and artificial intelligence-based technologies mitigates some of this volatility risk, potentially justifying a premium valuation.” Could GenAI Send Nvidia to $4 Trillion? Nvidia’s proactive approach to embracing generative AI technology means that the stock is likely to benefit from GenAI market growth. This is good news for NVDA when Bloomberg Intelligence forecasted generative AI to become a $1.3 trillion market by 2032. However, not all market commentators share such a bullish viewpoint. Gartner data predicts that 30% of current generative AI projects will ultimately be abandoned after proof-of-concept by 2025, with many falling flat due to factors like poor data quality, weak risk control, a lack of business value, or high implementation costs. John Naughton, professor of the public understanding of technology at the Open University, claimed that we’re currently in the ‘euphoria’ phase of what could be an AI bubble, which will soon give way to ‘profit-taking’ and, finally, ‘panic’. The coming months will be pivotal for the sustainability of the generative AI boom as enterprises seek out cost-effective ways to implement the technology, a feat that can be difficult when the money-spinning emerging tech appears to be confined to the multinational corporations developing or funding it. Despite this, Peter Oppenheimer, chief global equity strategist at Goldman Sachs Research, believes that generative AI stocks aren’t showing signs of being in a bubble. Instead, the strategist views the strong balance sheets and healthy returns on investment among the industry’s firms as a sign that the technology cycle is still in its early stages with more room for outperformance. Is There Room for More Growth for NVDA? While the stock’s strong Q2 2024 earnings report will help to shape Nvidia’s path throughout the third and fourth quarters, the wider generative AI boom will play the deciding role in whether or not NVDA can recapture its $3 trillion market capitalization as well as pave the way for a $4 trillion berth. Optimism for generative AI remains high on Wall Street, and investors wishing to know the future performance of Nvidia will do well to monitor the sentiment surrounding the emerging technology’s long-awaited implementation phase at an enterprise level. Nvidia (NASDAQ:NVDA) has shown breathtaking growth over the past 18 months, but with the stock becoming increasingly volatile in the third quarter, is it still the star of the ongoing generative AI boom? Q3 2024 has seen Nvidia ebb and flow on Wall Street, recording declines and rallies that have frequently exceeded 20% in a matter of days following the stock’s landmark $3 trillion market capitalization berth in June. Since its Q2 peak, NVDA has slipped more than 20%, falling back below its lofty $3 trillion cap. This newfound volatility doesn’t detract from Nvidia’s astounding performance of late. Between Q1 2023 and Q2 2024, the stock rallied 731.36%, and NVDA’s status as a key member of Wall Street’s Magnificent Seven appears to be assured. But the stock’s recent volatility has brought sharper and deeper losses than at any other stage of its bull run. Despite posting expectation-beating second-quarter earnings in recent weeks, Nvidia’s stock has continued to slide alongside wider market slowdowns in the US. With this in mind, should investors be worried? And is the stock really the same proposition today as it was during the heady days of the generative AI rally last year? expectation-beating second-quarter earnings expectation-beating second-quarter earnings Volatility is Common for NVDA Despite its significant levels of outperformance in recent months, Nvidia has a history of strong volatility. According to economist Hendrik Bessembinder, Nvidia’s stock price has fallen more than 50% repeatedly in the 21st Century. Notably, weak chip demand for the semiconductor firm brought a 60% decline from 2011 to 2012, and the arrival of crypto winter in 2018 saw NVDA fall 57% in the months that followed. Even in the months leading up to the launch of ChatGPT, the OpenAI innovation that heralded the start of the generative AI boom, Nvidia was on a 67% downturn due to widespread tech stock sell-offs on Wall Street. Historically, the semiconductor industry has been cyclical, so what’s stopping Nvidia from suffering from another heavy decline in the future? The answer is the firm’s gamble on generative AI. Nvidia’s Reliance on GenAI Growth Nvidia has bet big on the future of generative AI, and with the semiconductor firm well-positioned to drive the technology of the future using its powerful range of computer chips, there’s plenty of reason for the reliance on growing GenAI capabilities at an enterprise level. As a result, we’ve seen a steady innovation pipeline for generative AI initiatives from Nvidia. In recent weeks alone, the firm has announced an AI education program in association with the State of California, which will see college and adult education classes geared towards growing generative AI skills. August saw Nvidia launch a deep learning framework for generative physical AI, while July brought the announcement of generative AI models and NIM microservices that have the potential to grow artificial intelligence language, geometry, physics, and materials capabilities. Could this represent a gamble for Nvidia? According to Maxim Manturov, head of investment research at Freedom24, the strategy could help the firm diversify away from its old dependence on selling hardware. “Critics might argue that Nvidia's current market capitalization reflects overly optimistic expectations for the future, especially given its historical reliance on cyclical hardware sales,” Manturov explained. “However, its strategic pivot towards software and artificial intelligence-based technologies mitigates some of this volatility risk, potentially justifying a premium valuation.” Could GenAI Send Nvidia to $4 Trillion? Nvidia’s proactive approach to embracing generative AI technology means that the stock is likely to benefit from GenAI market growth. This is good news for NVDA when Bloomberg Intelligence forecasted generative AI to become a $1.3 trillion market by 2032. However, not all market commentators share such a bullish viewpoint. Gartner data predicts that 30% of current generative AI projects will ultimately be abandoned after proof-of-concept by 2025, with many falling flat due to factors like poor data quality, weak risk control, a lack of business value, or high implementation costs. John Naughton, professor of the public understanding of technology at the Open University, claimed that we’re currently in the ‘euphoria’ phase of what could be an AI bubble, which will soon give way to ‘profit-taking’ and, finally, ‘panic’. The coming months will be pivotal for the sustainability of the generative AI boom as enterprises seek out cost-effective ways to implement the technology, a feat that can be difficult when the money-spinning emerging tech appears to be confined to the multinational corporations developing or funding it. Despite this, Peter Oppenheimer, chief global equity strategist at Goldman Sachs Research, believes that generative AI stocks aren’t showing signs of being in a bubble. Instead, the strategist views the strong balance sheets and healthy returns on investment among the industry’s firms as a sign that the technology cycle is still in its early stages with more room for outperformance. Is There Room for More Growth for NVDA? While the stock’s strong Q2 2024 earnings report will help to shape Nvidia’s path throughout the third and fourth quarters, the wider generative AI boom will play the deciding role in whether or not NVDA can recapture its $3 trillion market capitalization as well as pave the way for a $4 trillion berth. Optimism for generative AI remains high on Wall Street, and investors wishing to know the future performance of Nvidia will do well to monitor the sentiment surrounding the emerging technology’s long-awaited implementation phase at an enterprise level.

Is Nvidia Still the Stock in Q3 That the Generative AI Boom Has Led Us to Believe? 

