How Long Can the Memory Storage Boom Last? A Backpack Crypto Analysis

What the data says

The supplied event argues that memory is no longer behaving like a normal commodity segment. It cites WSTS-based semiconductor shipment data showing memory growth becoming nearly vertical from around 2024, with the memory category described as breaking away from the long-term pattern seen across micro devices, logic, analog, and memory.

The brief states that MOS memory monthly shipments were about 5.6 billion dollars in 2016, fell near 5.8 billion dollars around the early 2023 downturn, and reached 63.3 billion dollars by May 2026. It also says recent year-over-year memory growth reached 285%, far above the earlier memory bubble peak of around 60% and above the growth rates cited for logic, micro, and analog categories.

TrendForce-based figures in the brief add another layer. They describe DRAM and NAND markets recovering from early 2023 lows, then expanding sharply into a forecasted second quarter of 2026. The brief attributes much of that expansion to price increases rather than a simple surge in unit shipments.

Why this boom is different

The direct driver is pricing. The brief says DRAM spot prices for DDR5 16Gb 2Gx8 rose from 4.70 dollars in early 2025 to 46.00 dollars recently, while NAND 1Tb TLC wafer prices rose from 2.40 dollars to 25.00 dollars. In both cases, the described increase is about tenfold.

That matters because revenue can multiply even if physical output does not multiply at the same pace. When the unit price rises by roughly ten times, the market value can expand sharply without needing ten times as many chips. This is why the supplied brief treats the current memory boom as an abnormal price cycle rather than a standard growth story.

For memory manufacturers, the brief presents this as an unusually favorable environment. Higher prices can lift margins quickly, especially when the market is tight. But that same price sensitivity is also the weakness of the cycle: if prices normalize, revenue growth can fall faster than end-demand headlines imply.

The AI data center link

The supplied event identifies hyperscale AI infrastructure spending as the core demand source. It says Amazon, Google, Microsoft, and Meta had combined capital expenditure of 21 billion dollars in 2015, with the figure expected to reach 355 billion dollars in 2025 and 755 billion dollars in 2026.

According to the brief, AI data centers are absorbing GPUs, HBM, high-performance DRAM, and SSD capacity. Memory manufacturers then prioritize higher-margin HBM and data-center-grade products, which reduces available capacity for consumer electronics such as PCs, smartphones, and game consoles.

This creates a two-sided squeeze. AI infrastructure pulls supply toward high-value demand, while consumer device makers face tighter availability and higher procurement costs. The brief says PC and smartphone makers are already signaling difficulty obtaining memory and passing higher costs into product prices.

How this connects to crypto and Backpack

The connection to crypto is indirect. The supplied brief is about semiconductor memory, AI infrastructure, and pricing pressure. It does not provide Backpack-specific operating data, exchange volume, user growth, custody details, token economics, rewards, registration status, or ranking claims. Any Backpack analysis therefore has to stay at the level of market context and user decision checks.

For crypto traders, the useful takeaway is that AI infrastructure can shape narratives around compute, data centers, storage, and semiconductor-linked assets. But a macro narrative does not validate any exchange, trading venue, token, or referral offer by itself. Market infrastructure stories can raise attention without reducing execution, custody, liquidity, or counterparty risk.

If a reader is evaluating Backpack in this context, the practical move is not to assume that AI-driven memory demand creates a direct benefit. The better approach is to verify the exchange experience, supported assets, fees, withdrawal process, risk controls, and account requirements directly before using any referral link or code. The supplied CTA is a conversion path, not evidence of investment merit.

Evidence limits

This article uses only the supplied event and brief. It does not verify the original WSTS, TrendForce, company filing, or source-page data independently. It also does not add live market prices, current Backpack product details, or regulatory status beyond what appears in the provided material.

Several figures in the brief are forecasts or source-derived estimates, including the 2026 hyperscaler capital expenditure and 2026 semiconductor market outlook. Forecasts can change if AI spending plans, memory supply, consumer demand, or pricing conditions change.

The brief strongly supports the conclusion that the current memory cycle is abnormal and price-led. It does not prove how long the cycle will last, whether the cited forecast path will be met, or which crypto platforms, if any, will benefit from the trend.

Practical checks before acting

First, separate semiconductor evidence from crypto venue decisions. The memory data can explain why AI infrastructure is a major market theme, but it does not answer whether a specific exchange account, referral code, or trading strategy is suitable.

Second, check supply-side signals. A memory boom based heavily on price can reverse if manufacturers add capacity, redirect capacity away from AI products, or if downstream buyers delay purchases. The brief itself makes clear that price is the key mechanism.

Third, check platform basics before using Backpack or any other exchange. Confirm account access rules, fees, supported assets, withdrawal limits, security settings, custody model, and any jurisdiction-specific restrictions from the platform’s own current materials. Do not rely on a macro AI storage article for those facts.

For readers who have already decided to inspect Backpack, the supplied referral path is BACKPACK official destination with code 7nfg8123. Treat it as a signup route to review, not as a recommendation, guarantee, or financial instruction.

Risk disclosure

This is not financial advice. Semiconductor market growth, AI infrastructure spending, and crypto market narratives can move in different directions. A strong memory cycle does not guarantee crypto returns, exchange adoption, token performance, or trading profits.

The biggest risks in the supplied thesis are demand concentration, price normalization, and forecast uncertainty. If hyperscale AI spending slows, if memory supply catches up, or if consumer and enterprise buyers reject higher prices, the current expansion could lose momentum.

Crypto users face additional risks that are separate from the memory cycle: market volatility, platform failure, withdrawal delays, security mistakes, liquidity gaps, and regulatory changes. Those risks should be checked directly before depositing funds or trading.