AI Research
1 Incredible Artificial Intelligence (AI) Chip Stock to Buy Before It Soars 85% (Hint: Not Nvidia), According to a Select Wall Street Analyst
This important component maker is poised to take share of a growing market.
Big tech companies are spending hundreds of billions of dollars on chips and equipment to outfit their growing data centers to continue pushing the potential of generative AI. Total infrastructure spending from the top 10 AI tech companies could climb from $435 billion last year to over $1 trillion by 2028, according to estimates from Dell’Oro. In other words, there’s still a lot of room for AI chip stocks to keep growing.
Perhaps the most important component of any data center focused on AI training and inference is the GPU cluster. Bigger clusters of more powerful GPUs are capable of training bigger models faster. Nvidia has established itself as the leading GPU maker, and its revenue and profits have skyrocketed as hyperscalers snatch up its chips as fast as it can produce them.
But GPU makers aren’t the only chipmakers benefiting from the rapid growth in AI spending. There are a lot of different components that go into data centers. As demand continues to grow over the next few years, one chipmaker’s stock could climb up to 85% from its price as of this writing through the next 12 months, according to one Wall Street analyst.
Here’s what investors need to know.
Image source: Getty Images.
Don’t forget about this component
One of the most expensive parts of building a GPU, which is more than just a piece of silicon these days, is the high-bandwidth memory, or HBM. The most advanced GPUs process tons of data every second. But in order to process that data, the unit must have a way to access the data quickly. Traditional memory components quickly became a bottleneck as the processing power of GPUs increased. As such, demand for HBM chips has exploded alongside the growing demand for the most advanced GPUs.
There are only a few chipmakers producing HBM chips. The leader in the market is SK Hynix, which established a strong relationship with Nvidia. But another memory chip maker, Micron Technology (MU 2.70%), is poised to take share from the market leader.
Micron was late to HBM, but now it’s ramping up development on its latest generation HBM3E 12H product, which it expects to be its biggest source of HBM shipments in the current quarter. It earned a big design win with Advanced Micro Devices‘ latest GPU, the MI355X. Analysts expect AMD’s latest chip to compete for more share of data center spending against Nvidia, which bodes well for Micron as well. Overall, Micron expects its share of the HBM market to grow to the same level as its total DRAM (general memory chips) market share, about 25%, at some point in the second half of this year. That’s pretty rapid progress after starting from a near standstill a few years ago.
Importantly, Micron’s next-generation HBM4 progress is going well, too, with performance 60% higher than its HBM3E chips with 20% less power consumption. Management says it’s delivered samples to customers, and it expects to ramp up volume production next year.
The early results are evident in Micron’s financials. HBM revenue grew 50% sequentially in its most recent quarter. As a result, total revenue from DRAM sales (of which HBM is a part) climbed 51% year over year. Management expects the ramp in HBM3E to push its gross margin higher this quarter, reaching 42%, up from 39% in its most recent quarter.
While HBM is the driving force behind Micron’s recent results, it’s not the only factor pushing demand for Micron’s chips. Device makers are also in need of more traditional memory chips from Micron as it’s also an important component for on-device AI capabilities. Everything from PCs and smartphones to automobiles with advanced computing capabilities (like self-driving) need more powerful memory chips. On-device AI capabilities may drive significant smartphone upgrades over the next few years, representing another potential catalyst for Micron.
The 80% upside in the stock
Micron is making strong progress in the HBM market, and that led Rosenblatt Securities to slap a $200 price target on the stock following its third-quarter earnings report in June. The key factor behind the analyst’s Street-high price target, which is an 80% jump from today’s price, is the capacity constraints on the market.
SK Hynix notably said it had already sold out its entire capacity for 2025 by the end of the first quarter and it expected to finalize its 2026 volume within the first half of the year.
“With DRAM wafer capacity expansion over 18 months away, we see this cycle driving Micron’s income model to all-time highs,” Rosenblatt’s Kevin Cassidy wrote in an investor note. He find’s Micron’s current valuation, less than 14 times forward earnings, as extremely attractive, especially given the strength of its balance sheet and potential earnings leverage.
Before investors run out and buy the stock, though, there’s an important risk to consider with Micron. It’s an extremely cyclical stock.
