Tag: AI

Nvidia Stock Still Has Room to Run in 2024 Despite Massive 200%+ Surge

Posted on by slightbourne@noblecapitalmarkets.com

Nvidia’s share price has skyrocketed over 200% in 2023 alone, but some analysts believe the AI chip maker still has more gas in the tank for 2024. The meteoric rise has pushed Nvidia near trillion-dollar status, leading some to question how much higher the stock can climb. However, bullish analysts argue shares still look attractively priced given massive growth opportunities in AI computing.

Nvidia has emerged as the dominant player in AI chips, which are seeing surging demand from companies developing new generative AI applications. The company’s deals this year with ServiceNow and Snowflake for its H100 chip underscore how major tech firms are racing to leverage Nvidia’s graphics processing units (GPUs) to power natural language systems like ChatGPT.

This voracious appetite for Nvidia’s AI offerings has triggered a wave of earnings upgrades by analysts. Where three months ago Wall Street saw Nvidia earning $10.76 per share this fiscal year, the consensus forecast now stands at $12.29 according to Yahoo Finance data.

Next fiscal year, profits are expected to surge over 67% to $20.50 per share as Nvidia benefits from its pole position in the white-hot AI space. The upgraded outlooks have eased valuation concerns even as Nvidia’s stock price has steadily climbed to nosebleed levels.

Surge Driven by AI Dominance But Valuation Not Overstretched

Nvidia’s trailing P/E ratio now exceeds 65, but analysts note other metrics suggest the stock isn’t overly inflated. For example, Nvidia trades at a PEG ratio of just 0.5 times, indicating potential undervaluation for a hyper-growth company.

Its forward P/E of 24.5 also seems reasonable relative to expected 70%+ earnings growth next year. While far above the market average, analysts argue Nvidia deserves a premium multiple given its AI leadership and firm grasp on the emerging market.

Evercore ISI analyst Matthew Prisco sees a clear path for Nvidia to become the world’s most valuable company, surpassing Apple and Microsoft. But even if that lofty goal isn’t achieved, Prisco notes Nvidia still has ample room for expansion both in revenue and profits for 2024.

Other Catalysts to Drive Growth Despite Stellar Run

Prisco points to Nvidia expanding its customer base beyond AI startups to bigger enterprise players as one growth driver. Increasing production capacity for key AI chips like the H100 is another, which will allow Nvidia to capitalize on the AI boom.

Patrick Moorhead of Moor Insights & Strategy expects the untapped potential in inference AI applications to fuel Nvidia’s next leg higher. This is reminiscent of the machine learning surge that propelled Nvidia’s last massive rally around 2018.

While risks remain like potential profit-taking and Nvidia’s inability to sell advanced AI chips to China, analysts contend the long-term growth story remains solid. Nvidia is firing on all cylinders in perhaps the most disruptive tech space today in AI computing.

With its gaming roots and GPU headstart, Nvidia enjoys a competitive advantage over rivals in the AI chip race. And its platform approach working with developers and marquee customers helps feed an innovation flywheel difficult for challengers to replicate.

Final Thoughts on Nvidia’s Outlook

Nvidia has already achieved meteoric stock gains rarely seen for a mega-cap company. Yet analysts argue its leading position in the AI revolution merits an extended valuation premium despite the triple-digit surge.

Earnings estimates continue marching higher as customers clamor for Nvidia’s AI offerings. While the current P/E is lofty on an absolute basis, growth-adjusted valuations suggest upside remains as Nvidia cements it dominance across AI use cases.

If Nvidia can broaden its customer base, boost production capacity, and capitalize on emerging opportunities like inference AI, shares could continue to charge ahead despite their blistering 2023 rally. With tech titans racing to deploy the next generation of AI, Nvidia looks poised to provide the supercharged semiconductors powering this computing transformation.

Amazon Trainium2 Takes Aim at Nvidia’s AI Chip Dominance

Posted on by slightbourne@noblecapitalmarkets.com

As artificial intelligence continues its seemingly unstoppable rise, tech giants are racing to power the next generation of AI applications. This week, Amazon Web Services unveiled its latest salvo directed squarely at sector leader Nvidia – the new Trainium2 AI training chip. Promising up to quadruple the performance of its predecessor, Trainium2 represents Amazon’s most aggressive move yet to challenge Nvidia’s dominance in the white-hot AI chip space.

Nvidia’s GPUs Fuel Explosive Growth of AI

Over the past decade, Nvidia has capitalized on the AI boom more than any other company. Its graphics processing units, or GPUs, first designed for video gaming proved remarkably adept at accelerating machine learning. Aggressive investments in its Tensor Core GPU architecture tailored specifically for AI workloads cemented Nvidia’s status as the chipmaker of choice for everything from natural language AI like ChatGPT to computer vision, robotics and self-driving vehicles.

Demand for Nvidia chips now far outstrips supply, as businesses of all stripes rush to infuse AI capabilities into their operations. The company’s data center revenue expanded sharply in its most recent quarter, overtaking its gaming segment for the first time, demonstrating the commercial appetite for its AI offerings. Nvidia also boasts partnerships expanding its reach, including an alliance with Microsoft to power Azure’s AI cloud infrastructure.

Can Trainium2 Take on Nvidia’s AI Dominance?

