Nvidia and Broadcom Compete in AI Infrastructure
Written by Emily J. Thompson, Senior Investment Analyst
Updated: 1 hour ago
0mins
Should l Buy AVGO?
Source: NASDAQ.COM
- Market Share Advantage: Nvidia holds over 90% market share in the GPU space, with its graphics processing units being the primary chips for AI workloads, ensuring the company continues to benefit from the booming AI infrastructure, particularly in training large language models.
- Custom Chip Opportunities: Broadcom leads in ASIC technology, providing building blocks for customers to create custom chips; while AI ASICs lack the flexibility of GPUs, they excel in specific tasks and are more energy-efficient, helping clients reduce costs.
- Collaborations and Orders: Broadcom's partnership with Alphabet on Tensor Processing Units (TPUs) is set to drive growth, with Alphabet's massive capex budget providing a strong market opportunity, and Anthropics placing a $21 billion TPU order with Broadcom, further solidifying its market position.
- Future Growth Potential: With Broadcom generating nearly $64 billion in total revenue last fiscal year, it is poised for explosive growth in the coming years, making it a top stock in the AI infrastructure space, despite not being included in the current best stock picks by the analyst team.
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Analyst Views on AVGO
Wall Street analysts forecast AVGO stock price to rise
30 Analyst Rating
29 Buy
1 Hold
0 Sell
Strong Buy
Current: 333.990
Low
370.00
Averages
457.75
High
525.00
Current: 333.990
Low
370.00
Averages
457.75
High
525.00
About AVGO
Broadcom Inc. is a global technology firm that designs, develops, and supplies a range of semiconductors, enterprise software and security solutions. The Company operates through two segments: semiconductor solutions and infrastructure software. Its semiconductor solutions segment includes all of its product lines and intellectual property (IP) licensing. It provides a variety of radio frequency semiconductor devices, wireless connectivity solutions, custom touch controllers, and inductive charging solutions for mobile applications. Its infrastructure software segment includes its private and hybrid cloud, application development and delivery, software-defined edge, application networking and security, mainframe, distributed and cybersecurity solutions, and its FC SAN business. It provides a portfolio of software solutions that enable customers to plan, develop, automate, manage and secure applications across mainframe, distributed, mobile and cloud platforms.
About the author
Emily J. Thompson
Emily J. Thompson, a Chartered Financial Analyst (CFA) with 12 years in investment research, graduated with honors from the Wharton School. Specializing in industrial and technology stocks, she provides in-depth analysis for Intellectia’s earnings and market brief reports.
Nvidia and Broadcom Compete in AI Infrastructure
- Market Share Advantage: Nvidia holds over 90% market share in the GPU space, with its graphics processing units being the primary chips for AI workloads, ensuring the company continues to benefit from the booming AI infrastructure, particularly in training large language models.
- Custom Chip Opportunities: Broadcom leads in ASIC technology, providing building blocks for customers to create custom chips; while AI ASICs lack the flexibility of GPUs, they excel in specific tasks and are more energy-efficient, helping clients reduce costs.
- Collaborations and Orders: Broadcom's partnership with Alphabet on Tensor Processing Units (TPUs) is set to drive growth, with Alphabet's massive capex budget providing a strong market opportunity, and Anthropics placing a $21 billion TPU order with Broadcom, further solidifying its market position.
- Future Growth Potential: With Broadcom generating nearly $64 billion in total revenue last fiscal year, it is poised for explosive growth in the coming years, making it a top stock in the AI infrastructure space, despite not being included in the current best stock picks by the analyst team.
See More
Nvidia and Broadcom Compete in AI Infrastructure
- Market Share Dominance: Nvidia holds over 90% market share in the GPU space, with its graphics processing units being the primary chips for AI workloads, ensuring the company's leading position in the rapidly growing AI infrastructure market.
- CUDA Ecosystem: By promoting its CUDA software in universities and research labs, Nvidia has trained a generation of developers, resulting in nearly all foundational AI code being written on its platform, thereby solidifying its market moat.
- Broadcom's Growth Potential: As a leader in custom AI chips and data center networking, Broadcom presents a more attractive investment choice in AI infrastructure buildout, particularly with its Tomahawk Ethernet switches being widely adopted in large-scale data centers.
- Custom Chip Opportunities: Broadcom's collaboration with Alphabet on Tensor Processing Units (TPUs) presents significant growth potential, with Anthropics placing a $21 billion order for TPUs, highlighting the immense demand in the custom chip market.
See More
Taiwan Semiconductor Set to Benefit from Surge in AI Spending
- AI Spending Outlook: The four major AI hyperscalers are projected to spend around $650 billion on data center capital expenditures by 2026, indicating strong AI demand, and companies not keeping pace with spending risk falling behind.
