Hot Stocks: The 3 Best Opportunities for Investing in Machine Learning
Machine learning has been an integral part of artificial intelligence (AI) advances. Over the last two years, the number of use cases for the technology has grown exponentially.
First, let’s highlight some of the few applications of machine learning today. In healthcare, doctors are using ML models to analyze medical imaging to accurately detect diseases like cancer early. Another positive development lies within drug discovery and manufacturing. Here, machine learning predicts molecule behavior and discovers new molecules.
Also, machine learning has permeated the most mundane part of our lives. For instance, entertainment services like YouTube and Spotify (NYSE:SPOT) heavily rely on machine learning to recommend personalized content. Spotify research has disclosed that machine learning touches every aspect of the service.
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Besides the use cases mentioned above, machine learning is used in finance for fraud detection, algorithmic trading and improving credit scoring models. Retailers are using the technology for customer service, online recommendation engines and inventory management. All these use cases validate the investment case for these machine learning stocks.
Alphabet (GOOG, GOOGL)
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One of the most obvious machine learning stocks to buy is Alphabet (NASDAQ:GOOG, NASDAQ:GOOGL). Indeed, Google has been a pioneer in machine learning. It continues to lead today with projects like TensorFlow, its open-source ML framework.
Notably, Google was among the earliest companies to integrate machine learning technology into its products. The company first deployed ML models to improve Search in 2001. Today, Alphabet has incorporated machine learning into several products, including YouTube, Photos and Google Cloud.
Alphabet’s ML efforts have been particularly important in personalizing the user experience. For instance, personalized recommendation engines have improved engagement on platforms like YouTube. As a result, the platform has grown viewership and attracted more advertisers.
The company’s ML efforts go beyond the consumer. Its Google Cloud division offers developers and enterprises AI and machine learning services. Its data warehouse, BigQuery, has integrated advanced ML capabilities. Impressively, this enables customers to analyze 110 terabytes of data per second. That’s the reason the division’s revenue growth has been impressive, growing from $13 billion in 2020 to $33 billion in 2023.
Without a doubt, Alphabet is one of the best machine learning stocks. Since 2001, when Google first incorporated machine learning into Search, Google has been an innovator in the space. Its streak of innovative achievements underlines its position as a leader.
Apple (AAPL)
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One reason Apple (NASDAQ:AAPL) has such a fanatical fan base is its superior product and user experience. And guess what? The incredible experience is a result of the heavy application of machine learning.
The company integrates the technology into its device ecosystem, starting with basic features like Face ID, which uses facial recognition powered by machine learning models. Other features that rely on the technology include the camera and Siri. For example, machine learning supports personalized responses from Siri.
Health and wellness is an area in which the technology giant has been making significant investments. It is no surprise that Tim Cook has stated that the company’s biggest contribution to humanity will be in health. On that note, machine learning is central to these ambitions.
One product that Apple has heavily integrated machine learning is the Apple Watch, a product that’s become one of consumers’ most popular health companions. By integrating ML, the Apple Watch can accurately monitor your heart rate and even detect a fall.
Lastly, Apple has always been one of the best consumer privacy advocates. Today, the company is leveraging AI across its ecosystem of devices and services to offer consumers the best privacy and data protection. For instance, it provides intelligent tracking prevention to reduce tracking by advertisers.
All of the above ML applications point to a company at the leading edge of AI. While naysayers declare that Apple has missed the AI boat, it’s time to load up on one of the best machine learning stocks.
Nvidia (NVDA)
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The hardware to run machine learning algorithms is just as important as the software. Companies that produce GPUs and specialized chips for AI processing are critical to the ecosystem. And on the hardware front, the undisputed leader is Nvidia (NASDAQ:NVDA).
Today, the semiconductor company is experiencing soaring demand for its GPUs used in machine learning applications. Every data center provider and technology company wants Nvidia’s best GPUs. These extremely powerful chips are necessary for training models as well as inference.
Specifically, Nvidia’s H100 GPUs have been the backbone of many cloud AI services. Customers like Microsoft (NASDAQ:MSFT) and Alphabet are relying upon these chips to build out their AI infrastructure. Also, the company is developing other cutting-edge machine learning solutions. For instance, its DRIVE platform leverages machine learning to deliver autonomous vehicle navigation.
Despite its massive leadership in machine learning, Nvidia is widening the gap against its competitors. On February 18, the company launched its most powerful chips, the Grace Blackwell 200 Superchips. These chips will enhance Nvidia’s dominance in ML hardware and software.
NVDA’s innovation is unparalleled and has triggered an AI arms race. The company has been a key beneficiary, with revenues growing by 126% in fiscal year 2024. The GB200 will further extend the company’s dominance in the AI race. Therefore, Wall Street is doubling down on the stock and expects further upside.
On the date of publication, Charles Munyi did not hold (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.
Charles Munyi has extensive writing experience in various industries, including personal finance, insurance, technology, wealth management and stock investing. He has written for a wide variety of financial websites including Benzinga, The Balance and Investopedia.
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