Since it manufactures its chips itself, it has significant capital expenditures for equipment and capacity. A downturn in demand would not only hurt volume but pricing as well, because most of its products aren’t very differentiated from SK Hynix or other competitors. That would weigh heavily on earnings. Micron saw a significant shock to its earnings in 2023, as inventory levels rose and demand from China vanished.
That said, the strong expected growth in AI spending could provide a huge boost to Micron’s revenue and profit margins over the next few years, as long as it’s able to maintain leading-edge technology with HBM. That could mean an extended earnings cycle with very strong earnings growth for the next few years. At some point, however, Micron will see a big drop in demand and earnings will severely suffer. But the long-term trends favor growing demand for memory both in data centers and consumer devices and automobiles.
As such, Micron is a great value at today’s price, especially for investors looking for a way to invest in the growing spending of the hyperscalers without paying up for expensive GPU chipmakers like Nvidia and AMD.
The National Science Foundation plans to award up to $35 million to establish an operations center for its National AI Research Resource, signaling a step toward the pilot becoming a more permanent program.
Despite bipartisan support for the NAIRR, Congress has yet to authorize a full-scale version of the resource designed to democratize access to tools needed for AI research. The newly announced solicitation indicates the project is taking steps to scale the project absent additional support.
“The NAIRR Operating Center solicitation marks a key step in the transition from the NAIRR Pilot to building a sustainable and scalable NAIRR program,” Katie Antypas, who leads NSF’s Office of Advanced Cyberinfrastructure, said in a statement included in the announcement.
She added that NSF looks forward to collaborating with partners in the private sector and other agencies, “whose contributions have been critical in demonstrating the innovation and scientific impact that comes when critical AI resources are made accessible to research and education communities across the country.”
The NAIRR began as a pilot in January 2024 as a resource for researchers to access computational data, AI models, software, and other tools that are needed for AI research. Since then, the public-private partnership pilot has supported over 490 projects in 49 states and Washington, per its website, and is supported by contributions from 14 federal agencies and 28 private sector partners.
As the pilot has moved forward, lawmakers have attempted to advance bipartisan legislation that would codify the NAIRR, but those bills have not passed. Previous statements from science and tech officials during the Biden administration made the case that formalization would be important as establishing NAIRR fully was expected to take a significant amount of funding.
In response to a FedScoop question about funding for the center, an NSF spokesperson said it’s covered by the agency’s normal appropriations.
NAIRR has remained a priority even as the Trump administration has sought to make changes to NSF awards, canceling hundreds of grants that were related to things like diversity, equity and inclusion (DEI) and environmental justice. President Donald Trump’s AI Action Plan, for example, included a recommendation for the NAIRR to “build the foundations for a lean and sustainable NAIRR operations capability.”
According to the solicitation, NSF will make an award of a maximum of $35 million for a period of up to five years for the operations center project. That award will be made to a single organization. That awardee would ultimately be responsible for establishing a “community-based organization,” including tasks such as establishing the operation framework, working with stakeholders, and coordinating with the current pilot project functions.
The awardee would also be eligible to expand their responsibilities and duties at a later date, depending on factors such as NAIRR’s priorities, the awardee’s performance and funding.
AI Research
Top AI Code Generation Tools of 2025 Revealed in Info-Tech Research Group’s Emotional Footprint Report
The recently published 2025 AI Code Generation Emotional Footprint report from Info-Tech Research Group highlights the top AI code generation solutions that help organizations streamline development and support innovation. The report’s insights are based on feedback from users on the global IT research and advisory firm’s SoftwareReviews platform.
TORONTO, Sept. 3, 2025 /PRNewswire/ – Info-Tech Research Group has published its 2025 AI Code Generation Emotional Footprint report, identifying the top-performing solutions in the market. Based on data from SoftwareReviews, a division of the global IT research and advisory firm, the newly published report highlights the five champions in AI-powered code generation tools.
