3 best artificial intelligence stocks to buy right now
IDC estimates that the global artificial intelligence (AI) market is on track to generate $ 327.5 billion in revenue in 2021, a jump of 16.4% from last year. The research firm predicts that spending on AI hardware, software and services could increase at an annual rate of 17.5% through 2024 and reach $ 554 billion in revenue.
There are a number of ways that investors can take advantage of this massive opportunity, as there is a plethora of artificial intelligence stocks to choose from. However, Apple (NASDAQ: AAPL), Advanced micro-systems (NASDAQ: AMD), and Micronic Technology (NASDAQ: MU) look like three of the best stocks investors can buy right now to take advantage of the huge AI opportunity.
Apple derives most of its revenue from the sale of hardware products such as iPhone, iPad, MacBooks, portable devices, smart home devices, and other accessories. These product lines generated nearly 78% of Apple’s revenue in the fourth quarter of fiscal 2021, with services activities accounting for the remainder. The tech giant has already built AI-powered features into its hardware devices, such as Face ID, card suggestions, handwriting recognition, and digital assistant Siri, among others.
However, Apple appears to be making a bigger push into AI as it is reportedly working on a fully autonomous electric vehicle. Third-party reports indicate that Apple aims to provide an electrically powered autonomous vehicle within the next four years. The company has reportedly completed most of the core development of the processor that will power its autonomous driving system.
Apple’s autonomous car chip will be based on neural processors that will allow its cars to run 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 autonomous driving technology and help the company perfect 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 entering 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 register an annual growth rate of 63% through 2030, with most of that growth coming from North America.
Apple’s entry into this space could prove to be a smart long-term move and become a major catalyst for the company which is currently profiting from another hot trend in the form of 5G smartphones. The fact that Apple is trading at 28 times earnings, compared to Nasdaq 100The earnings multiple of 36’s, means investors can enter this potential AI winner at an attractive valuation right now.
2. Advanced micro devices
AMD’s EPYC server processors and graphics processing units (GPUs) will play a critical role in the adoption of AI applications. Indeed, the deep neural networks that power AI applications, such as self-driving cars or other real-time applications, should be able to perform hundreds of thousands, millions, or even billions of operations. in order to recognize various objects and react to them correctly.
AMD’s chips help data centers and supercomputers cope with the enormous workload required to activate AI applications. The chipmaker recently unveiled the Instinct MI200 series of data center accelerators based on the CDNA 2 architecture, claiming that these chips are 4.9 times faster while performing high performance computing (HPC) operations and of AI, compared to competing data center accelerators. .
Likewise, AMD’s third generation EPYC server processors have improved AI inference capabilities over their predecessors. Unsurprisingly, AMD has seen strong growth in the adoption of its server processors and GPUs. Meta-platforms, for example, recently selected AMD’s EPYC processors for use in its hyperscale data centers that would be used to power the first metaverse – a virtual environment where people can interact with each other as 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 number could rise in the years to come, as Meta CEO Mark Zuckerberg pointed out during 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 handle data-intensive workloads. According to SK Hynix, hyperscale data center deployments are expected to reach 1,060 by 2025, which would be double the current installed base.
Not surprisingly, the demand for data center accelerators may increase dramatically in the future. A third-party estimate indicates that data center accelerator sales could reach $ 53 billion in 2027, up from $ 4.2 billion last year, thanks to strong sales of CPUs (central processing units) and GPU. This should pave the way for strong growth at AMD and help the chipmaker remain a growth company for a long time, especially since it has other catalysts besides AI that could increase its bottom line in the long run. .
3. Micron technology
The increasing adoption of AI applications would create the need for more storage and faster memory processing. For example, data generated by an autonomous vehicle using multiple sensors and cameras will need to be processed quickly, this is where the faster DRAM (Dynamic Random Access Memory) will come into play.
Likewise, HPC data centers will create the need for more flash memory, as AI applications will need faster access to stored data, which can be provided by SSDs (SSDs) capable of transmitting data. data quickly, compared to traditional drives.
Unsurprisingly, Micron CEO Sanjay Mehrotra estimates that the need for DRAM in AI servers is six times that of standard servers. Likewise, AI servers would need twice as much SSD storage as standard servers.
The good part is that Micron is already taking steps to exploit this huge opportunity with its GDDR6X memory. The company claims that GDDR6X DRAM is suitable for AI inference applications, thanks to its system bandwidth of over 1 terabyte per second (TB / s), compared to system bandwidth of 0.7 TB / s. s from previous generations. Meanwhile, the company’s HBM2E high-bandwidth memory can exceed the 2TB / s system bandwidth, making it ideal for cloud AI training and inference.
Micron controls over 23% of the global DRAM market and 11% of the NAND flash market, so it stands to gain from the centuries-old growth in the memory market which counts AI as one of its catalysts. The good thing is that investors can access Micron stock at a very low valuation right now as it is trading at just 16 times trailing earnings and nine times futures earnings.
This makes it significantly cheaper than the S&P 500 index, which has an income multiple of 28.9. The purchase of Micron looks like a good deal as it is expected to record annual profit growth of over 22% over the next five years.
This article represents the opinion of the author, who may disagree with the “official” recommendation position of a premium Motley Fool consulting service. We are heterogeneous! Questioning an investment thesis – even one of our own – helps us all to think critically about investing and make decisions that help us become smarter, happier, and richer.