From improbable to inevitable. Nvidia’s emergence as the frontrunner to become the world’s first $4 trillion stock has been sustained by the generative AI boom. With no signs of slowing, NVDA’s potential appears endless. The third quarter of 2024 began with the same level of momentum on display for Nvidia as KeyBanc analyst John Vinh raised his target price on the stock to $180. This boost of 33% from current levels would see the stock surpass the $4 trillion market capitalization mark and become the first company to do so. These lofty expectations encapsulate the meteoric rise of the semiconductor firm. Just two years ago, NVDA was battling a sustained Wall Street decline amid tech stock sell-offs. The prospect of becoming a $1 trillion stock seemed like a pipedream, let alone mounting a challenge to become the world’s most valuable stock. The generative AI boom changed everything. Bloomberg estimates suggest that the generative AI market alone will grow at a CAGR of 42% over the next 10 years into a $1.3 trillion market by 2032. Nvidia’s status as a market leader in providing AI chipsets ensures that the company will be a driving force in this growth. Strength in Fundamentals Although the long-term sustainability of the generative AI frenzy has been called into question, there’s little doubt that Nvidia has showcased tangible fundamentals to support its impressive Wall Street performance in recent months. In May, the semiconductor giant reported revenues that tripled to $26.04 billion year over year, weighing in well above analyst forecasts. Additionally, Nvidia saw net income rise to $14.88 billion, comfortably up from the $2.04 billion reported a year prior. Nvidia’s buoyant outlook is further supported by forecasts for Q2 2024 revenue reaching $28 billion, plus or minus two percent. This would also fall way above analyst expectations. Driving Force in Generative AI The brilliance of Nvidia’s position as a market leader in providing the computer chips that will power the generative AI boom has drawn some impressive comparisons. According to Jim Keller, a former AMD and Tesla engineer and current CEO of AI firm Tenstorrent, Nvidia is becoming the IBM of the AI era. Given the sheer scale of the ongoing AI boom, Nvidia could surpass IBM in terms of performance and make an unprecedented claim to become the cornerstone of generative AI. This claim could be sustained by the launch of Nvidia’s Blackwell computing processors, which were unveiled in spring 2024. The new products will replace the company’s popular H100 chips and facilitate further revenue generation. The arrival of Blackwell processors comes at a time when an increasing number of firms are seeking ways to incorporate generative AI into their operations. This could help drive sales even higher for Nvidia. However, Nvidia isn’t simply driving the future of AI hardware for enterprises. The firm announced in its June 2024 keynote address plans to integrate its AI services into the world of video games through its ACE-powered Convert Protocol to create fresh on-demand interactions between games and gamers. Given that Microsoft opted to acquire Activision Blizzard for $68.7 billion on the belief that gaming is the future of entertainment and the metaverse, Nvidia’s strides in the landscape could drive its growth further into the future. Is the GenAI Boom Sustainable? Although it appears clear that generative AI will continue its emergence as a disruptive force throughout a vast array of industries, Nvidia’s position as the king of GenAI isn’t necessarily assured. Competition is growing, and more budget-focused firms like Taiwan Semiconductor Manufacturing Company and Advanced Micro Devices are names that could position themselves as cheaper alternatives as the technology continues its emergence. Likewise, many of the tech giants that are currently among Nvidia’s list of customers are intent on taking the production of AI chips in-house. These factors could all eat into NVDA’s dominance. “Investors should exercise caution and conduct thorough research before investing in any field, especially one as dynamic as GenAI,” warns Maxim Manturov, head of investment research at Freedom24. “Success in GenAI depends not only on cutting-edge technology but also on a robust data infrastructure, a skilled workforce, and strategic planning.” While Nvidia’s position as a generative AI market leader appears solid today, there will certainly be challenges to its dominance in the years to come. Should a rival begin generating cheaper AI chipsets, the company’s stock could tumble. Thinking Two Moves Ahead The most important factor in determining Nvidia’s path to $4 trillion is the fact that the company is never content with resting on its laurels. With Nvidia investing billions of dollars into developing leading generative AI computer chips, we’re looking at a company that’s seeking to stay two moves ahead of its rivals. As the market grows, new competitors are likely to emerge, but as one of the world’s largest companies, it’s unlikely that they would have the firepower to go toe-to-toe with Nvidia. With this in mind, Nvidia’s future is in the firm’s hands. If $4 trillion is inevitable, then the likelihood is that CEO Jensen Huang already has $5 trillion and beyond in his sights. From improbable to inevitable. Nvidia’s emergence as the frontrunner to become the world’s first $4 trillion stock has been sustained by the generative AI boom. With no signs of slowing, NVDA’s potential appears endless. The third quarter of 2024 began with the same level of momentum on display for Nvidia as KeyBanc analyst John Vinh raised his target price on the stock to $180 . This boost of 33% from current levels would see the stock surpass the $4 trillion market capitalization mark and become the first company to do so. target price on the stock to $180 target price on the stock to $180 These lofty expectations encapsulate the meteoric rise of the semiconductor firm. Just two years ago, NVDA was battling a sustained Wall Street decline amid tech stock sell-offs. The prospect of becoming a $1 trillion stock seemed like a pipedream, let alone mounting a challenge to become the world’s most valuable stock. The generative AI boom changed everything. Bloomberg estimates suggest that the generative AI market alone will grow at a CAGR of 42% over the next 10 years into a $1.3 trillion market by 2032. Nvidia’s status as a market leader in providing AI chipsets ensures that the company will be a driving force in this growth. CAGR of 42% over the next 10 years CAGR of 42% over the next 10 years Strength in Fundamentals Although the long-term sustainability of the generative AI frenzy has been called into question, there’s little doubt that Nvidia has showcased tangible fundamentals to support its impressive Wall Street performance in recent months. In May, the semiconductor giant reported revenues that tripled to $26.04 billion year over year , weighing in well above analyst forecasts. tripled to $26.04 billion year over year tripled to $26.04 billion year over year Additionally, Nvidia saw net income rise to $14.88 billion, comfortably up from the $2.04 billion reported a year prior. Nvidia’s buoyant outlook is further supported by forecasts for Q2 2024 revenue reaching $28 billion, plus or minus two percent. This would also fall way above analyst expectations. Driving Force in Generative AI The brilliance of Nvidia’s position as a market leader in providing the computer chips that will power the generative AI boom has drawn some impressive comparisons. According to Jim Keller, a former AMD and Tesla engineer and current CEO of AI firm Tenstorrent, Nvidia is becoming the IBM of the AI era . becoming the IBM of the AI era becoming the IBM of the AI era Given the sheer scale of the ongoing AI boom, Nvidia could surpass IBM in terms of performance and make an unprecedented claim to become the cornerstone of generative AI. This claim could be sustained by the launch of Nvidia’s Blackwell computing processors , which were unveiled in spring 2024. The new products will replace the company’s popular H100 chips and facilitate further revenue generation. launch of Nvidia’s Blackwell computing processors launch of Nvidia’s Blackwell computing processors The arrival of Blackwell processors comes at a time when an increasing number of firms are seeking ways to incorporate generative AI into their operations. This could help drive sales even higher for Nvidia. However, Nvidia isn’t simply driving the future of AI hardware for enterprises. The firm announced in its June 2024 keynote address plans to integrate its AI services into the world of video games through its ACE-powered Convert Protocol to create fresh on-demand interactions between games and gamers. fresh on-demand interactions fresh on-demand interactions Given that Microsoft opted to acquire Activision Blizzard for $68.7 billion on the belief that gaming is the future of entertainment and the metaverse, Nvidia’s strides in the landscape could drive its growth further into the future. future of entertainment future of entertainment Is the GenAI Boom Sustainable? Although it appears clear that generative AI will continue its emergence as a disruptive force throughout a vast array of industries, Nvidia’s position as the king of GenAI isn’t necessarily assured. Competition is growing, and more budget-focused firms like Taiwan Semiconductor Manufacturing Company and Advanced Micro Devices are names that could position themselves as cheaper alternatives as the technology continues its emergence. Likewise, many of the tech giants that are currently among Nvidia’s list of customers are intent on taking the production of AI chips in-house . These factors could all eat into NVDA’s dominance. taking the production of AI chips in-house taking the production of AI chips in-house “Investors should exercise caution and conduct thorough research before investing in any field, especially one as dynamic as GenAI,” warns Maxim Manturov, head of investment research at Freedom24. “Success in GenAI depends not only on cutting-edge technology but also on a robust data infrastructure, a skilled workforce, and strategic planning.” While Nvidia’s position as a generative AI market leader appears solid today, there will certainly be challenges to its dominance in the years to come. Should a rival begin generating cheaper AI chipsets, the company’s stock could tumble. Thinking Two Moves Ahead The most important factor in determining Nvidia’s path to $4 trillion is the fact that the company is never content with resting on its laurels. With Nvidia investing billions of dollars into developing leading generative AI computer chips, we’re looking at a company that’s seeking to stay two moves ahead of its rivals. As the market grows, new competitors are likely to emerge, but as one of the world’s largest companies, it’s unlikely that they would have the firepower to go toe-to-toe with Nvidia. With this in mind, Nvidia’s future is in the firm’s hands. If $4 trillion is inevitable, then the likelihood is that CEO Jensen Huang already has $5 trillion and beyond in his sights.

