When discussing the current top technology stocks, artificial intelligence and machine learning often get used interchangeably. They are closely related, but should be considered as two distinct technologies. Machine learning is primarily concerned with the algorithms and statistical model development required for AI to function. In other words, machine learning is necessary for artificial intelligence.
Stocks related to both fields have exploded in 2023 producing very strong returns. 2024 looks to possess similarly strong potential. Thus, investors are considering which machine learning and AI shares they ought to be picking up as December winds down. Investors should stick with what has worked in 2023 while also directing capital toward some more speculative plays in the sector. Here are three of the top machine learning stocks to start off 2024 on a good foot.
Amazon (AMZN)
Amazon (NASDAQ:AMZN) is the leading cloud provider. That makes the company and its stock almost impossible to ignore in relation to machine learning.
Amazon has worked diligently to build out a platform that attracts businesses for the purposes of machine learning. The company has created a workflow pipeline to onboard businesses of all sizes, leveraging the AWS cloud in order to build AI models.
As I mentioned, Amazon has the largest cloud platform with more than 100,000 partners utilizing AWS. It is therefore reasonable to assume that the data contained within Amazon’s cloud contains vast, vast insights. Machine learning can theoretically be applied in ways that will allow its partners to mine that data for the purposes of AI.
That’s how I look at Amazon in relation to machine learning as 2023 comes to an end. Further, simply consider the stock for no other reason than the fact that this is expected to be a strong holiday shopping season and Amazon is the e-commerce king.
Nvidia (NVDA)
Let’s start with what Nvidia (NASDAQ:NVDA) actually does in the realm of machine learning. Investors are well aware of how important Nvidia is to the continued growth of AI. That doesn’t look to be slowing down as we prepare for 2024. However, that doesn’t mean they necessarily understand what the company is doing in regard to machine learning.
Nvidia’s machine learning ecosystem is defined by RAPIDS and CUDA. They are respectively a series of open source api and development architecture that allow businesses to build AI models. Nvidia utilizes those assets across its machine learning platform for businesses of all sizes. As the company notes, whether a business is developing an AI system from scratch or updating a current platform, it’s machine learning is applicable.
Nvidia is also noted to have the best talent at its firm. So, whether it is leveraging that talent to create next generation chips, or to improve its machine learning algorithms, the company has an edge.
Advanced Micro Devices (AMD)
Advanced Micro Devices (NASDAQ:AMD) is engaged in a pitched battle against Nvidia in relation to AI and machine learning. Those who follow the twists and turns of the saga will know that it’s very difficult to get an accurate reading on the reality of the situation.
It’s very easy to find opinions stating that AMD has no chance at this point. The notion is that Nvidia is simply too strong and will only get stronger. when you realize how strong demand has been for its H100 chips, it becomes easy to fall in line with that thinking.
However, the truth is more nuanced and only time will tell which firm, if either, will dominate. AMD recently unveiled its MI300 chips. Leading firms including Meta (NASDAQ:META) and Microsoft (NASDAQ:MSFT), which gobbled up large percentages of Nvidia’s H100 chips, have now said they will buy AMD’s new offering. The battle is only beginning between AMD and Nvidia, and AMD has a strong, strong chance of succeeding.
On the date of publication, Alex Sirois 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.
