Top 3 Artificial Intelligence Stocks To Buy

IDC is estimating that the global artificial intelligence (AI) market will generate $327.5 billion in revenue this year, a jump of 16% over last year’s numbers and it expects spending on AI-related hardware/software to increase at an annual rate of 17%. There are several ways investors can tap into this massive opportunity; one way would be by investing their money into certain companies with technologies such as Apple who offer products like iPhones or iPads which have been developed using Northern California based company Siri Technology LLC among others - all backed up by powerful chips designed specifically for “ intelligent machines.”

There are several ways investors can tap into this massive opportunity, as there are a plethora of artificial intelligence stocks out there to choose from. However, Apple (NASDAQ:AAPL), Advanced Micro Devices (NASDAQ:AMD), and Micron Technology (NASDAQ:MU) look like three of the best stocks investors can buy right now to benefit from the massive AI opportunity.

Apple gets most of its revenue from selling hardware products such as the iPhone, the iPad, MacBooks, wearables, smart-home devices, and other accessories. These product lines produced nearly 78% of Apple’s revenue in the fourth quarter of fiscal 2021, with the services business accounting for the rest. The tech giant has already incorporated AI-powered features into its hardware devices, such as Face ID, map suggestions, handwriting recognition, and the Siri digital assistant, among many others.

However, Apple seems to be making a bigger push into AI as it’s reportedly working on a fully autonomous electric vehicle. Third-party reports indicate that Apple is aiming to deliver an electric-powered self-driving vehicle in the next four years. The company has reportedly completed most of the core development of the processor that will be powering its self-driving system.

Apple’s self-driving car chip will be based on neural processors that will allow its cars to operate on their own. It’s worth noting that Apple has a fleet of 69 test cars that are expected to be powered by its latest self-driving technology and help the company hone its autonomous driving system in the real world.

Wall Street seems excited about Apple’s foray into autonomous electric vehicles. Morgan Stanley analyst Katy Huberty said she believes that the entry into the self-driving car space could help Apple double its revenue and market capitalization in the long run. According to third-party estimates, the global autonomous-vehicle market is expected to clock an annual growth rate of 63% through 2030, with most of that growth coming from North America.

Apple’s move into this space could turn out to be a smart move in the long run and become a major catalyst for the company that’s currently taking advantage of another hot trend in the form of 5G smartphones. The fact that Apple is trading at 28 times earnings, as compared to the Nasdaq 100’s earnings multiple of 36, means that investors can get into this potential AI winner at an attractive valuation right now.

AMD’s EPYC server processors and data center graphics processing units (GPUs) are going to play a critical role in the adoption of AI applications. That’s because the deep neural networks that power AI applications, such as self-driving cars or other real-time applications, should be able to carry out hundreds of thousands, millions, or even billions of operations in order to recognize various objects and react to them properly.

AMD’s chips help data centers and supercomputers tackle the massive workload that’s required to enable AI applications. The chipmaker recently revealed the Instinct MI200 series of data center accelerators that are based on the CDNA 2 architecture, claiming that these chips are 4.9 times faster while carrying out high-performance computing (HPC) and AI operations, as compared to competing data center accelerators.

Similarly, AMD’s third-generation EPYC server processors have improved AI inferencing capabilities over their predecessors. Not surprisingly, AMD has been witnessing strong growth in the adoption of its server processors and GPUs. Meta Platforms, for instance, recently selected AMD’s EPYC processors for use in its hyperscale data centers that would be used to power up the former’s metaverse – a virtual environment where people can interact with each other like they do in the real world.

This win could be a big deal for AMD as Meta is expected to invest $10 billion to boost its metaverse capabilities this year. That figure could head higher in the coming years as Meta CEO Mark Zuckerberg had pointed out on the October earnings conference call.

More importantly, AI applications, such as the metaverse and self-driving cars, are expected to increase the deployment of HPC data centers, thanks to their ability to address data-intensive workloads. According to SK Hynix, hyperscale data center deployments are expected to hit 1,060 by 2025, which would be double the current installed base.

Not surprisingly, the demand for data center accelerators can shoot substantially higher in the future. A third-party estimate points out that sales of data center accelerators could hit $53 billion in 2027, as compared to $4.2 billion last year, driven by strong sales of both CPUs (central processing units) and GPUs. This should pave the way for strong growth at AMD and help the chipmaker remain a top growth stock for a long time to come, especially considering that it has other catalysts apart from AI that could boost its top and bottom lines in the long run.

The increasing adoption of AI applications would create the need for more storage and faster memory processing. For instance, the data generated by an autonomous vehicle that uses several sensors and cameras will have to be processed quickly, which is where faster DRAM (dynamic random access memory) will come into play.

Similarly, HPC data centers will create the need for more flash memory as AI applications will need faster access to stored data, which can be delivered by SSDs (solid-state drives) that can transmit data quickly, as compared to traditional drives.

Not surprisingly, Micron CEO Sanjay Mehrotra estimates that the need for DRAM in AI servers would be six times as much, compared to standard servers. Similarly, AI servers would need twice the amount of SSD storage, as compared to standard servers.

The good part is that Micron is already taking steps to tap into this massive opportunity with its GDDR6X memory. The company claims that GDDR6X DRAM is suited for AI inference applications, thanks to its system bandwidth of more than 1 terabyte per second (TB/s), as compared to the system bandwidth of 0.7 TB/s of prior generations. Meanwhile, the company’s HBM2E high-bandwidth memory can exceed system bandwidth of 2 TB/s, making it ideal for AI training and inference in the cloud.

Micron controls over 23% of the global DRAM market and 11% of the NAND flash market, so it stands to gain from the secular growth of the memory market that counts AI as one of its catalysts. The good thing is that investors can get into Micron stock at a dirt-cheap valuation right now as it’s trading for at just 16 times trailing earnings and nine times forward earnings.

This makes it substantially cheaper than the S&P 500 index, which has an earnings multiple of 28.9. Buying Micron looks like a steal as it’s expected to clock annual earnings growth of over 22% for the next five years.