This is the competitive landscape now facing Trainium2 as Amazon seeks to grow its 7% share of the nearly $61 billion AI chip market. Boasting 58 billion transistors, far greater than Nvidia’s offerings, and advanced compression technology minimizing data movement, the second-generation Trainium aims to match or beat Nvidia’s training performance at lower cost.

Crucially for Amazon Web Services customers, Trainium2 optimizes TensorFlow, PyTorch and MXNet, among the most popular open-source AI frameworks. It can also handle multi-framework workloads simultaneously. Amazon is counting on these features combined with integrated tools for scaling model training to convince AI developers and businesses to give Trainium2 a look over Nvidia’s ubiquitous GPUs.

Still, Nvidia isn’t standing still. Its latest H100 GPU packs 80 billion transistors enabling an order of magnitude performance leap over previous generations. Plus, Nvidia’s CUDA programming framework and expansive software ecosystem powering over 2.3 million AI developers globally cannot be easily dismissed.

The AI Chip Wars Have Only Just Begun

While Trainium2 faces stiff competition, its arrival underscores how vital the AI chip space has become. Amazon is also expanding collaboration with Nvidia, incorporating H200 GPUs into AWS infrastructure so customers can access Nvidia’s most advanced AI hardware. With AI poised to unleash a new industrial revolution, expect the battle for chip supremacy powering everything from intelligent search to autonomous robotaxis to keep heating up.

Nvidia Out to Prove AI Means (Even More) Business

Posted on by slightbourne@noblecapitalmarkets.com

Chipmaker Nvidia (NVDA) is slated to report fiscal third quarter financial results after Tuesday’s closing bell, with major implications for tech stocks as investors parse the numbers for clues about the artificial intelligence boom.

Heading into the print, Nvidia shares closed at an all-time record high of $504.09 on Monday, capping a momentous run over the last year. Bolstered by explosive growth in data center revenue tied to AI applications, the stock has doubled since November 2022.

Now, Wall Street awaits Nvidia’s latest earnings and guidance with bated breath, eager to gauge the pace of expansion in the company’s most promising segments serving AI needs.

Consensus estimates call for dramatic sales and profit surges versus last year’s third quarter results. But in 2022, Nvidia has made beating expectations look easy.

This time, another strong showing could validate nosebleed valuations across tech stocks and reinforce the bid under mega-cap names like Microsoft and Alphabet that have ridden AI fervor to their own historic highs this month.

By contrast, any signs of weakness threatening Nvidia’s narrative as an AI juggernaut could prompt the momentum-driven sector to stumble. An upside surprise remains the base case for most analysts. But with tech trading at elevated multiples, the stakes are undoubtedly high heading into Tuesday’s report.

AI Arms Race Boosting Data Center Sales

Nvidia’s data center segment, which produces graphics chips for AI computing and data analytics, has turbocharged overall company growth in recent quarters. Third quarter data center revenue is expected to eclipse $12.8 billion, up 235% year-over-year.

Strength is being driven by demand from hyperscale customers like Amazon Web Services, Microsoft Azure, and Alphabet Cloud racing to build out AI-optimized infrastructure. The intense competition has fueled a powerful upgrade cycle benefiting Nvidia.

Now, hopes are high that Nvidia’s next-generation H100 processor, unveiled in late 2021 and ramping production through 2024, will drive another leg higher for data center sales.

Management’s commentary around H100 adoption and trajectory will help investors gauge expectations moving forward. An increase to the long-term target for overall company revenue, last quantified between $50 billion and $60 billion, could also catalyze more upside.

What’s Next for Gaming and Auto?

Beyond data center, Nvidia’s gaming segment remains closely monitored after a pandemic-era boom went bust in 2022 amid fading consumer demand. The crypto mining crash also slammed graphics card orders.

Gaming revenue is expected to grow 73% annually in the quarter to $2.7 billion, signaling a possible bottom but well below 2021’s peak near $3.5 billion. Investors will watch for reassurance that the inventory correction is complete and gaming sales have stabilized.

Meanwhile, Nvidia’s exposure to AI extends across emerging autonomous driving initiatives in the auto sector. Design wins and partnerships with electric vehicle makers could open another massive opportunity. Updates on traction here have the potential to pique further interest.

Evercore ISI analyst Julian Emanuel summed up the situation: “It’s still NVDA’s world when it comes to [fourth quarter] reports – we’ll all just be living in it.”

In other words, Nvidia remains the pace-setter steering tech sector sentiment to kick off 2024. And while AI adoption appears inevitable in the long run, the market remains keenly sensitive to indications that roadmap is progressing as quickly as hoped.

Microsoft Scores AI Talent by Hiring OpenAI’s Sam Altman

Posted on by slightbourne@noblecapitalmarkets.com

Microsoft emerged victorious in the artificial intelligence talent wars by hiring ousted OpenAI CEO Sam Altman and other key staff from the pioneering startup. This coup ensures Microsoft retains exclusive access to OpenAI’s groundbreaking AI technology for its cloud and Office products.

OpenAI has been a strategic partner for Microsoft since 2019, when the software giant invested $1 billion in the nonprofit research lab. However, the surprise leadership shakeup at OpenAI late last week had sparked fears that Microsoft could lose its AI edge to hungry rivals.

Hiring Altman and other top OpenAI researchers nullifies this threat. Altman will lead a new Microsoft research group developing advanced AI. Joining him from OpenAI are co-founder Greg Brockman and key staff like Szymon Sidor.