- Taiwan Semiconductor's Competitive Edge: Taiwan Semiconductor is viewed as the only company capable of standing out in the AI chip market, with clients like Nvidia, AMD, and Broadcom, ensuring its neutral position and profitability in the AI buildout.
- Revenue Growth Expectations: Management at Taiwan Semiconductor anticipates AI chip revenue to grow at nearly a 60% compound annual growth rate from 2024 to 2029, reflecting the scale and longevity of the ongoing AI buildout.
- Valuation Reasonableness: Despite the surge in AI spending, Taiwan Semiconductor's stock trades at a price-to-earnings ratio of 26, slightly above the S&P 500's 22, indicating it remains a quality investment choice.
See More
Taiwan Semiconductor Leads AI Chip Market
- Surge in AI Spending: The four major AI hyperscalers are projected to spend around $650 billion on data center capital expenditures by 2026, indicating strong demand for AI technology, which positions Taiwan Semiconductor as a key beneficiary and solidifies its market leadership.
- Revenue Growth Expectations: Taiwan Semiconductor's management anticipates that AI chip revenue will grow at nearly a 60% compound annual growth rate from 2024 to 2029, highlighting the substantial growth potential and long-term prospects of the AI market, thereby boosting investor confidence in its future performance.
- Clear Competitive Advantage: While companies like Intel and Samsung have some capabilities in chip manufacturing, Taiwan Semiconductor stands out as the only major option due to its vast production capacity and client base, including Nvidia and AMD, ensuring its neutral position in the AI buildout.
- Reasonable Valuation: With a price-to-earnings ratio of 26, slightly above the S&P 500's 22, Taiwan Semiconductor is still considered a quality investment for playing the AI buildout, reflecting market recognition of its future growth potential.
See More
Tech Giants Commit Billions to Indian AI Initiatives
- Massive Investment Commitments: Tech giants including Amazon, Microsoft, Meta, and Alphabet have announced plans to invest up to $700 billion in AI projects in India in 2023, reflecting the intense global competition and enthusiasm for AI technology.
- Reliance and Adani Plans: Indian tech group Reliance is set to invest $110 billion in data centers and infrastructure, while Adani outlines a $100 billion AI data center buildout over the next decade, further solidifying India's position in the global AI landscape.
- Microsoft and OpenAI Collaboration: At the Indian AI Impact Summit, Microsoft announced plans to invest $50 billion in the Global South by 2030, partnering with OpenAI and AMD to enhance India's AI capabilities, indicating a strong focus on the region's market potential.
- Deepening US-India Trade Cooperation: During the summit, India and the US signed the Pax Silica agreement aimed at securing the global supply chain for silicon-based technologies, further strengthening technological ties between the two nations.
See More
AI Spending Continues to Surge, Favoring Key Stocks
- Strong Market Demand: Despite market hopes for a slowdown in AI spending, this trend is expected to persist for several years, particularly as the construction of large data centers takes time, indicating a bullish outlook for companies involved in AI.
- Nvidia's Leading Position: Nvidia (NVDA) has emerged as the top provider of AI computing units since 2023, with its latest Rubin chip architecture requiring four times fewer GPUs for training AI models, further driving customer upgrade demand, and is projected to grow at 65% in fiscal year 2027.
- TSMC's Growth Potential: Taiwan Semiconductor Manufacturing (TSM), as the world's largest chip foundry, is expected to see nearly 30% revenue growth this year, benefiting from the four major hyperscalers planning to invest around $650 billion in capital expenditures, highlighting its crucial role in AI spending.
- Broadcom's Market Opportunity: Broadcom (AVGO) is experiencing exploding demand for its custom AI chips, with management projecting a doubling of AI chip revenue in the upcoming quarter, positioning itself as a strong alternative to Nvidia in the competitive AI computing landscape.
See More
Nvidia and Broadcom Compete in AI Infrastructure
- Market Share Advantage: Nvidia holds over 90% market share in the GPU space, with its graphics processing units being the primary chips for AI workloads, ensuring the company continues to benefit from the booming AI infrastructure, particularly in training large language models.
- Custom Chip Opportunities: Broadcom leads in ASIC technology, providing building blocks for customers to create custom chips; while AI ASICs lack the flexibility of GPUs, they excel in specific tasks and are more energy-efficient, helping clients reduce costs.
- Collaborations and Orders: Broadcom's partnership with Alphabet on Tensor Processing Units (TPUs) is set to drive growth, with Alphabet's massive capex budget providing a strong market opportunity, and Anthropics placing a $21 billion TPU order with Broadcom, further solidifying its market position.
- Future Growth Potential: With Broadcom generating nearly $64 billion in total revenue last fiscal year, it is poised for explosive growth in the coming years, making it a top stock in the AI infrastructure space, despite not being included in the current best stock picks by the analyst team.
See More
Nvidia and Broadcom Compete in AI Infrastructure
- Market Share Dominance: Nvidia holds over 90% market share in the GPU space, with its graphics processing units being the primary chips for AI workloads, ensuring the company's leading position in the rapidly growing AI infrastructure market.