$4 Trillion Appears Inevitable as Nvidia Remains the Star of the Generative AI Boom

Heavy is the head that wears the crown during a Wall Street bull run, and Nvidia’s status as the king of the ongoing generative AI boom means that the stock can be especially vulnerable to the prospect of weakening investor appetite. Nvidia (NASDAQ:NVDA) became Wall Street’s most exciting story in 2023. The chipmaker rallied some 239% throughout the year, smashing through the $1 trillion market capitalization glass ceiling before peaking at a cap in excess of $2tn. The optimism, fuelled by the ongoing generative AI market rally, continued to make waves in the first-quarter of 2024. NVDA rallied almost 90% in the opening three months of the year to continue its strong spell of dominance. But finally, at the beginning of April, the stock took its biggest tumble in four years. The wider implications of the Nvidia sell-off are likely to shake up the entire generative AI market. Counting the Cost of NVDA Sell-Offs The first three weeks of April 2024 saw NVDA shed more than 15% of its value amid widespread investor sell-offs. Although greater degrees of volatility can be expected for stocks caught up in the hype phase of an emerging market, Nvidia’s April downturn has been the company’s biggest dip since the initial outbreak of the Covid-19 pandemic in March 2020. For Nvidia, the pandemic era must seem like a lifetime ago. Its March 2020 sell-offs saw the stock tumble to $51.44. The stock’s peak closing price in March 2024 was $950.02. But after four years of meteoric growth, Nvidia’s recent market downturn is particularly concerning–particularly now the stock’s gained the status as a tech pioneer that’s been driving the S&P 500 higher on a consistent basis. Nvidia’s position at the pinnacle of the generative AI boom could mean that the stock would always be the first to absorb the impact of a change in investor sentiment, and the fears are that NVDA would be the canary in the mine should we suddenly discover that generative AI has been in a hype bubble that’s ready to burst for some time. Although Nvidia’s recent difficulties have coincided with the news that US inflation rates have continued to defy expectations, placing the prospect of interest rate cuts on hold for the foreseeable future, analysts suggest that fears over a cooling generative AI boom remain the key cause of investor concern in the wake of the underperformance. “The stock pullback has very little to do with rates,” explained Parag Thatte, strategist at Deutsche Bank, in a recent Financial Times interview. “It’s more to do with investors pricing in slower earnings growth.” There’s also a growing concern that generative AI has begun to transform from its hype phase towards the question of implementation. While Large Language Models (LLMs) like ChatGPT have been excellent tools in showcasing the sheer power and potential of generative AI, they’ve also been largely error-prone in a manner that could cause more hesitancy among enterprises seeking to embrace the technology. It’s for this reason that Gil Luria, analyst at DA Davidson, warned that a 20% slide in Nvidia stock could take place by the end of 2024. Luria suggests that the implementation phase of Nvidia’s products, which are currently being bought en masse by the likes of Microsoft and Amazon, could run into trouble when key buyers reach capacity and demand begins to fall. However, other analysts suggest that the end of the generative AI hype phase will be met by a more strategic implementation phase which could keep the industry growing. “Concerns about GenAI failing to meet expectations in 2024 should be seen in the context of the natural cycle of hype and maturity of new technologies,” said Maxim Manturov, head of investment research at Freedom Finance Europe. “While some industry leaders have expressed frustration with the speed of progress in artificial intelligence and GenAI in their organisations, others remain optimistic about its potential.” “Companies heavily invested in GenAI are under pressure to prove profitability, and industry reports indicate a shift to more strategic AI initiatives in the coming years,” Manturov added. Is the Generative AI an Exceptional Case? Here, it’s worth reminding ourselves that we’re talking about the generative AI boom. This is an industry that Bloomberg Intelligence last year suggested would grow at a CAGR of 42% into a $1.3 trillion industry by 2032. Fresh demand for generative AI products was predicted to add around $280 million in new software revenue. Could we be talking about an emerging technology that’s market impact is without precedent? Morgan Stanley analysts have underlined the indecisive outlook for Nvidia and the wider generative AI market in Q2 2024 by proposing a more bullish outlook for NVDA as well as the generative AI-focused Amazon (AMZN). As Nvidia reported Q4 2023 revenue increases of 265% to $22 billion, CEO Jensen Huang claimed that "accelerated computing and generative AI have hit the tipping point," before adding that "demand is surging worldwide across companies, industries and nations." The company’s innovations in recent weeks have included the text-to-3D tool, LATTE3D, which Nvidia described as a ‘virtual 3D printer’, as well as a collaboration with Hipocratic AI to develop a network of generative AI nurses that could cost $9 an hour. Nvidia’s quick 5% rebound following its record sell-offs should serve as a wider vote of confidence in the innovation that the company is capable of. Regardless of whether its success has made it the GenAI canary, NVDA is certainly an innovative stock that’s capable of sustaining its impressive growth. Bubble or Boom? Ultimately, Nvidia’s performance over the past 12 months means that the stock has become a live litmus test for investor sentiment in generative AI. Whether that’s a good thing or not depends wholly on the capabilities of the industry itself. Nvidia’s rapid growth has seen the stock rub shoulders with the likes of Microsoft, Apple, and Alphabet, and the company will be keen to follow the lead of other industry giants to continue sustaining its growth through innovation. As a semiconductor leader, the possibilities are nearly endless for Nvidia. As long as the capabilities of generative AI continue to astound clients and deliver on its promises, NVDA remains a stock that can continue to grow. If investors get a whiff of saturation or inefficiency, the Nvidia litmus test could face some further challenges ahead. Heavy is the head that wears the crown during a Wall Street bull run, and Nvidia’s status as the king of the ongoing generative AI boom means that the stock can be especially vulnerable to the prospect of weakening investor appetite. Nvidia (NASDAQ:NVDA) became Wall Street’s most exciting story in 2023. The chipmaker rallied some 239% throughout the year, smashing through the $1 trillion market capitalization glass ceiling before peaking at a cap in excess of $2tn. Nvidia The optimism, fuelled by the ongoing generative AI market rally, continued to make waves