This star-studded team will provide Microsoft with a huge boost in the race against Google, Amazon and Apple to dominate artificial intelligence. Microsoft’s share price rose 1.5% on Monday on the news, adding nearly $30 billion to its valuation.

The poaching also prevents Altman from jumping ship to competitors, according to analysts. “If Microsoft lost Altman, he could have gone to Amazon, Google, Apple, or a host of other tech companies,” said analyst Dan Ives of Wedbush Securities. “Instead he is safely in Microsoft’s HQ now.”

OpenAI Turmoil Prompted Microsoft’s Bold Move

The impetus for Microsoft’s talent grab was OpenAI’s messy leadership shakeup last week. Altman and other executives were reportedly forced out by OpenAI board chair.

The nonprofit recently created a for-profit subsidiary to commercialize its research. This entity was prepping for a share sale at an $86 billion valuation that would financially reward employees. But with Altman’s ouster, these lucrative payouts are now in jeopardy.

This uncertainty likely prompted top OpenAI staff to leap to the stability of Microsoft. Analysts believe more employees could follow as doubts grow about OpenAI’s direction under Emmett Shear.

Microsoft’s infrastructure and resources also make it an attractive home. The tech giant can provide the enormous computing power needed to develop ever-larger AI models. OpenAI’s latest system, GPT-3, required 285,000 CPU cores and 10,000 GPUs to train.

By housing OpenAI’s brightest minds, Microsoft aims to supercharge its AI capabilities across consumer and enterprise products.

The Rise of AI and Competition in the Cloud

Artificial intelligence is transforming the technology landscape. AI powers everything from search engines and digital assistants to facial recognition and self-driving cars.

Tech giants are racing to lead this AI revolution, as it promises to reshape industries and create trillion-dollar markets. This battle spans hardware, software and talent acquisition.

Microsoft trails category leader Google in consumer AI, but leads in enterprise applications. Meanwhile, Amazon dominates the cloud infrastructure underpinning AI development.

Cloud computing and AI are symbiotic technologies. The hyperscale data centers operated by Azure, AWS and Google Cloud provide the computational muscle for AI training. These clouds also allow companies to access AI tools on-demand.

This has sparked intense competition between the “Big 3” cloud providers. AWS currently has 33% market share versus 21% for Azure and 10% for Google Cloud. But Microsoft is quickly gaining ground.

Hiring Altman could significantly advance Microsoft’s position. His team can create exclusive AI capabilities that serve as a differentiator for Azure versus alternatives.

Microsoft’s Prospects in AI and the Stock Market

Microsoft’s big OpenAI poach turbocharged its already strong prospects in artificial intelligence. With Altman on board, Microsoft is better positioned than any rival to lead the next wave of AI innovation.

This coup should aid Microsoft’s fast-growing cloud business. New AI tools could help Microsoft chip away at AWS’s dominance while holding off Google Cloud.

If Microsoft extends its edge in enterprise AI, that would further boost revenue and earnings. This helps explain Wall Street’s positive reaction lifting Microsoft’s stock 1.5% and adding $30 billion in market value.

The success of cloud and AI has fueled Microsoft’s transformation from a stagnant also-ran to a Wall Street darling. Its stock has nearly tripled since early 2020 as earnings rapidly appreciate thanks to its cloud and subscription-based revenue.

Microsoft stock trades at a reasonable forward P/E of 25 and offers a dividend yield around 1%. If Microsoft keeps leveraging AI to expand its cloud business, its stock could have much further to run.

Hiring Altman and deploying OpenAI’s technology across Microsoft’s vast resources places a momentous technology advantage within the company’s grasp. Realizing this potential would be a major coup for Satya Nadella as CEO. With OpenAI’s crown jewels now safely in house, Microsoft’s tech lead looks more secure than ever.

Microsoft Makes Waves with New AI and ARM Chips

Posted on by slightbourne@noblecapitalmarkets.com

Microsoft made waves this week by unveiling its first ever custom-designed chips at the Ignite conference. The tech giant introduced two new processors: the Maia 100 chip for artificial intelligence workloads and the Cobalt 100 chip for general computing purposes. These new silicon offerings have the potential to shake up the chip industry and cloud computing markets.

The Maia 100 is Microsoft’s answer to the AI accelerators from rivals like Nvidia and Amazon. It is tailored to boost performance for AI tasks like natural language processing. During Ignite, Microsoft demonstrated Maia handling queries for its Bing search engine, powering the Copilot coding assistant, and running large OpenAI language models.

Microsoft has been collaborating closely with OpenAI and is a major investor in the AI research company. OpenAI’s popular ChatGPT was trained on Azure using Nvidia GPUs. By designing its own chip, Microsoft aims to reduce reliance on third-party silicon for AI workloads.

Though performance details remain unclear, Microsoft stated that Maia handles AI tasks with high throughput and low latency. It emphasized efficiency as a key design goal. The chip was engineered in close consultation with Microsoft’s internal AI teams to ensure it fits their requirements.

Microsoft has created novel liquid cooling technology called Sidekicks to work alongside Maia server racks. This advanced thermal management unlocks Maia’s full processing capacity while avoiding the overheating issues that often plague GPU-powered data centers.

When available on Azure, Maia will provide customers access to specialized AI hardware on demand instead of buying dedicated GPUs. Microsoft did not provide a timeline for Maia’s availability or pricing. But offering it as a cloud service instead of a physical product sets Maia apart from AI chips from Intel, Nvidia and others.

