Thu Sep 11 14:00:00 UTC 2025: Here’s a summary and rewritten news article based on the provided text:
**Summary:**
Micron Technology shares rallied following a positive analyst note from Citigroup and bullish forecasts from Oracle regarding future AI infrastructure demand. Citigroup believes memory supply will be constrained through 2026, driven by both DRAM and NAND flash demand for AI inferencing and edge computing. Oracle Chairman Larry Ellison highlighted the significant opportunity in AI inferencing, predicting massive demand and a corresponding boom in cloud infrastructure revenue, which in turn boosted AI-related stock prices.
**News Article:**
**Micron Soars on AI Inferencing Hype and Analyst Optimism**
**NEW YORK, NY** – Shares of Micron Technology (NASDAQ: MU) surged Wednesday, initially climbing over 5%, before settling with a 3.5% gain, fueled by a confluence of positive market signals. The rally followed a bullish analyst note from Citigroup, reaffirming a “buy” rating and predicting a prolonged period of memory undersupply, coupled with Oracle’s (NYSE: ORCL) surprisingly strong long-term guidance emphasizing AI infrastructure demand.
Citigroup analysts pointed to a shift in AI development from training models to AI inferencing and edge AI devices as a key driver of future memory demand. They anticipate DRAM demand will outpace supply by 1.8 percentage points and, surprisingly, even NAND flash, recently plagued by oversupply, will see demand exceed supply by 4 percentage points.
Oracle Chairman Larry Ellison further stoked the market’s enthusiasm during the company’s earnings call. Ellison highlighted the massive potential of AI inferencing and Oracle’s aggressive pursuit of this market. Oracle’s backlog of $455 Billion, a 359% increase, underscores the anticipated demand. The company forecasts its cloud infrastructure revenue to grow from $18 billion this year to a staggering $144 billion by 2030.
The connection between the analyst note and Oracle’s bullish outlook is clear: AI inferencing, the application of trained AI models, requires significant memory capacity, driving demand for both high-bandwidth memory (HBM) used in training and general-purpose DRAM and NAND in edge devices. With Micron’s technology now considered on par with or better than its competitors, the company is well-positioned to capitalize on the anticipated AI-driven memory boom. While the memory business has historically been cyclical, persistent AI demand could provide stability and higher pricing for the foreseeable future.
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