in the first-quarter of 2024. NVDA rallied almost 90% in the opening three months of the year to continue its strong spell of dominance. But finally, at the beginning of April, the stock took its biggest tumble in four years. The wider implications of the Nvidia sell-off are likely to shake up the entire generative AI market. Counting the Cost of NVDA Sell-Offs The first three weeks of April 2024 saw NVDA shed more than 15% of its value amid widespread investor sell-offs. Although greater degrees of volatility can be expected for stocks caught up in the hype phase of an emerging market, Nvidia’s April downturn has been the company’s biggest dip since the initial outbreak of the Covid-19 pandemic in March 2020. For Nvidia, the pandemic era must seem like a lifetime ago. Its March 2020 sell-offs saw the stock tumble to $51.44. The stock’s peak closing price in March 2024 was $950.02. But after four years of meteoric growth, Nvidia’s recent market downturn is particularly concerning–particularly now the stock’s gained the status as a tech pioneer that’s been driving the S&P 500 higher on a consistent basis. Nvidia’s position at the pinnacle of the generative AI boom could mean that the stock would always be the first to absorb the impact of a change in investor sentiment, and the fears are that NVDA would be the canary in the mine should we suddenly discover that generative AI has been in a hype bubble that’s ready to burst for some time. Although Nvidia’s recent difficulties have coincided with the news that US inflation rates have continued to defy expectations, placing the prospect of interest rate cuts on hold for the foreseeable future, analysts suggest that fears over a cooling generative AI boom remain the key cause of investor concern in the wake of the underperformance. prospect of interest rate cuts on hold prospect of interest rate cuts on hold “The stock pullback has very little to do with rates,” explained Parag Thatte , strategist at Deutsche Bank, in a recent Financial Times interview. “It’s more to do with investors pricing in slower earnings growth.” explained Parag Thatte explained Parag Thatte There’s also a growing concern that generative AI has begun to transform from its hype phase towards the question of implementation. While Large Language Models (LLMs) like ChatGPT have been excellent tools in showcasing the sheer power and potential of generative AI, they’ve also been largely error-prone in a manner that could cause more hesitancy among enterprises seeking to embrace the technology. largely error-prone largely error-prone It’s for this reason that Gil Luria, analyst at DA Davidson, warned that a 20% slide in Nvidia stock could take place by the end of 2024. Luria suggests that the implementation phase of Nvidia’s products, which are currently being bought en masse by the likes of Microsoft and Amazon, could run into trouble when key buyers reach capacity and demand begins to fall. 20% slide in Nvidia stock 20% slide in Nvidia stock However, other analysts suggest that the end of the generative AI hype phase will be met by a more strategic implementation phase which could keep the industry growing. “Concerns about GenAI failing to meet expectations in 2024 should be seen in the context of the natural cycle of hype and maturity of new technologies,” said Maxim Manturov, head of investment research at Freedom Finance Europe . “While some industry leaders have expressed frustration with the speed of progress in artificial intelligence and GenAI in their organisations, others remain optimistic about its potential.” Freedom Finance Europe Freedom Finance Europe “Companies heavily invested in GenAI are under pressure to prove profitability, and industry reports indicate a shift to more strategic AI initiatives in the coming years,” Manturov added. Is the Generative AI an Exceptional Case? Here, it’s worth reminding ourselves that we’re talking about the generative AI boom. This is an industry that Bloomberg Intelligence last year suggested would grow at a CAGR of 42% into a $1.3 trillion industry by 2032 . $1.3 trillion industry by 2032 $1.3 trillion industry by 2032 Fresh demand for generative AI products was predicted to add around $280 million in new software revenue. Could we be talking about an emerging technology that’s market impact is without precedent? Morgan Stanley analysts have underlined the indecisive outlook for Nvidia and the wider generative AI market in Q2 2024 by proposing a more bullish outlook for NVDA as well as the generative AI-focused Amazon (AMZN). more bullish outlook more bullish outlook As Nvidia reported Q4 2023 revenue increases of 265% to $22 billion, CEO Jensen Huang claimed that "accelerated computing and generative AI have hit the tipping point," before adding that "demand is surging worldwide across companies, industries and nations." claimed that claimed that The company’s innovations in recent weeks have included the text-to-3D tool , LATTE3D, which Nvidia described as a ‘virtual 3D printer’, as well as a collaboration with Hipocratic AI to develop a network of generative AI nurses that could cost $9 an hour. text-to-3D tool text-to-3D tool collaboration with Hipocratic AI collaboration with Hipocratic AI Nvidia’s quick 5% rebound following its record sell-offs should serve as a wider vote of confidence in the innovation that the company is capable of. Regardless of whether its success has made it the GenAI canary, NVDA is certainly an innovative stock that’s capable of sustaining its impressive growth. Bubble or Boom? Ultimately, Nvidia’s performance over the past 12 months means that the stock has become a live litmus test for investor sentiment in generative AI. Whether that’s a good thing or not depends wholly on the capabilities of the industry itself. Nvidia’s rapid growth has seen the stock rub shoulders with the likes of Microsoft, Apple, and Alphabet, and the company will be keen to follow the lead of other industry giants to continue sustaining its growth through innovation. As a semiconductor leader, the possibilities are nearly endless for Nvidia. As long as the capabilities of generative AI continue to astound clients and deliver on its promises, NVDA remains a stock that can continue to grow. If investors get a whiff of saturation or inefficiency, the Nvidia litmus test could face some further challenges ahead.

Nvidia’s Shaky Q2 Underlines the Stock as Generative AI’s Sentiment Litmus Test

এনভিডিয়ার শ্যাকি Q2 জেনারেটিভ এআই এর সেন্টিমেন্ট লিটমাস টেস্ট হিসাবে স্টককে আন্ডারলাইন করেছে

Nvidias wackeliges zweites Quartal unterstreicht die Aktie als Lackmustest für die Stimmung von Generative AI

El inestable segundo trimestre de Nvidia subraya la acción como prueba de fuego del sentimiento de la IA generativa

Le Shaky Q2 de Nvidia souligne le titre en tant que test décisif du sentiment de Generative AI

एनवीडिया की अस्थिर Q2 स्टॉक को जेनरेटिव एआई के सेंटीमेंट लिटमस टेस्ट के रूप में रेखांकित करती है

エヌビディアの第2四半期の不安定さは、ジェネレーティブAIの感情リトマス試験として株価を浮き彫りにする

Nvidia의 Shaky Q2는 Generative AI의 감정 리트머스 테스트로서 주식을 강조합니다.