The second new chip announced at Ignite was the Cobalt 100 ARM-based processor for general computing. It is expected to deliver a 40% performance boost over existing Azure ARM chips from Ampere.

Microsoft believes Cobalt will provide a compelling alternative to Intel’s server CPUs for cloud workloads. Companies like Amazon have already demonstrated success in cloud data centers by transitioning from Intel to custom ARM chips.

Virtual machines powered by Cobalt will become available on Azure in 2024. Microsoft is currently testing it for key services like Teams and Azure SQL database. More efficient ARM servers can translate to lower costs for cloud customers.

The Cobalt announcement highlights Microsoft’s growing reliance on ARM architecture across its cloud infrastructure. ARM chips are known for power efficiency in mobile devices, but companies like Amazon, Microsoft and Apple now recognize their benefits for data centers too.

By designing its own server-class ARM processor, Microsoft can optimize performance and features specifically for its cloud services. With both Maia and Cobalt, Microsoft aims to give Azure a competitive edge over rivals like AWS and Google Cloud.

Microsoft has lagged behind in cloud infrastructure market share, but introducing unique silicon could help close the gap. Its vertically integrated approach produces chips tailor-made for AI and its cloud platform. With demand for AI compute and cloud services booming, Microsoft’s gambit on custom chips could soon pay dividends.

Airbnb Makes First Acquisition as Public Company, Buys AI Startup

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Airbnb has made its first acquisition since going public in 2020, purchasing artificial intelligence startup Gameplanner.AI for just under $200 million. The deal marks Airbnb’s intent to integrate more AI technology into its platform to enhance the user experience.

Gameplanner.AI was founded in 2020 and has operated in stealth mode, away from the public eye. The startup was co-founded by Adam Cheyer, one of the original creators of the Siri voice assistant acquired by Apple. Cheyer also co-founded Viv Labs, the technology behind Samsung’s Bixby voice assistant.

With the acquisition, Airbnb is bringing Cheyer’s AI expertise in-house. In a statement, Airbnb said Gameplanner.AI will accelerate development of AI projects designed to match users to ideal travel recommendations.

Airbnb’s CEO Brian Chesky has previously outlined plans to transform Airbnb into a “travel concierge” that learns about user preferences over time. The integration of Gameplanner.AI’s technology could allow Airbnb to provide highly personalized suggestions for homes and experiences based on an individual’s travel history and interests.

For example, the AI could recommend beach houses for a user that has booked seaside destinations in the past, or suggest museums and restaurants suited to a traveler’s tastes. This would enhance the trip planning experience and help users discover new, relevant options.

The acquisition aligns with Chesky’s vision to have AI play a central role in Airbnb’s future. With Gameplanner.AI’s specialized knowledge, Airbnb can refine its AI models and more seamlessly incorporate predictive data, natural language processing, and machine learning across its apps and website.

Strategic First Acquisition for Airbnb

The purchase of Gameplanner.AI is Airbnb’s first acquisition since going public in December 2020. The deal could signal a shift in Airbnb’s M&A strategy as it looks to supplement organic growth with targeted acquisitions.

The ability to tap into Gameplanner.AI’s talent pool and proprietary technology accelerates Airbnb’s timeline for deploying more sophisticated AI tools. Developing similar capabilities in-house could have taken years and delayed the introduction of new AI features.

Acquiring an established startup with proven expertise allows Airbnb to boost its competitive edge in AI much faster. As travel continues to rebound from the pandemic, Airbnb can capitalize on these enhancements sooner to attract and retain users.

The Gameplanner.AI deal is relatively small for Airbnb, which as of September 2023 held $11 billion in cash and liquid assets on its balance sheet. But the acquisition could pave the way for more M&A deals that augment Airbnb’s core business.

As Airbnb branches out into new offerings like Airbnb Experiences and long-term rentals, the company may seek to acquire startups innovating in these spaces as well. For investors, Airbnb’s renewed openness to acquisitions makes it a more well-rounded and potentially appealing target.

AI Race in Travel Heats Up

Airbnb’s acquisition also comes amid surging demand for AI across the travel industry. Google is rumored to be investing hundreds of millions into a startup called Character AI that creates virtual travel companions powered by artificial intelligence.

Character AI lets users chat with AI versions of celebrities and public figures, including a virtual travel advisor designed to mimic the personality and advice of Sir David Attenborough.

With travel demand rebounding sharply, Google and Airbnb are demonstrating the value of AI for reinventing the trip planning and booking process. Both companies recognize the technology’s potential for driving personalization and convenience in the fiercely competitive sector.

As part of the wider rush to AI adoption, expect Airbnb’s move to spur more activity in the space as other travel platforms vie to enhance customer experiences through intelligent automation. The Gameplanner.AI acquisition gives Airbnb first-mover advantage, but likely won’t be the last pivot toward AI we see in the industry.

For Airbnb, integrating advanced AI unlocks tremendous opportunity to tighten its grip on the global accommodation and experiences market. With innovation led by strategic acquisitions like this, Airbnb aims to extend its position as the premier one-stop shop for travel.

BigBear.ai Makes Bold Move to Lead Vision AI Industry with Acquisition of Pangiam

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BigBear.ai, a provider of AI-powered business intelligence solutions, has announced the acquisition of Pangiam, a leader in facial recognition and biometrics, for approximately $70 million in an all-stock deal. The acquisition represents a major strategic move by BigBear.ai to expand its capabilities and leadership in vision artificial intelligence (AI).

