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Machine learning is an integral part of artificial intelligence (A.I.) will proceed. Over the past two years, the number of use cases for this technology has grown exponentially.
First, let's focus on some applications of machine learning today. In the medical field, doctors use ML models to analyze medical images to detect diseases such as cancer early and accurately. Another positive development is in the field of drug discovery and manufacturing. Here, machine learning predicts the behavior of molecules and discovers new molecules.
Machine learning is also permeating even the most mundane parts of our lives.For example, entertainment services such as YouTube and spotify (New York Stock Exchange:spot) relies heavily on machine learning to recommend personalized content. Spotify's research reveals that machine learning is impacting every aspect of the service.
In addition to the above use cases, machine learning is used in the financial sector to detect fraud, algorithmic trading, and improve credit scoring models. Retailers use this 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:googleNasdaq:Google). In fact, Google is a pioneer in machine learning. The company continues to lead with projects such as his TensorFlow, an open source ML framework.
Notably, Google was one of the first companies to integrate machine learning technology into its products. The company first introduced his ML models in 2001 to improve search. Currently, Alphabet is incorporating machine learning into several of its products, including YouTube, Photos, and Google Cloud.
Alphabet's ML efforts are particularly important in personalizing the user experience. For example, personalized recommendation engines have increased engagement on platforms like YouTube. As a result, the platform's viewership has increased and it has started to attract more advertisers.
The company's ML efforts go beyond consumers. The company's Google Cloud division offers its AI and machine learning services to developers and enterprises. Its data warehouse, BigQuery, integrates advanced ML capabilities. Amazingly, this allows the customer to analyze his 110 terabytes of data per second. That's why the sector's revenue growth has been so impressive, growing from $13 billion in 2020 to $33 billion in 2023.
Without a doubt, Alphabet is one of the best machine learning stocks. Google has been an innovator in this field since 2001, when Google first incorporated machine learning into search. The company's string of innovative achievements underlines its leadership position.
Apple (AAPL)
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one reason apple (NASDAQ:AAPL) has such a passionate following because of its superior products and user experience. And guess what? This amazing experience is the result of heavy use of machine learning.
The company is integrating this 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 this technology include the camera and Siri. For example, machine learning supports personalized responses from Siri.
Health and wellness is an area where tech giants are investing heavily. No wonder Tim Cook said the company's greatest contribution to humanity is health. In that respect, machine learning is central to these goals.
One of the products that Apple has highly integrated machine learning into is the Apple Watch, which has become one of the most popular health companions for consumers. With ML integration, Apple Watch can also accurately monitor heart rate and detect falls.
Finally, Apple has always been one of the biggest defenders of consumer privacy. Today, the company leverages AI across its ecosystem of devices and services to provide consumers with the highest privacy and data protection. For example, we offer intelligent tracking protection features that reduce tracking by advertisers.
The ML applications mentioned above all represent companies at the cutting edge of AI. While naysayers declare that Apple has missed the AI boat, it's time to invest in one of the best machine learning stocks.
Nvidia (NVDA)
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The hardware that runs machine learning algorithms is just as important as the software. Companies that make chips that specialize in GPUs and AI processing are important to the ecosystem.And when it comes to hardware, the undisputed leader is Nvidia (NASDAQ:NVDA).
The semiconductor company is currently experiencing a surge in demand for GPUs used in machine learning applications. Every data center provider and technology company wants Nvidia's best GPUs. These extremely powerful chips are required for model training and inference.
Specifically, Nvidia's H100 GPU is the backbone of many cloud AI services.customers prefer microsoft (NASDAQ:MSFT) and Alphabet rely on these chips to build their AI infrastructure. The company is also developing other cutting-edge machine learning solutions. For example, the company's DRIVE platform leverages machine learning to enable self-driving navigation.
Despite Nvidia's overwhelming leadership in machine learning, the company is widening its lead over its competitors. On February 18th, the company launched its most powerful chip, the Grace Blackwell 200 Superchips. These chips strengthen Nvidia's lead in ML hardware and software.
NVDA's innovations are unparalleled and have sparked an AI arms race. The company has seen significant benefits, with revenue increasing by 126% in fiscal year 2024. GB200 will further expand the company's advantage in the AI race. Therefore, Wall Street is doubling down on the stock and expecting further gains.
On the date of publication, Charles Munyi did not have (directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer and are influenced by InvestorPlace.com. Publishing guidelines.
Charles Munyi has extensive writing experience in a variety of industries, including personal finance, insurance, technology, wealth management, and equity investing. He writes for various financial websites including Benzinga, The Balance, and Investopedia.
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