AI bubble? Demand exceeds production capacity

"The AI bubble"? 💭

Or perhaps all the short sellers are living in a bubble? ❓

Note how enormous the demand for AI is... 🚨

TSMC is building 20 new factories, yet it still cannot meet the immense wave of demand... 💵

$TSM 🏭

The demand for AI computing infrastructure continues to grow at a pace that surprises even the world's largest chip manufacturers, and the data coming from TSMC illustrates the depth of the production capacity shortage... 🔎

Dr. Ho Yung-ching, a senior executive at TSMC:

"This rate of demand increase is the largest of all demands ever in 30 years"

TSMC is in the midst of one of the largest production expansions in its history, with about 13 factories being built in Taiwan and another 5 to 6 factories outside Taiwan, totaling about 20 factories. 🏭

But here's the interesting part: even if TSMC doubles its production capacity, the company estimates that demand from AI infrastructure will still be greater. 💵

The problem is no longer just how many chips TSMC can produce, but how quickly the entire supply chain can expand. 💡

At the end of last year, TSMC estimated that new demand would grow by approximately 2x. 📈

In the first quarter, the forecast already doubled from the previous estimate. 📈

In July, the forecast jumped again, and again doubled. 📈

This is a dramatic change in a very short period, and according to Dr. Ho Yung-ching, such a rate of change in demand is something he has not seen during his approximately 30 years in the industry. 🔎

And this is precisely what makes the current AI cycle so exceptional. 💡

Another important point to understand here is that the problem is not just manufacturing plants...

To increase chip production, much more than a new factory is needed:

It requires:

🏭 Advanced manufacturing equipment. 🏭 Clean rooms. 🏭 Special gases. 🏭 Enormous power supply. 🏭 Cooling systems and infrastructure. 🏭 Advanced packaging facilities. 🏭 Engineering and technical personnel. 🏭 Workers to build the factories themselves.

And here another bottleneck is created. 💡

While TSMC is building factories in several regions worldwide simultaneously, this creates a shortage not only of chip manufacturing equipment but also of the personnel and equipment needed to build the factories. 🏭

And ultimately, bottlenecks extend throughout the entire AI chain,

As AI computing becomes more complex, the bottlenecks also change. 💡

The shortage is no longer limited to wafer production but extends to advanced packaging, system-level chip integration, power supply, and data center infrastructure. 🔎

Therefore, the competitive advantage is gradually shifting from the ability to produce a single chip to the ability to design and produce an entire computing system on an enormous scale. 💡

And the most interesting part: AI is beginning to solve the shortage it itself created:

TSMC uses AI tools within its production processes to improve efficiency, reduce reliance on human labor, and increase wafer output from the same resources. 📱

In other words, an interesting cycle is created here:

Artificial intelligence increases demand for chips -> Demand necessitates factory expansion -> Factory expansion creates shortages of equipment, labor, and infrastructure -> TSMC uses AI to increase productivity and produce more with the same resources. 🏭

And ultimately, the story is not just TSMC... 💡

The continued massive investments in AI infrastructure create demand across an entire chain:

🖥 $NVDA - Nvidia - AI accelerators and computing systems. 🏭 $TSM - Advanced chip manufacturing.

🕹 $MU - Memory. ⌨️ $SNDK - Storage. ▫️ $LITE - Optical components. 💭 $NBIS - Cloud infrastructure. ⚡️ $BE - Energy solutions for data centers.

🔄 $SKHY - Chip manufacturing.

The broader implication is that AI investments are still encountering a physical limitation: there simply isn't enough manufacturing, packaging, power, equipment, and personnel capacity to keep up with the pace of demand. 💵

And this may be one of the most important characteristics of the current AI cycle: demand is not just large, it is growing faster than the chip industry's ability to expand. 💡