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Computers excel at number-crunching, but not at the kinds of things people do with ease: language processing, visual perception, manipulating objects, reasoning, planning, and learning. Artificial intelligence, or AI -- including its offshoots deep learning and machine learning -- uses computers to perform tasks that normally require human intelligence.
Machine learning involves training a system with huge amounts of data, then using that trained system to make inferences about new data it’s never seen. The simplest example is a system designed for detecting objects in images. Images tagged with the objects they contain are fed into the system, and the system “learns” how to detect those objects in other images. The more data it learns from, the more accurate the system will become.
Companies employ artificial intelligence in two main ways:
Machine learning, or AI, involves training a system with huge amounts of data, then using that trained system to make inferences about new data it has never seen.
|NVIDIA (NASDAQ:NVDA)||Graphics chips and self-driving cars|
|IBM (NYSE:IBM)||Augmenting human intelligence across industries|
|Micron Technology (NASDAQ:MU)||Memory chips for data centers and self-driving cars|
Source: Company websites
Machine learning’s training phase demands a lot of computing power; its inference phase requires less. Graphics chips, used primarily for rendering video games, do both tasks well. Leading graphics chip company NVIDIA (NASDAQ:NVDA) has taken advantage of the AI boom, with its graphics cards becoming the de facto standard in data centers around the world.
NVIDIA’s data center business generated nearly $1 billion of revenue in its latest quarter. That’s not all AI-related – NVIDIA’s graphics cards are used to accelerate a wide variety of data center applications. But AI has been one of the driving forces behind the company’s growth.
Self-driving cars are another area of focus. NVIDIA develops platforms, including hardware and software, that can power driver-assistance features as well as full self-driving. The company’s DRIVE AGX Pegasus system includes two NVIDIA Xavier processors, two graphics processing units, and is capable of 320 trillion operations per second.
A self-driving car must process massive amounts of data from multiple sensors and cameras in real time, detect objects like pedestrians and other vehicles, and make complex decisions. They require a tremendous amount of computing power, and that’s exactly what NVIDIA’s platform delivers.
NVIDIA’s graphics cards could someday be supplanted by more specialized processors designed for AI, but for now the company is in an enviable position.
International Business Machines (NYSE:IBM) has been around for over a century. Today, the tech giant is an integrated provider of hardware, software, and services to large enterprise customers. Its mainframe computer systems are still ubiquitous in certain industries, and it regularly signs multi-year IT deals worth hundreds of millions of dollars each.
IBM’s strategy with AI is to apply the technology where it can augment human intelligence, increase efficiency, or lower costs. In the healthcare industry, IBM’s AI tech is being used to create individualized care plans, accelerate the process of bringing new drugs to market, and improve the quality of care. In the financial services industry via the company’s acquisition of Promontory Financial Group, IBM is using AI to help clients with the daunting task of regulatory compliance.
There are some applications that aren’t quite ready for primetime but show promise. For example, IBM is working with marine research organization ProMare on an “AI Captain” capable of allowing a ship to self-navigate across the Atlantic Ocean.
While the market for AI products and services is fragmented, IBM is leading the industry. The company generated over $2.5 billion of revenue from AI in 2018, according to IDC, giving it the largest market share in the industry.
IBM is a complicated company, and AI is far from its only growth opportunity. But if you’re looking to invest in a company that will benefit from the AI boom, IBM is a good choice.
Micron Technology (NASDAQ:MU) manufactures memory chips, including dynamic random-access memory (DRAM) and NAND flash memory found in solid-state drives. Most of what the company makes are commodity products, meaning that supply and demand dictate pricing. This leads to sometimes brutal cycles where an oversupply of chips push down prices.
In the long run, demand for memory chips will only grow, and that’s especially true in the AI industry. Self-driving cars are a good example. All the sensors and cameras produce a lot of data – Micron estimates it at around 1 GB per second. Back in 2018, the company forecast that a fully autonomous vehicle would require 74 GB of DRAM and 1 TB of NAND, and that there would be 26 million vehicles equipped with Level 3 autonomy by 2025. For comparison, a PC today may have 16 GB of RAM and 1 TB of NAND.
Outside of self-driving cars, data centers running AI workloads need plenty of memory as well. So do smartphones that may be doing AI work. Newer iPhones, for example, do all sorts of AI magic with the camera to produce improved images.
Investing in Micron will come with ups and downs due to the nature of its business. Even though AI will drive increased demand for memory chips in the long run, supply and demand reigns supreme in the short run. But if you have the stomach for a volatile stock, Micron isn’t a bad way to bet on AI.
IDC expects total spending on AI systems to reach $97.9 billion in 2023, up from $37.5 billion in 2019. For the five-year period ending in 2023, IDC sees a compound annual growth rate of 28.4%.
With the market already large and growing quickly, there’s room for plenty of companies to profit from AI. While picking stocks in a growth industry comes with a lot of uncertainty, NVIDIA, IBM, and Micron are AI stocks worth considering.
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