- CUDA Ecosystem: By promoting its CUDA software in universities and research labs, Nvidia has trained a generation of developers, resulting in nearly all foundational AI code being written on its platform, thereby solidifying its market moat.
- Broadcom's Growth Potential: As a leader in custom AI chips and data center networking, Broadcom presents a more attractive investment choice in AI infrastructure buildout, particularly with its Tomahawk Ethernet switches being widely adopted in large-scale data centers.
- Custom Chip Opportunities: Broadcom's collaboration with Alphabet on Tensor Processing Units (TPUs) presents significant growth potential, with Anthropics placing a $21 billion order for TPUs, highlighting the immense demand in the custom chip market.
See More
Taiwan Semiconductor Set to Benefit from Surge in AI Spending
- AI Spending Outlook: The four major AI hyperscalers are projected to spend around $650 billion on data center capital expenditures by 2026, indicating strong AI demand, and companies not keeping pace with spending risk falling behind.
- Taiwan Semiconductor's Competitive Edge: Taiwan Semiconductor is viewed as the only company capable of standing out in the AI chip market, with clients like Nvidia, AMD, and Broadcom, ensuring its neutral position and profitability in the AI buildout.
- Revenue Growth Expectations: Management at Taiwan Semiconductor anticipates AI chip revenue to grow at nearly a 60% compound annual growth rate from 2024 to 2029, reflecting the scale and longevity of the ongoing AI buildout.
- Valuation Reasonableness: Despite the surge in AI spending, Taiwan Semiconductor's stock trades at a price-to-earnings ratio of 26, slightly above the S&P 500's 22, indicating it remains a quality investment choice.
See More
Taiwan Semiconductor Leads AI Chip Market
- Surge in AI Spending: The four major AI hyperscalers are projected to spend around $650 billion on data center capital expenditures by 2026, indicating strong demand for AI technology, which positions Taiwan Semiconductor as a key beneficiary and solidifies its market leadership.
- Revenue Growth Expectations: Taiwan Semiconductor's management anticipates that AI chip revenue will grow at nearly a 60% compound annual growth rate from 2024 to 2029, highlighting the substantial growth potential and long-term prospects of the AI market, thereby boosting investor confidence in its future performance.
- Clear Competitive Advantage: While companies like Intel and Samsung have some capabilities in chip manufacturing, Taiwan Semiconductor stands out as the only major option due to its vast production capacity and client base, including Nvidia and AMD, ensuring its neutral position in the AI buildout.
- Reasonable Valuation: With a price-to-earnings ratio of 26, slightly above the S&P 500's 22, Taiwan Semiconductor is still considered a quality investment for playing the AI buildout, reflecting market recognition of its future growth potential.
See More
Tech Giants Commit Billions to Indian AI Initiatives
- Massive Investment Commitments: Tech giants including Amazon, Microsoft, Meta, and Alphabet have announced plans to invest up to $700 billion in AI projects in India in 2023, reflecting the intense global competition and enthusiasm for AI technology.
- Reliance and Adani Plans: Indian tech group Reliance is set to invest $110 billion in data centers and infrastructure, while Adani outlines a $100 billion AI data center buildout over the next decade, further solidifying India's position in the global AI landscape.
- Microsoft and OpenAI Collaboration: At the Indian AI Impact Summit, Microsoft announced plans to invest $50 billion in the Global South by 2030, partnering with OpenAI and AMD to enhance India's AI capabilities, indicating a strong focus on the region's market potential.
- Deepening US-India Trade Cooperation: During the summit, India and the US signed the Pax Silica agreement aimed at securing the global supply chain for silicon-based technologies, further strengthening technological ties between the two nations.
See More
AI Spending Continues to Surge, Favoring Key Stocks
- Strong Market Demand: Despite market hopes for a slowdown in AI spending, this trend is expected to persist for several years, particularly as the construction of large data centers takes time, indicating a bullish outlook for companies involved in AI.
- Nvidia's Leading Position: Nvidia (NVDA) has emerged as the top provider of AI computing units since 2023, with its latest Rubin chip architecture requiring four times fewer GPUs for training AI models, further driving customer upgrade demand, and is projected to grow at 65% in fiscal year 2027.
- TSMC's Growth Potential: Taiwan Semiconductor Manufacturing (TSM), as the world's largest chip foundry, is expected to see nearly 30% revenue growth this year, benefiting from the four major hyperscalers planning to invest around $650 billion in capital expenditures, highlighting its crucial role in AI spending.
- Broadcom's Market Opportunity: Broadcom (AVGO) is experiencing exploding demand for its custom AI chips, with management projecting a doubling of AI chip revenue in the upcoming quarter, positioning itself as a strong alternative to Nvidia in the competitive AI computing landscape.
See More