Shaky Q2 da Nvidia destaca o estoque como teste decisivo de sentimento da IA generativa

Нестабильный второй квартал Nvidia подчеркивает, что акции являются лакмусовой бумажкой настроений генеративного ИИ

Nvidia'nın Titrek 2. Çeyreği Hisse Senedinin Üretken Yapay Zekanın Duyarlılık Turnusol Testi Olduğunu Vurguluyor

Q2 run rẩy của Nvidia nhấn mạnh cổ phiếu là bài kiểm tra tình cảm của AI sáng tạo

Nvidia 第二季度业绩表现不佳，凸显其股票是生成式 AI 情绪的试金石

NVIDIA is one of the most successful electronics companies on the planet. Worth a staggering two trillion USD, NVIDIA has made it big with the production of computer GPUs that power much of the world’s PC hardware. Jensen Huang, the company CEO, has long been regarded as the main driver of the company’s enormous growth, becoming a fabled legend in the PC world and within business. The company succeeded by improving gaming-based experiences via its GPUs, enticing the average consumer through to avid esports player to buy its graphics cards by the bucket load. NVIDIA is known for its innovation, bringing world-class design and technology expertise to its development. More specifically, the company has implemented artificial intelligence into its GPUs to improve performance. An example is the company’s use of DLSS (deep learning super sampling technology), which employs AI to create new frames artificially and improve resolution. For example, a gamer with a 4k monitor but lacks the hardware to hit good FPS (frames per second) at higher resolutions will still be able to play at 4k without dipping in quality due to this technology. NVIDIA is also digitizing the industry through its Omniverse platform, which enables industrial players like Siemens to simulate and create industrial processes virtually in real time, acting as digital twins. NVIDIA Omniverse is a unique and groundbreaking platform for companies wanting to improve their industrial workflows. Last year, we had the opportunity to chat with Mike Geyer, the Head of Digital Twins at Nvidia; here’s what he had to say about the platform’s use as a tool for industrial collaboration: “Our collaboration with Siemens empowers us to harness their rich legacy in shop floor automation, manufacturing control systems, and an array of sophisticated software platforms. This, in turn, is seamlessly integrated into Nvidia Omniverse and other foundational technologies, culminating in the establishment of a collaborative and open ecosystem that delivers profound value to our clientele.” Alongside the Siemens partnership, NVIDIA has collaborated with many other partners, such as Bentley Motors and Service Now, to create a more immersive industrial ecosystem. For more information on the partners NVIDIA is working with, our intelligence platform showcases the breadth of the NVIDIA collaborator network in its full capacity. As mentioned earlier in the article, NVIDIA is an innovator with a 2 trillion dollar market cap for a reason. The technology giant has filed a whopping 224 patents in immersive technology, with noteworthy patents including virtual reality locomotion and a holographic reflective slim VR/AR display system. Below is a snapshot of the patents the company has been filing, showcasing the speed at which NVIDIA is moving to pivot toward emerging trends. Despite the speed of innovation, NVIDIA has faced notable negative sentiment in the media due to a recent decline in stock price, as shown in the image below; however, due to the company’s dominance in terms of coverage over rivals, this is expected due to increased public spotlight. Nevertheless, NVIDIA continues to redefine what is possible in PC hardware and software, acting as stalwarts in the quest for continued market dominance. This story was distributed under HackerNoon’s Business Blogging Program. Learn more about the program here. NVIDIA is one of the most successful electronics companies on the planet. Worth a staggering two trillion USD, NVIDIA has made it big with the production of computer GPUs that power much of the world’s PC hardware. Jensen Huang, the company CEO, has long been regarded as the main driver of the company’s enormous growth, becoming a fabled legend in the PC world and within business. The company succeeded by improving gaming-based experiences via its GPUs, enticing the average consumer through to avid esports player to buy its graphics cards by the bucket load. NVIDIA is known for its innovation, bringing world-class design and technology expertise to its development. More specifically, the company has implemented artificial intelligence into its GPUs to improve performance. An example is the company’s use of DLSS ( deep learning super sampling technology ), which employs AI to create new frames artificially and improve resolution. For example, a gamer with a 4k monitor but lacks the hardware to hit good FPS (frames per second) at higher resolutions will still be able to play at 4k without dipping in quality due to this technology. deep learning super sampling technology NVIDIA is also digitizing the industry through its Omniverse platform, which enables industrial players like Siemens to simulate and create industrial processes virtually in real time, acting as digital twins. NVIDIA Omniverse is a unique and groundbreaking platform for companies wanting to improve their industrial workflows. Last year, we had the opportunity to chat with Mike Geyer, the Head of Digital Twins at Nvidia; here’s what he had to say about the platform’s use as a tool for industrial collaboration: chat “Our collaboration with Siemens empowers us to harness their rich legacy in shop floor automation, manufacturing control systems, and an array of sophisticated software platforms. This, in turn, is seamlessly integrated into Nvidia Omniverse and other foundational technologies, culminating in the establishment of a collaborative and open ecosystem that delivers profound value to our clientele.” “Our collaboration with Siemens empowers us to harness their rich legacy in shop floor automation, manufacturing control systems, and an array of sophisticated software platforms. This, in turn, is seamlessly integrated into Nvidia Omniverse and other foundational technologies, culminating in the establishment of a collaborative and open ecosystem that delivers profound value to our clientele.” Alongside the Siemens partnership, NVIDIA has collaborated with many other partners, such as Bentley Motors and Service Now, to create a more immersive industrial ecosystem . For more information on the partners NVIDIA is working with, our intelligence platform showcases the breadth of the NVIDIA collaborator network in its full capacity. ecosystem intelligence platform As mentioned earlier in the article, NVIDIA is an innovator with a 2 trillion dollar market cap for a reason. The technology giant has filed a whopping 224 patents in immersive technology, with noteworthy patents including virtual reality locomotion and a holographic reflective slim VR/AR display system. Below is a snapshot of the patents the company has been filing, showcasing the speed at which NVIDIA is moving to pivot toward emerging trends. Despite the speed of innovation, NVIDIA has faced notable negative sentiment in the media due to a recent decline in stock price, as shown in the image below; however, due to the company’s dominance in terms of coverage over rivals, this is expected due to increased public spotlight. Nevertheless, NVIDIA continues to redefine what is possible in PC hardware and software, acting as stalwarts in the quest for continued market dominance. This story was distributed under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed under HackerNoon’s Business Blogging Program. Learn more about the program here. here.