Vision AI refers to AI systems that can perceive, understand and interact with the visual world. It includes capabilities like image and video analysis, facial recognition, and other computer vision applications. Vision AI is considered one of the most promising and rapidly growing AI segments.

With the acquisition, BigBear.ai makes a big bet on vision AI and aims to create one of the industry’s most comprehensive vision AI portfolios. Pangiam’s facial recognition and biometrics technologies will complement BigBear.ai’s existing computer vision capabilities.

Major Boost to Government Business

A key rationale and benefit of the deal is expanding BigBear.ai’s business with U.S. government defense and intelligence agencies. The company currently serves 20 government customers with its predictive analytics solutions. Adding Pangiam’s technology and expertise will open significant new opportunities.

Pangiam brings an impressive customer base that includes the Department of Homeland Security, U.S. Customs and Border Protection, and major international airports. Its vision AI analytics help these customers streamline operations and enhance security.

According to Mandy Long, BigBear.ai CEO, the combined entity will be able to “pursue larger customer opportunities” in the government sector. Leveraging Pangiam’s portfolio is expected to result in larger contracts for expanded vision AI services.

CombiningComplementary Vision AI Technologies

Technologically, the acquisition enables BigBear.ai to provide comprehensive vision AI solutions. Pangiam’s strength lies in near-field applications like facial recognition and biometrics. BigBear.ai has capabilities in far-field vision AI that analyzes wider environments.

Together, the combined portfolio covers the full spectrum of vision AI’s possibilities. BigBear.ai notes this full stack capability will be unique in the industry, giving the company an edge over other players.

The vision AI integration also unlocks new potential for BigBear.ai’s existing government customers. Its current predictive analytics solutions can be augmented with Pangiam’s facial recognition and biometrics tools. This builds on the company’s strategy to cross-sell new capabilities to established customers.

Long describes the alignment of Pangiam and BigBear.ai’s vision AI prowess as a key factor that will “vault solutions currently available in market.” The combined innovation assets create opportunities to push vision AI technology forward and build next-generation solutions.

Fast-Growing Market Opportunities

The acquisition comes as vision AI represents a $20 billion market opportunity predicted to grow at over 20% CAGR through 2030. It is one of the most dynamic segments within the booming AI industry.

With Pangiam under its wing, BigBear.ai is making a major play for leadership in this high-potential space. The new capabilities and customer reach significantly expand its addressable market in areas like government, airports, identity verification, and border security.

BigBear.ai also gains vital talent and IP to enhance its vision AI research and development efforts. This will help fuel its ability to bring new innovations to customers seeking advanced vision AI systems.

In a statement, BigBear.ai CEO Mandy Long called the merger a “holy grail” deal that delivers full spectrum vision AI capabilities spanning near and far field environments. It positions the newly combined company to capitalize on surging market demand from government and commercial sectors.

The proposed $70 million acquisition shows BigBear.ai is putting its money where its mouth is in terms of dominating the up-and-coming vision AI arena. With Pangiam’s tech and talent on board, BigBear.ai aims to aggressively pursue larger opportunities and cement its status as an industry frontrunner.

AMD’s Future Hinges on AI Chip Success

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Chipmaker Advanced Micro Devices (AMD) offered an optimistic forecast this week for its new data center AI accelerator chip, predicting $2 billion in sales for the product in 2024. This ambitious target represents a crucial test for AMD as it seeks to challenge rival Nvidia’s dominance in the artificial intelligence (AI) chip market.

AMD’s forthcoming MI300X processor combines the functionality of a CPU and GPU onto a single chip optimized for AI workloads. The chipmaker claims the MI300X will deliver leadership performance and energy efficiency. AMD has inked deals with major hyperscale cloud customers to use the new AI chip, including Amazon Web Services, Google Cloud, Microsoft Azure and Oracle Cloud.

The $2 billion revenue projection for 2024 would represent massive growth considering AMD expects a modest $400 million from the MI300X this quarter. However, industry analysts caution that winning significant market share from Nvidia will prove challenging despite AMD’s technological advancements. Nvidia currently controls over 80% of the data center AI accelerator market, fueled by its popular A100 and H100 chips.

“The AI chip market is still in its early phases, but it’s clear Nvidia has built formidable customer loyalty over the past decade,” said Patrick Moorhead, President of Moor Insights & Strategy. “AMD will need to aggressively discount and wow customers with performance to take share.”

AMD’s fortunes sank earlier this year as the PC market slumped and excess inventory weighed on sales. Revenue from the company’s PC chips dropped 42% in the third quarter. However, AMD sees data center and AI products driving its future growth. The company aims to increase data center revenue by over 60% next year, assuming the MI300X gains traction.

But AMD faces headwinds in China due to new U.S. export rules limiting the sale of advanced AI chips there. “AMD’s ambitious sales target could prove difficult to achieve given the geopolitical climate,” said Maribel Lopez, Principal Analyst at Lopez Research. China is investing heavily in AI and domestic chipmakers like Baidu will be courting the same hyperscale customers.

Meanwhile, Intel aims to re-enter the data center GPU market next year with its new Ponte Vecchio chip. Though still behind Nvidia and AMD, Intel boasts financial resources and manufacturing scale that shouldn’t be underestimated. The AI chip market could get very crowded very quickly.

