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Is NVIDIA (NVDA) the Best Machine Learning Stock to Buy Now?

We recently published a list of the 10 Best Machine Learning Stocks to Buy Now. In this article, we are going to take a look at where NVIDIA Corporation (NASDAQ:NVDA) stands against other machine-learning stocks.

Grand View Research reported that the global machine-learning market was valued at $36.73 billion in 2022. It’s now expected to grow at a 34.8% CAGR from 2023 to 2030. Machine learning helps machines and systems learn from experience instead of through explicit programming. It uses algorithms to improve and analyze vast amounts of complex data to make informed decisions. Machine learning is quickly progressing as AI is rapidly expanding and transforming how businesses and individuals operate. These technological advancements are revolutionizing consumer experiences, and enabling convenient creation of digital services, products, and optimized supply chains. With this, startups can focus on specific solutions while larger companies can deliver comprehensive AI platforms.

On April 10, Amazon CEO Andy Jassy joined CNBC’s ‘Squawk Box’ to discuss the cost of AI and what has to happen to bring it down. Jassy emphasized that the growth in data center demand is now so significant that there is no foreseen attenuation here, even with ongoing macroeconomic uncertainties under tariffs. While there’s a general belief that the emergence of DeepSeek could now reduce the need for extensive data centers, processing power, and energy consumption previously forecasted at different tech companies, Jassy thinks that DeepSeek’s introduction did not disrupt any of this. Despite cost reductions that occurred have already over time, AI deployment still requires significant investment. He thinks that the current AI operations are expensive due to chip costs and other factors, but big techs, including his own company, would welcome any reductions in AI costs for customers moving forward.

Jassy underscored the demand for data centers despite tariff impacts and reflected optimism regarding lowering costs, which would potentially drive innovation and expanded use of AI across industries. AI is still limited and requires substantial human oversight as of now but it has massive potential across various sectors.

Our Methodology

We sifted through ETFs and financial media reports to compile a list of the top ML stocks. We then selected the 10 stocks that were the most popular among elite hedge funds and that analysts were bullish on. The stocks are ranked in ascending order of the number of hedge funds that have stakes in them, as of Q4 2024. The hedge fund data was sourced from Insider Monkey’s database which tracks the moves of over 900 elite money managers.

Why are we interested in the stocks that hedge funds pile into? The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter’s strategy selects 14 small-cap and large-cap stocks every quarter and has returned 373.4% since May 2014, beating its benchmark by 218 percentage points (see more details here).

A close-up of a colorful high-end graphics card being plugged in to a gaming computer.

NVIDIA Corporation (NASDAQ:NVDA)

Number of Hedge Fund Holders: 223

NVIDIA Corporation (NASDAQ:NVDA) offers essential GPUs and AI platforms that help develop and execute machine learning workloads. The company’s Compute & Networking segment encompasses the Data Center computing platforms and end-to-end networking platforms. It also includes the NVIDIA AI Enterprise and other software. The company also customizes agentic solutions to accelerate enterprise AI adoption.

Recently, the US introduced new AI Diffusion Rules that impact the global chip distribution. With this control, the spread of AI can be regulated. Despite this, Bank of America remains optimistic and reiterated a Buy rating on the company on March 28 with a $200 price target. This is mainly driven by the Blackwell system deployments by Large cloud service providers as their AI infrastructure demands expand. These CSPs include Azure, GCP, AWS, and OCI. Other applications for the company’s GPUs include GenAI and deep learning in consumer internet companies like Meta.

However, as larger tech companies try to make their own AI chips now, NVIDIA Corp.’s (NASDAQ:NVDA) market shares are threatened. It’s also facing increased competition with major tech players like Apple, Qualcomm, and AMD. For instance, the company heavily relies on the 3nm process nodes that Taiwan Semiconductor Manufacturing Company makes. These enable the production of smaller and more energy-efficient chips at NVIDIA Corp. (NASDAQ:NVDA).

Guinness Global Innovators is highly bullish on NVIDIA Corp. (NASDAQ:NVDA) due to its dominant AI chip market position. It stated the following in its Q4 2024 investor letter:

“For a second year running, NVIDIA Corporation (NASDAQ:NVDA) was the Fund’s top performing stock, delivering a stellar return of +177.7% over the year. Since the beginning of last year, Nvidia’s ‘Hopper’ GPUs have been at the centre of exploding demand for chips powerful and efficient enough to facilitate the energy intensive requirements of AI processes within datacentres. Initially possessing over 95% of market share in these types of chips, Nvidia have been quick to entrench their position as the technological leader in the space, launching the successor to the current ‘Hopper’ GPU in March, Blackwell, inhibiting the likes of AMD and Intel making meaningful inroads in taking share of the fast-growing market. Compared to the previous iteration (Hopper) which is continuing to fuel Nvidia’s extreme revenue growth, the Blackwell chip is twice as powerful for training AI models and has 5 times the capability when it comes to “inference” (the speed at which AI models respond to queries). Throughout the year, Nvidia’s financial performance has remained resilient. Quarterly revenues hit $35.1 billion in their most recent quarter, beating consensus expectations by 6% and representing a +94% year-over-year increase. Additionally, Nvidia’s data centre segment, driven by the Hopper (H100) chip, grew fivefold over the past year, underscoring the sustained demand for advanced AI infrastructure. The H100 chip, priced at around $40,000, continues to see significant adoption due to its ability to enhance AI model training efficiency while lowering overall costs. This growth is expected to continue as companies invest in upgrading existing data centres and building new ones, with Nvidia well-positioned to capture a significant share of the estimated $2 trillion market opportunity over the next five years. There have been some concerns over Blackwell production delays causing share price volatility however, Nvidia has recovered swiftly, driven by positive earnings results through the year and assurances from management regarding future supply. Additionally, the release of the H200 chip promises to extend Nvidia’s technological leadership, ensuring continued momentum into 2025. While Nvidia’s valuation remains a topic of debate, the stock is not at a significant premium to history, and it still appears reasonable given its dominant market position, innovative prowess, and exposure to long-term secular growth trends in AI, cloud computing, and data infrastructure. As a result, Nvidia remains well-positioned to deliver sustained outperformance over the long term, making it a cornerstone of growth-oriented portfolios.”

Overall, NVDA ranks 5th on our list of the best machine learning stocks to buy now. While we acknowledge the growth potential of NVDA, our conviction lies in the belief that AI stocks hold great promise for delivering high returns and doing so within a shorter time frame. There is an AI stock that went up since the beginning of 2025, while popular AI stocks lost around 25%. If you are looking for an AI stock that is more promising than NVDA but that trades at less than 5 times its earnings, check out our report about this cheapest AI stock.

READ NEXT: 20 Best AI Stocks To Buy Now and 30 Best Stocks to Buy Now According to Billionaires.

Disclosure: None. This article is originally published at Insider Monkey.

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Click to continue reading…