NVIDIA: Redefining Possibilities in PC Hardware and Industry Standards

এনভিআইডিএ: পিসি হার্ডওয়্যার এবং শিল্পের মানদণ্ডে সম্ভাবনার পুনর্নির্ধারণ

NVIDIA: Neue Möglichkeiten bei PC-Hardware und Industriestandards

NVIDIA: Redefiniendo las posibilidades en hardware de PC y estándares de la industria

NVIDIA : redéfinir les possibilités en matière de matériel PC et de normes industrielles

NVIDIA: पीसी हार्डवेयर और उद्योग मानकों में संभावनाओं को पुनर्परिभाषित करना

NVIDIA: PC ハードウェアと業界標準の可能性を再定義

NVIDIA: PC 하드웨어 및 산업 표준의 가능성 재정의

NVIDIA: redefinindo possibilidades em hardware de PC e padrões da indústria

NVIDIA: переосмысление возможностей аппаратного обеспечения ПК и отраслевых стандартов

NVIDIA: PC Donanımı ve Endüstri Standartlarında Olanakları Yeniden Tanımlamak

NVIDIA: Xác định lại các khả năng trong phần cứng PC và các tiêu chuẩn ngành

NVIDIA：重新定义 PC 硬件和行业标准的可能性

Hey everyone! and just like you, I’ve been fascinated with the recent progress of artificial intelligence. Realizing that I needed to stay abreast with all the developments happening, I decided to embark on a personal journey of learning, thus was born! With this series, I will be learning about LLMs and share ideas, experiments, opinions, trends & learnings through my blog posts. You can follow along the journey on HackerNoon or my personal website . In today’s article, we’ll be talking about take aways from Nvidia’s , I’m Nataraj 100 days of AI here here If AI is a gold rush, Nvidia is the ultimate picks and shovels company. All things AI go through Nvidia because of its dominance as the sole company that creates the chips (GPUs) needed to deploy the computationally expensive large language models. As the models scale, it increases the need for more powerful GPUs and the entire world is relying on Nvidia to deliver on them. Its not an exaggeration to say Nvidia is at the core of all things AI and they recently had their semi-annual developer conference GTC (March 18-21). In this post I am going to summarize my key takeaways from this very special GTC conference and what it means for the gen AI space. Takeaway 1: AI is not limited to the tech sector The power of what gen AI can do and deliver has not been lost on non-tech sectors. Companies across all the sectors in the economy think that there is a need for them to adopt AI and find a way to partner, execute and stay ahead. The proof here is looking at how many non-tech sector companies have partnered with Nvidia. Companies from retail, automobile, construction, design and everything else have announced partnerships with Nvidia. Takeaway 2: We need much bigger GPUs Ever since transformers were invented, we are doubling the scale of LLMs every 6 months. For example, look at the parameter count of Open AI models below. In GPT-3 series alone the parameter count ranged from 125M to 175B. And the latest models expected to come out of Open AI are rumored to have parameter counts above trillion and soon could hit trillions in less than two years, if the rate of scaling continues. To support the increasing scale of LLMs we need increased computational power. To capture the market, Nvidia is launching a new series of GPUs called as Blackwell, named after statistician & mathematician David Blackwell. Blackwell is a new series of GPUs (GB200) but also a new super computer platform. Here’s a performance comparison of the new Blackwell GPU with its previous generation GPU Hopper. Takeaway 3: Moving from retrieval to generation In the current generation of computing, everything is about retrieving a piece of data stored in different formats and presenting it in a way that is useful to the user. But in the coming generation of computing and apps, we are about to see more of generating things at the user’s request and giving it back to the user. In case of chat-gpt for example, the answer you are getting is not stored in some database before hand, but is being generated in real time to serve the user’s question. We are about to see the generation of text, images, videos, chemicals, proteins and more. Takeaway 4: Inference is getting better Inferencing is when you ask chat-gpt a question, the model is figuring out the answer in the form of token generation and returning the answer in the form of tokens. If inference is not fast enough, then the consumers will not be able to use any of the AI applications. Inference is especially tricky because LLMs are getting larger and larger and they don’t fit in one GPU, so parallelizing the inference across GPUs is a difficult task and involves programming Nvidia GPUs to use multiple optimization techniques. With Blackwell GPUs, Nvidia is able to achieve 30x faster inference speeds. Takeaway 5: The real metaverse is NVidia’s Omniverse As I learnt more and more about Omniverse by Nvidia I am more and more bullish on the product and the idea. This is because to really leverage AI and unlock all the possibilities in automation and robotics, we actually do not have all the data needed. For example, say you want to create a robot which cooks great food of all kinds. There is no data where you have first person view of chefs cooking various kinds of dishes. We have general data of various cooking in the form of YouTube videos, but to get the robots learn the physical movements involved in cooking a first person data is needed. A 3d simulation of the world in Omniverse can help bridge that gap of data needed for unlocking all these use cases. I am extremely bullish on the idea. That’s it for Day 22 of 100 Days of AI. I write a newsletter called Above Average where I talk about the second order insights behind everything that is happening in big tech. If you are in tech and don’t want to be average, . subscribe to it Follow me on , or for latest updates on 100 days of AI or . If you are in tech you might be interested in joining my community of tech professionals . Twitter LinkedIn HackerNoon bookmark this page here

100 Days of AI, Day 16: 5 Key Takeaways From NVIDIA’s AI Developer Event

AI এর 100 দিন, দিন 16: 5 NVIDIA এর aI ডেভেলপার ইভেন্ট থেকে মূল টেকওয়ে

100 Tage KI, Tag 16: 5 wichtige Erkenntnisse aus dem AI-Entwicklerevent von NVIDIA

100 días de IA, día 16: 5 conclusiones clave del evento para desarrolladores de IA de NVIDIA

100 jours d'IA, jour 16 : 5 points clés à retenir de l'événement pour développeurs IA de NVIDIA

AI के 100 दिन, दिन 16: NVIDIA के aI डेवलपर इवेंट से 5 मुख्य बातें

AI の 100 日間、16 日目: NVIDIA の aI 開発者イベントから得た 5 つの重要なポイント

100일간의 AI, 16일차: NVIDIA AI 개발자 이벤트의 5가지 주요 시사점

100 dias de IA, dia 16: 5 principais conclusões do evento de desenvolvedores de IA da NVIDIA

100 дней искусственного интеллекта, день 16: 5 ключевых выводов с мероприятия NVIDIA для разработчиков искусственного интеллекта