AMD CEO Lisa Su expressed confidence in meeting customer demand and hitting sales goals for the MI300X. She expects AMD’s total data center revenue mix to shift from approximately 20% today to over 40% by 2024. “The AI market presents a tremendous opportunity for AMD to grow and diversify,” commented Su.

With PC sales stabilizing, AMD raising its AI chip forecast provided a sigh of relief for investors. The company’s stock rebounded from earlier losses after management quantified the 2024 sales target. All eyes will now turn to AMD’s execution ramping production and adoption of the MI300X over the coming year. AMD finally has a shot at becoming a major player in the AI chip wars—as long as the MI300X lives up to the hype.

President Biden’s Sweeping AI Executive Order: What Investors Need to Know

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On October 30th, President Biden signed a landmark executive order to increase oversight and regulation of artificial intelligence (AI) systems and technologies. This sweeping regulatory action has major implications for tech companies and investors in the AI space.

The order establishes new security and accountability standards for AI that companies must meet before releasing new systems. Powerful AI models from leading developers like Microsoft, Amazon, and Google will need to undergo government safety reviews first.

It also aims to curb harmful AI impacts on consumers by mandating privacy protections and anti-bias guardrails when algorithms are used in areas like housing, government benefits programs, and criminal justice.

For investors, this secures a leadership role for the U.S. in guiding AI development. It follows $1.6 billion in federal AI investments this fiscal year and supports American competitiveness versus China in critical tech sectors.

Here are the key takeaways for investors and industries affected:

Tech Giants – For AI leaders like Alphabet, Meta, and Microsoft, compliance costs may increase to meet new standards. But early buy-in by these companies helped shape the order to be achievable. The upfront reviews could also reduce downstream AI risks.

Chipmakers – Companies like Nvidia and Intel providing AI hardware should see continued demand with U.S. positioning as an AI hub. But if smaller competitors struggle with new rules, consolidation may occur.

Defense – AI has become vital for advanced weapons systems and national security. The order may add procurement delays but boosts accountability in this sensitive area. Northrop Grumman, Lockheed Martin and other defense contractors will adapt.

Automotive – Self-driving capabilities rely on AI. Mandating safety reviews for AI systems helps build public trust. Automakers investing heavily in autonomy like GM, Ford and Waymo will benefit.

Healthcare – AI holds promise for improving patient care and outcomes. But bias concerns have arisen, making regulation welcome. Medical AI developers and adopters such as IBM Watson Health now have clearer guidelines.

Startups – Early-stage AI innovators may face added hurdles competing as regulations rise. But they can tout adherence to government standards as a competitive advantage to enterprises adopting AI.

China Competition – China aims to lead in AI by 2030. This order counters with U.S. investment, tech sector support, and global cooperation on AI ethics. Investors can have confidence America won’t cede this key industry.

While adaptation will be required, investors can find opportunities within the AI landscape as it evolves. Companies leaning into the new rules and transparency demands can realize strategic gains.

But those lagging in ethics and accountability may see valuations suffer. disciplines like algorithmic bias auditing will now become critical enterprise functions.

Overall the AI executive order puts guardrails in place against unchecked AI harms. Done right, it can increases trust and spur responsible innovation. That’s a bullish signal for tech investors looking to deploy capital into this transformative sector.

Nvidia and Chip Stocks Tumble Amid Escalating China-U.S. AI Chip Export Tensions

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Shares of Nvidia and other semiconductor firms tumbled Tuesday morning after the U.S. announced stringent new curbs on exports of artificial intelligence chips to China. The restrictions spooked investors already on edge about the economic fallout from deteriorating U.S.-China relations.

Advanced AI chips like Nvidia’s flagship A100 and H100 models are now barred from shipment to China, even in downgraded versions permitted under prior rules. Nvidia stock plunged nearly 7% on the news, while chip stocks like Marvell, AMD and Intel sank 3-4%. The Philadelphia Semiconductor Index lost over 5%.

The export crackdown aims to hamper China’s progress in developing cutting-edge AI, which relies on massive computing power from state-of-the-art chips. U.S. officials warned China could use next-generation AI to threaten national security.

“We have specific concern with respect to how China could use semiconductor technologies to further its military modernization efforts,” said Alan Estevez, an under secretary at the Commerce Department.

But hampering China’s AI industry could substantially dent revenues for Nvidia, the dominant player in advanced AI chips. China is estimated to account for billions in annual sales.

While Nvidia said the financial impact is not immediate, it warned of reduced revenues over the long-term from tighter China controls. Investors are concerned these export curbs could be just the beginning if tensions continue to escalate between the global superpowers.

The escalating trade barriers also threaten to disrupt global semiconductor supply chains. Many chips contain components sourced from the U.S., Japan, Taiwan and other countries before final manufacturing and assembly occurs in China. The complex web of cross-border production could quickly seize up if trade restrictions proliferate.

Nvidia and its peers sank Tuesday amid fears of being caught in the crossfire of a technology cold war between the U.S. and China. Investors dumped chip stocks on worries that shrinking access to the massive Chinese market will severely depress earnings.

AI chips are essential to powering everything from data centers, autonomous vehicles, and smart devices to facial recognition, language processing, and machine learning. As AI spreads across the economy, demand for specialized semiconductors is surging.

