Q2 AI Watch: 3 Stocks to Keep Your Eyes On Now
While investors’ eyes remain glued on the big names in artificial intelligence, endless other companies are integrating AI technology more quietly. Not every company actively chooses to rebrand as an AI specialist, even while benefiting from its popularity. Yet, savvy investors who know some of the best AI stocks to watch out for may not be the obvious early adopters.
As the technology matures, expanding applications allow more industries to reap the benefits of lower costs and improved efficiency through the machine learning algorithms of AI. These applications are likely to drive increases in stock value for said companies.
From transistor manufacturing to medical imaging and beyond, the streamlining effect of AI has cemented its use. In the case of these three AI stocks, the companies in question utilize the technology in novel ways to improve within their specific niches. As such, the potential return on investment could be greater than the general AI trend.
ASML Holdings (ASML)
The world’s leading manufacturer of chipmaking technology, ASML Holdings (NYSE:ASML), commands a critical component of the global electronics industry. The Dutch technology giant dominates the market for photolithography machines, the designs of which it has extensively improved over time. These fabrication devices enable the etching of transistors onto circuit boards at the nanometer scale.
Thanks to its advanced products, ASML provides the highest quality chipmakers the tools necessary for building incredibly powerful computers and processors. But ASML has an ace up its sleeve for the AI industry. As more computing companies rush to test the limits of AI, ASML will be selling the machines that make its infrastructure possible.
With the introduction of its new high-NA extreme ultraviolet system, ASML’s innovation will power the computational needs of the coming AI generations. This machine can etch transistor lines on semiconductors 8 nanometers thick, 1.7 times smaller than any available alternative. This means the most powerful AI chips of the future will likely be built using ASML machinery, solidifying it as one of the AI stocks to watch.
Nano-X Imaging (NNOX)
While the first line of defense against disease may be prevention, the second is detection. This essential component of healthcare has become Nano-X Imaging’s (NASDAQ:NNOX) company mission but with an AI twist. To achieve this lofty goal, the company has taken the AI paradigm of medical data analysis to the next level.
Currently, the company markets two direct applications of analytical AI to the diagnostic process in medicine. One is called HealthCCSng which focuses on coronary artery disease and the other is HealthOST for osteoporosis. Both are AI applications that have been FDA-cleared and use pattern recognition models to help identify patient conditions. Technologies such as these have significant potential to reduce the risk of misdiagnosis and improve treatment efficacy.
This could ultimately have a cascading effect on the way many hospitals approach diagnosing common conditions. Should this occur, NNOX’s products could become a staple of the healthcare industry and how the modern physician practices medicine.
Micron Technology (MU)
Perhaps the single greatest limiting factor to the current AI industry is computer memory storage. While other companies rush to produce the fastest computers, Micron Technology (NASDAQ:MU) specializes in helping AI remember its skills. Presently, many native AI applications voraciously consume random access memory, limiting the devices and environments they can operate within.
However, MU’s DRAM and LPDDR product lines aim to solve this for the computing world. The former of the two is a scalable memory chip for data center applications. Due to its modular design, the DRAM series easily integrates into existing databases to expand as memory needs increase.
On the other hand, the LPDDR, or low-power double-data-rate memory chip, leverages its design to offer high-speed data access. It applies to mobile device processing units without drawing prohibitive amounts of power from the circuit. While relatively nascent in the sales process, both designs will likely see increasing demand, growing MU’s potential value.
On the date of publication, Viktor Zarev did not have (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.