100 Gün Yapay Zeka, 16. Gün: NVIDIA'nın AI Geliştirici Etkinliğinden 5 Temel Çıkarım

100 Ngày của AI, Ngày 16: 5 bài học quan trọng từ Sự kiện dành cho nhà phát triển AI của NVIDIA

AI 100 天，第 16 天：NVIDIA 人工智能开发者活动的 5 个要点

Nvidia's annual developer conference in 2024, known as GTC (GPU Technology Conference), was a pivotal event that unveiled groundbreaking advancements in artificial intelligence (AI) chips, software tools, and strategic partnerships. The conference, led by Nvidia's CEO Jensen Huang, showcased the company's commitment to innovation and leadership in the tech industry. And if you want to understand the latest trends from the world of AI - subscribe to my newsletter ‘ ‘. And the best part - it’s completely free! AI Hunters Now, onto the key takeaways from Nvidia's GTC 2024: Flagship AI Chip - B200 "Blackwell" The Flagship AI Chip - B200 "Blackwell" unveiled by Nvidia at GTC 2024 represents a groundbreaking advancement in AI chip technology. Named after mathematician David Blackwell, this new chip is a significant leap forward in performance, being 30 times faster than its predecessor, the Hopper series, particularly excelling at tasks like supporting advanced chatbots and large language models. With an impressive 208 billion transistors, more than double the previous chip, the B200 chip offers exceptional processing power. Despite its remarkable performance, the B200 chip is designed with efficiency in mind, using 25 times less energy and money than the previous Hopper series. This focus on efficiency not only enhances its cost-effectiveness but also positions it as a sustainable solution for AI applications. The innovative design of the B200 chip, which combines two squares of silicon into a single chip, allows all transistors to access memory simultaneously, further boosting productivity and performance. Nvidia's dominance in the data center AI chip market, with a market share of roughly 80%, underscores the significance of the B200 chip in shaping the future of AI technology. Major tech giants like Amazon, Google, Meta Platforms, Microsoft, OpenAI, and Tesla are expected to adopt this new chip, highlighting its importance and impact in the industry. Expected to hit the market later in 2024, the B200 chip offers advanced capabilities for AI applications. With its powerful performance, energy efficiency, and anticipated industry-wide adoption, the Blackwell B200 chip is poised to redefine AI processing and drive innovation across various sectors. Points to Reflect Upon: Performance Leap: Consider the implications of the B200 chip's 30x performance increase for AI applications and industries. Assess the feasibility of integrating the B200 chip into existing AI infrastructure for enhanced performance. Efficiency Benefits: Conduct a cost-benefit analysis to determine the potential savings from transitioning to the B200 chip. Software Tools for AI Integration Nvidia Inference Microservices (NIM) introduced at GTC 2024 represent a significant advancement in AI deployment technology. NIM is a cloud-native microservices solution that simplifies the development and deployment of generative AI applications across various infrastructures, including cloud, data centers, and GPU-accelerated workstations. It offers a streamlined path for developing AI-powered enterprise applications and deploying AI models in production, aiming to shorten time-to-market and simplify deployment processes for organizations transitioning to full-scale production deployments. NIM is designed to bridge the gap between the complexities of AI model development and the operational needs of enterprises, enabling a broader pool of developers to contribute to AI transformations within their companies. Some core benefits of NIM include its portability and control, allowing model deployment across various infrastructures, from local workstations to cloud environments. It provides prebuilt containers and Helm charts with optimized models validated across different NVIDIA hardware platforms, cloud service providers, and Kubernetes distributions, ensuring support across all NVIDIA-powered environments. Developers can access AI models through industry-standard APIs, simplifying the development of AI applications and enabling swift updates within the ecosystem. NIM also addresses the need for domain-specific solutions by packaging domain-specific NVIDIA CUDA libraries and specialized code tailored to various domains like language, speech, video processing, healthcare, and more. Leveraging optimized inference engines for each model and hardware setup, NIM ensures the best possible latency and throughput on accelerated infrastructure, reducing the cost of running inference workloads as they scale and enhancing the end-user experience. Part of the NVIDIA AI Enterprise suite, NIM is built with an enterprise-grade base container, providing a solid foundation for enterprise AI software through rigorous validation, enterprise support, and regular security updates. With support for various AI models, including community models, NVIDIA AI Foundation models, and custom AI models, NIM simplifies the AI model deployment process by packaging algorithmic, system, and runtime optimizations and adding industry-standard APIs. This comprehensive solution accelerates the deployment of scalable and customized AI applications in production, making AI more accessible and customizable across industries. Points to Reflect Upon: Business Impact: Consider how NIM can empower businesses to harness AI capabilities and drive innovation. Operational Efficiency: Evaluate how enhanced system efficiency can optimize business processes and decision-making. Strategic Partnerships and Collaborations Nvidia's expanded partnerships with industry leaders and software makers announced at GTC 2024 mark a significant milestone in the development of AI technologies and their integration into various sectors. These collaborations highlight Nvidia's strategic efforts to advance AI infrastructure, enhance AI capabilities, and drive innovation across industries. One key partnership involves Microsoft, where Nvidia and Microsoft are working together to bring the power of Nvidia Grace Blackwell GB200 and advanced Nvidia technologies to Azure. This collaboration aims to deliver trillion-parameter foundation models for tasks like natural language processing, computer vision, speech recognition, and more. Additionally, Microsoft is introducing the Azure NC H100 v5 VM virtual machine based on the Nvidia H100 NVL platform to cater to midrange training and inferencing needs. Furthermore, Nvidia's inference microservices are being integrated into Azure, enhancing AI capabilities for users by providing cloud-native microservices for optimized inference on various foundation models. This integration streamlines AI deployments and accelerates the development of performance-optimized production AI applications. In the automotive sector, Nvidia has deepened its ties with leading Chinese automakers like BYD, Xpeng, GAC Aion's Hyper brand, Zeekr, and Li Auto. These partnerships focus on integrating Nvidia's cutting-edge technologies, such as the Drive Thor in-vehicle chips, to enhance autonomous driving capabilities and infotainment systems in vehicles. Collaborations with US-based software company Cerence aim to adapt large language model AI systems for in-car applications, promising advanced voice command systems and improved user experiences. Overall, these partnerships unveiled at GTC 2024 demonstrate Nvidia's commitment to driving innovation across various industries by leveraging cutting-edge technologies and fostering collaborations with industry leaders and software makers. Points to Reflect Upon: Industry Impact: Consider how partnerships with key players can influence the adoption and integration of Nvidia's technology in various sectors. Innovation Potential: Reflect on the potential for collaborative efforts to drive innovation and create new opportunities in AI and technology. Focus on Sustainability and Sovereign AI Nvidia's emphasis on sustainability and sovereign AI initiatives at GTC 2024 underscores the company's commitment to responsible technology development. The focus on addressing environmental concerns related to AI training and data center energy consumption demonstrates Nvidia's proactive stance on sustainability issues. By prioritizing energy efficiency and sustainable practices in AI development, Nvidia is setting a standard for responsible innovation in the tech industry. Furthermore, Nvidia's dedication to sovereign AI initiatives, which enable nations to produce AI using their infrastructure and workforce, highlights the company's commitment to promoting ethical and secure AI practices globally. By empowering countries to develop AI capabilities locally, Nvidia is fostering digital sovereignty and supporting economic growth while ensuring data protection and security. Overall, Nvidia's dual focus on sustainability and sovereign AI at GTC 2024 showcases the company's holistic approach to technology development, balancing innovation with ethical considerations and environmental responsibility. This strategic emphasis on sustainability and sovereignty sets Nvidia apart as a leader in responsible AI practices and underscores its commitment to shaping a more sustainable and secure future for AI technologies. Points to Reflect Upon: Environmental Responsibility: Consider the implications of Nvidia's sustainability efforts on the tech industry and environmental conservation. Develop a sustainability strategy to align with Nvidia's initiatives. Ethical AI Practices: Reflect on the importance of promoting ethical AI practices and ensuring transparency in AI development. Global Engagement: Explore opportunities for global engagement to promote sovereign AI practices and support technological independence. Market Position and Future Outlook Nvidia's strong market position and future outlook were prominently highlighted at GTC 2024, emphasizing the company's leadership in GPU technology and AI innovation amidst competition from rivals like AMD, Intel, and emerging startups. Announcements at GTC 2024 regarding new products such as the Blackwell GPU series, DGX GB200 System, and DGX SuperPOD underscore Nvidia's focus on advancing AI infrastructure and enabling next-generation AI models. This strategic vision positions Nvidia at the forefront of technological advancements that will shape the future of AI computing and high-performance computing (HPC). Overall, Nvidia's market position and future outlook at GTC 2024 highlight its resilience, innovation drive, and strategic vision for continued growth and leadership in the evolving landscape of AI technologies. To sum up, Nvidia's annual developer conference in 2024 was a platform for unveiling cutting-edge AI technology, software tools, and strategic partnerships that reinforce the company's position as a leader in the tech industry. The key takeaways from GTC 2024 underscore Nvidia's commitment to innovation, sustainability, and collaboration, setting the stage for continued advancements in AI, GPU technology, and high-performance computing. P.S. Check out some of my previous articles at HackerNoon: Google Introduces Gemma: Revolutionary Access to Pre-Trained AI Models Sora's AI Innovation Set to Disrupt Video Content Creation Breaking Down the Next Big Thing in NFTs: ERC-404 Spotlight Gemini 1.5 Unleashes Unprecedented Context for AI Applications The AI Revolution in Journalism: A New Era of Enhanced Reporting DeFi Community Building: A Step-by-Step Guide for Crypto Startups