But rivalries between the U.S. and China now threaten to put a ceiling on that growth. Both nations are aggressively competing to dominate AI research and set the global standards for integrating these transformative technologies. Access to the most powerful AI chips is crucial to these efforts.

By curbing China’s chip supply, the U.S. administration aims to safeguard America’s edge in AI development. But tech companies may pay the price through lost revenues if China restricts access to its own market in retaliation.

For the broader stock market already on edge about resurgent inflation, wars in Ukraine and the Middle East, and rising interest rates, the intensifying technology cold war represents yet another worrying threat to global economic growth. While a severe downturn may ultimately be avoided, the rising risk level underscores why investors are growing more anxious.

AMD Will Acquire AI Software Specialist Nod.ai Amid Mixed Tech IPO Environment

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AMD announced Monday that it will acquire Nod.ai, an expert in optimized artificial intelligence (AI) software solutions. The deal aims to boost AMD’s capabilities in open-source AI development tools, compilers, and models tuned for AMD data center, PC, gaming and graphics chips.

The acquisition comes during a rocky period for initial public offerings in the technology sector. Chip designer Arm Holdings, which recently went public, has seen its shares drop below its IPO price as investors grow concerned over tech valuations and growth prospects in a turbulent market.

Nod.ai: Boosting AMD’s AI Software Expertise

San Jose-based Nod.ai has developed industry-leading software that speeds the deployment of AI workloads optimized for AMD hardware, including Epyc server CPUs, Radeon gaming graphics, and Instinct data center GPUs.

Nod.ai maintains and contributes to vital open-source AI repositories used by developers and engineers globally. It also works closely with hyperscale cloud providers, enterprises and startups to deploy robust AI solutions.

AMD gains both strategic technology and rare AI software expertise through Nod.ai’s highly experienced engineering team. Nod.ai’s compiler and automation capabilities reduce the complexity of optimizing and deploying high-performance AI models across AMD’s product stack.

Market Tailwinds for AI Innovation

The pickup in AI workload optimization comes at a time when machine learning and deep learning are being rapidly adopted across industries. AI-optimized hardware and software will be critical to support resource-intensive models and deliver speed, accuracy and scalability.

AMD is looking to capitalize on this demand through its unified data center GPU architecture for AI acceleration. Meanwhile, rival Nvidia dominates the data center GPU space crucial for AI computing power.

Arm IPO Capitulates Amid Market Jitters

UK-based Arm Holdings, which supplies intellectual property for chips used in devices like smartphones, recently conducted a $40 billion IPO, one of the largest listings of 2023. However, Arm’s share price plunged below its IPO level soon after debuting in September.

The weak stock performance highlights investor skittishness around loss-making tech firms amid economic headwinds. ARM’s licensing model also faces risks as major customers like Apple and Qualcomm develop their own proprietary chip technologies and architectures.

Unlike Arm, AMD is on solid financial footing, with its data center and gaming chips seeing strong uptake. However, AMD must still convince Wall Street that its growth trajectory warrants robust valuations, especially as Intel mounts a comeback.

Betting on Open Software Innovation

AMD’s Nod.ai purchase aligns with its strategic focus on open software ecosystems that promote accessibility and standardization for AI developers. Open software and hardware foster collaborative innovation within the AI community.

With Nod.ai’s talents added to the mix, AMD is betting it can democratize and optimize AI workload deployment across the full range of AMD-powered devices – from data center CPUs and GPUs to client PCs, gaming consoles and mobile chipsets.

If successful, AMD could carve out an advantage as the preferred AI acceleration platform based on open software standards. This contrasts with Nvidia’s proprietary approaches and closed ecosystems tailored exclusively for its GPUs.

As AI permeates across industries and applications, AMD is making the right long-term bet on open software innovation to unlock the next phase of computing.

Amazon Bets Big on AI Startup to Advance Generative Tech

Posted on by slightbourne@noblecapitalmarkets.com

E-commerce titan Amazon is making a huge investment into artificial intelligence startup Anthropic, injecting up to $4 billion into the budding firm. The massive funding underscores Amazon’s ambitions to be a leader in next-generation AI capabilities.

Anthropic is a two-year old startup launched by former executives from AI lab OpenAI. The company recently introduced its new chatbot called Claude, designed to converse naturally with humans on a range of topics.

While Claude has similarities to OpenAI’s popular ChatGPT, Anthropic aims to take natural language AI to the next level. Amazon’s investment signals its belief in Anthropic’s potential to pioneer groundbreaking generative AI.

Generative AI refers to AI systems that can generate new content like text, images, or video based on data they are trained on. The technology has exploded in popularity thanks to ChatGPT and image generator DALL-E 2, sparking immense interest from Big Tech.

Amazon is positioning itself to capitalize on this surging interest in generative AI. As part of the deal, Amazon Web Services will become Anthropic’s primary cloud platform for developing and delivering its AI services.

The startup will also let AWS customers access exclusive features to customize and fine-tune its AI models. This tight integration gives Amazon a competitive edge by baking Anthropic’s leading AI into its cloud offerings.

Additionally, Amazon will provide custom semiconductors to turbocharge training for Anthropic’s foundational AI models. These chips aim to challenged Nvidia’s dominance in supplying GPUs for AI workloads.

With its end-to-end AI capabilities across hardware, cloud services and applications, Amazon aims to be the go-to AI provider. The Anthropic investment caps off a flurry of activity from Amazon to own the AI future.