Info-Tech Research Group’s 2025 AI Code Generation Emotional Footprint report identifies leading solutions that enable organizations to accelerate development and drive innovation. (CNW Group/Info-Tech Research Group)
AI code generation tools make coding easier by taking care of repetitive tasks. Instead of starting from scratch, developers get ready-made snippets, smoother workflows, and support built right into their IDEs and version control systems. With machine learning and natural language processing behind them, these tools reduce mistakes, speed up projects, and give developers more room to focus on creative problem solving and innovation.
Info-Tech’s Emotional Footprint measures high-level user sentiment. It aggregates emotional response ratings across 25 proactive questions, creating a powerful indicator of overall user feeling toward the vendor and product. The result is the Net Emotional Footprint, or NEF, a composite score that reflects the overall emotional tone of user feedback.
Data from 1,084 end-user reviews on Info-Tech’s SoftwareReviews platform was used to identify the top AI code generation tools for the 2025 Emotional Footprint report. The insights support organizations looking to streamline development, improve code quality, and scale their software delivery capabilities to drive innovation and business growth.
The 2025 AI Code Generation Tools – Champions are as follows:
- Visual Studio IntelliCode, +96 NEF, ranked high for delivering more than promised.
- ChatGPT 5, +94 NEF, ranked high for its effectiveness.
- GitHub Copilot, +94 NEF, ranked high for its transparency.
- Replit AI, +96 NEF, ranked high for its reliability.
- Amazon Q Developer, +94 NEF, ranked high for helping save time.
Analyst Insight:
“Organizations that adopt AI code generation tools gain a significant advantage in software delivery and innovation,” says Thomas Randall, a research director at Info-Tech Research Group. “These tools help developers focus on complex, high-value work, improve code quality, and reduce errors. Teams that delay adoption risk slower projects, lower-quality software, and missed opportunities to innovate and stay competitive.”
User assessments of software categories on SoftwareReviews provide an accurate and detailed view of the constantly changing market. Info-Tech’s reports are informed by the data from users and IT professionals who have intimate experience with the software throughout the procurement, implementation, and maintenance processes.
Read the full report: Best AI Code Generation Tools 2025
For more information about Info-Tech’s SoftwareReviews, the Data Quadrant, or the Emotional Footprint, or to access resources to support the software selection process, visit softwarereviews.com.
About Info-Tech Research Group
Info-Tech Research Group is one of the world’s leading research and advisory firms, proudly serving over 30,000 IT and HR professionals. The company produces unbiased, highly relevant research and provides advisory services to help leaders make strategic, timely, and well-informed decisions. For nearly 30 years, Info-Tech has partnered closely with teams to provide them with everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.
To learn more about Info-Tech’s divisions, visit McLean & Company for HR research and advisory services and SoftwareReviews for software buying insights.
Media professionals can register for unrestricted access to research across IT, HR, and software, and hundreds of industry analysts through the firm’s Media Insiders program. To gain access, contact [email protected].
For information about Info-Tech Research Group or to access the latest research, visit infotech.com and connect via LinkedIn and X.
About SoftwareReviews
SoftwareReviews is a division of Info-Tech Research Group, a world-class technology research and advisory firm. SoftwareReviews empowers organizations with the best data, insights, and advice to improve the software buying and selling experience.
For buyers, SoftwareReviews’ proven software selection methodologies, customer insights, and technology advisors help maximize success with technology decisions. For providers, the firm helps build more effective marketing, product, and sales processes with expert analysts, how-to research, customer-centric marketing content, and comprehensive analysis of the buyer landscape.
SOURCE Info-Tech Research Group
Vanderbilt University has established the Enterprise AI and Computing Innovation Studio, a groundbreaking collaboration between VUIT, the Amplify Generative AI Innovation Center and the Data Science Institute. This studio aims to prototype and pilot artificial intelligence–driven innovations that enhance how we learn, teach, work and connect.
Each of the partner areas has a strong record of addressing challenges and solving problems independently. By uniting this expertise, the studio can accelerate innovation and expand the capacity of the university to harness emerging technologies to support its mission.
Through the studio, students will have immersive experiences collaborating on AI-focused projects. Staff will deepen their skills through engagement with AI research. In addition, the studio underscores Vanderbilt’s position as a destination for global talent in artificial intelligence and related fields.
Members of the university community who have specific challenges or opportunities that AI may solve or address can submit a consultation request.
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