Nvidia GPU Technology Conference In 2024: A Deep-Dive 

I remember the feeling of getting a new video card with a more powerful GPU for my PC. Everyone at school would be jealous, and you knew — the best games were at your disposal now. That’s what NVIDIA is in my mind — making the best games possible. With their strategic advance into all things AI, that’s what they’re doing again: making the best games — in reality now! — possible. Their gaming plan has spread across accelerated computing, , industry applications, automotive, enterprise platforms, Omniverse, and robotics. generative AI Today, at their annual GTC conference, they announced new developments in all of those areas. Covering them all would be impossible in one newsletter, but that’s what stands out for me: AI-driven self-driving cars as intelligent companions Tesla is already a giant iPhone, meaning it’s more a device than a car. NVIDIA is following the same idea: helping to create cars that are defined by software. A few leading Chinese transportation companies are adopting NVIDIA DRIVE Thor — an in-vehicle computing platform architected for generative AI applications, delivering four times the performance of its predecessor. With up to a thousand trillion operations per second, it’s equipped to handle a diverse array of AI workloads, setting the stage for safer autonomous driving. And though the industry is currently navigating through various levels of assisted driving (Levels 2 and 3), the hardware and software are designed to evolve, allowing vehicles equipped with NVIDIA technology today to reach higher levels of autonomy as software and regulations evolve. Thanks to implemented genAI you will be able to talk to your car. And the car could answer back. Chinese automakers are indeed fast in adopting NVIDIA technologies — which raises some questions from the media; that’s due to incentives, regulations favoring innovation, and a strategic focus on new vehicle architectures that prioritize centralized computing and AI. But NVIDIA also assured us at a press briefing that engagement with Western automakers continued robustly, with mentions of ongoing projects with Mercedes-Benz and Jaguar Land Rover. NVIDIA announces GR00T and Omniverse (a digital twin ecosystem) , NVIDIA’s platform for creating and deploying digital twins, marks a significant milestone in industrial digitalization. By facilitating the integration of physical and virtual worlds, it allows industries to simulate, optimize, and execute operations with unprecedented efficiency. The introduction of Omniverse Cloud APIs extends these capabilities, promising a transformative impact across various sectors, including automotive, robotics, and beyond. Omniverse represents a leap in robotics and AI, catering to both runtime and AI training for robots. With advancements like project GR00T and Isaac Manipulator, NVIDIA is enabling a new generation of robotics development, emphasizing large, multimodal models for a future where robots are more versatile and capable than ever before. NVIDIA’s Isaac robotics platform And a few more technical announcements: — a cutting-edge advancement designed to power the next generation of AI with 20 petaflops of performance. This GPU represents a quantum leap in AI capabilities, aiming to democratize access to trillion-parameter models. Nvidia Blackwell GPU Key Features: Combines two of the largest dies achievable, linked by a high-bandwidth NVLink, ensuring seamless operation as a unified architecture. Dual-Die Architecture: Enhances AI computations to achieve unprecedented efficiency, enabling operations in just four bits of precision. Second-Generation Transformer Engines: Delivers four times the training performance and 30 times the inference performance of its predecessor, with 25 times better energy efficiency. Performance: — a new generation interconnect technology, which addresses the bottleneck of data exchange. It is designed to facilitate communication between GPUs at a scale suitable for the most advanced AI models. NVLink Switch 7.2 TI Key Features: Offers 18 times faster throughput compared to previous solutions, enabling efficient scaling for trillion-parameter models. High Throughput: Facilitates a new level of data exchange efficiency among GPUs, crucial for complex AI model training and inference. Enhanced Communication: features 72 Blackwell GPUs. It showcases Nvidia’s commitment to pushing the boundaries of data center capabilities. New GB 272 Computing Platform — a new software product aimed at simplifying the deployment of generative AI within enterprise environments. It packages models with optimized inference engines and supports a wide range of GPU architectures. They call it AI package for all. NVIDIA NIM Key Features: Bundles AI models into a deployable container, facilitating easy deployment and scalability across various environments. Containerized Microservice: Accommodates a diverse range of AI models, including proprietary and open-source, ensuring flexibility and control over intellectual property. Support for Custom and Open Models: Offers industry-standard APIs, enabling seamless integration with existing enterprise systems and processes. Standardized APIs: From : “Nvidia is on top of the world. They have supreme pricing power right now . Everyone simply has to take what Nvidia is feeding them with a silver spoon.” SemiAnalysis despite hyperscaler silicon ramping If there’s ever a course about the greatest tech CEOs, Jensen Huang will definitely be on the list. His idea of continuously leveraging GPU technology to accelerate computing across a myriad of domains has fundamentally changed how we interact with technology. It’s enabled breakthroughs that were once considered science fiction, and that’s how NVIDIA hit a $2 trillion valuation. Under Hueng’s supervision, we’re all following NVIDIA’s game plan. Enjoyed This Story? I write a weekly analysis of the AI world in the newsletter. We aim to equip you with comprehensive knowledge and historical insights so you can make informed decisions about AI and ML. Turing Post Also published . here

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