Recently, Amazon unveiled Alexa Voice, AI-generated voice assistant. The company also launched Amazon Bedrock, a service enabling companies to easily build custom AI tools using Amazon’s machine learning models.

And Amazon Web Services already offers robust AI services like image recognition, language processing, and data analytics to business clients. Anthropic’s generative smarts will augment these solutions.

The race to lead in AI accelerated after Microsoft’s multi-billion investment into ChatGPT creator OpenAI in January. Google, Meta and others have since poured billions into AI startups to not get left behind.

Anthropic has already raised funding from top tier backers like Google’s VC arm and Salesforce Ventures. But Amazon’s monster investment catapults the startup into an elite group of AI startups tapping into Big Tech’s cash reserves.

The deal grants Amazon a minority stake in the startup, suggesting further collaborations ahead. With Claude 2 generating buzz, Anthropic’s next-gen AI technology and Amazon’s vast resources could be a potent combination.

For Amazon, owning a piece of a promising AI startup hedges its bets should generative AI disrupt major industries. And if advanced chatbots like Claude reshape how customers interact with businesses, Amazon is making sure it has skin in the game.

The e-commerce behemoth’s latest Silicon Valley splash cements its position as an aggressive AI player not content following others. If Amazon’s bet on Anthropic pays off, it may pay dividends in making Amazon a go-to enterprise AI powerhouse.

Tesla’s Dojo Supercomputer Presents Massive Upside for Investors

Posted on by slightbourne@noblecapitalmarkets.com

Tesla’s new Dojo supercomputer could unlock tremendous value for investors, according to analysts at Morgan Stanley. The bank predicts Dojo could boost Tesla’s market valuation by over $600 billion.

Morgan Stanley set a sky-high 12-18 month price target of $400 per share for Tesla based on Dojo’s potential. This implies a market cap of $1.39 trillion, which is nearly 76% above Tesla’s current $789 billion valuation.

Tesla only began producing Dojo in July 2022 but plans to invest over $1 billion in the powerful supercomputer over the next year. Dojo will be used to train artificial intelligence models for autonomous driving.

Morgan Stanley analysts estimate Dojo could enable robotaxis and software services that extend far beyond Tesla’s current business of vehicle manufacturing. The bank nearly doubled its 2040 revenue projection for Tesla’s network services division from $157 billion to $335 billion thanks to Dojo.

By licensing self-driving software powered by Dojo to third-party transportation fleets, Tesla could generate tremendous high-margin revenues. Morgan Stanley sees network services delivering over 60% of Tesla’s core earnings by 2040, up from just 30% in 2030.

Thanks to this upside potential, Morgan Stanley upgraded Tesla stock from Equal-Weight to Overweight. The analysts stated “Dojo completely changes the growth trajectory for Tesla’s autonomy business.”

At its current $248.50 share price, Tesla trades at a lofty forward P/E ratio of 57.9x compared to legacy automakers like Ford at 6.3x and GM at 4.6x. But if Morgan Stanley’s bull case proves accurate, Tesla could rapidly grow into its valuation over the next decade.

In summary, Tesla’s AI advantage with Dojo makes the stock’s premium valuation more reasonable. Investors buying at today’s prices could reap huge gains if Dojo unlocks a new $600 billion revenue stream in autonomous mobility services.

The Power and Potential of Dojo

Dojo represents a massive investment by Tesla as it aims to lead the future of autonomous driving. The specialized supercomputer is designed to train deep neural networks using vast amounts of visual data from Tesla’s fleet of vehicles.

This differentiated AI training will allow Tesla to improve perceptions for full self-driving at a faster pace. As self-driving functionality becomes more robust, Tesla can unlock new revenue opportunities.

Morgan Stanley analyst Adam Jones stated: “If Dojo can help make cars ‘see’ and ‘react,’ what other markets could open up? Think of any device at the edge with a camera that makes real-time decisions based on its visual field.”

Dojo’s processing power will permit Tesla to develop advanced simulations that speed up testing. The supercomputer’s capacity is expected to exceed that of the top 200 fastest supercomputers combined.

Tesla claims Dojo will drive down the costs of training networks by orders of magnitude. This efficiency can translate into higher margins as costs drop for autonomous AI development.

Dojo was designed in-house by Tesla AI director Andrej Karpathy and his team. Karpathy called Dojo the “most exciting thing I’ve seen in my career.” With Dojo, Tesla is aiming to reduce reliance on external cloud providers like Google and Amazon.

Morgan Stanley Boosts Tesla Price Target by 60%

The potential of monetizing Tesla’s self-driving lead through Dojo led analysts at Morgan Stanley to dramatically increase their expectations.

Led by analyst Adam Jones, Morgan Stanley boosted its 12-18 month price target on Tesla stock by 60% to $400 per share. This new level implies a market value for Tesla of nearly $1.39 trillion.

Hitting this price target would mean Tesla stock gaining about 76% from its current level around $248.50. Tesla shares jumped 6% on Monday following the report as investors reacted positively.

Jones explained the sharply higher price target by stating: “Dojo completely changes the growth trajectory for Tesla’s autonomy business.”

He expects Dojo will open up addressable markets for Tesla that “extend well beyond selling vehicles at a fixed price.” In other words, Dojo can turn Tesla into more of a high-margin software and services provider.

Take a look at One Stop Systems (OSS), a US-based company that designs and manufactures AI Transportable edge computing modules and systems that are used in autonomous vehicles.