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Are many people surprised that Meta was willing to spend tens of billions of dollars on AI but suddenly stopped the AI chip project with Samsung right in the middle of the fiercest race in technology history?
A new report from Korean media is attracting the attention of the technology world as Meta is said to have paused its cooperation in developing custom AI chips with Samsung. The information appears in the context that large technology corporations are racing to reduce dependence on NVIDIA and build their own AI infrastructure.
If this information is accurate, this could be a sign that AI chip development is much more difficult than what the market had expected.
The current picture of the AI chip race
Direction Company
Meta Develops MTIA internal AI chip
NVIDIA GPU AI dominates the market
AMD GPU Instinct competes AI
New generation Google TPU
Amazon Chip Trainium and Inferentia
Microsoft Maia AI Accelerator
Samsung Manufactures AI chips under contract
Meta has for many years relied heavily on NVIDIA GPUs to train giant AI models.
However, AI investment costs are increasing at a rapid pace.
Meta's AI investment scale
ββββββββββββββββββββββββ
β AI INVESTMENT 2026 β
ββββββββββββββββββββββββ€
β Annual estimates β
β 60 - 72 BILLION VND USD β
ββββββββββββββββββββββββ
This level of spending is among the largest in the technology world today.
ChiTherefore, Meta wants to design its own chips to reduce long-term operating costs and optimize the performance of its AI systems.
Why did Meta choose Samsung?
Samsung is one of the few businesses in the world that possesses advanced semiconductor manufacturing capacity.
The Korean corporation is trying to compete with TSMC in the field of AI chip processing.
If the cooperation is successful, Samsung can win a huge strategic customer and create leverage for the foundry segment, which is facing many difficulties.
However, according to new reports, the project has now been paused.
The specific cause has not been announced.
Some experts say it may be related
β’ Chip performance is not satisfactory
β’ Production costs are too high
β’ Change Meta's AI strategy
β’ Difficulties in the production process
β’ Market demands change rapidly
Compare the positions of AI chip companies
Enterprise Main advantages
NVIDIA The strongest CUDA ecosystem
AMD Competitive price
Google Deep integration with AI Cloud
Amazon Optimizes AWS
Meta Autonomous AI Infrastructure
Samsung Semiconductor manufacturing capacity
It is worth noting that although Meta stopped the project with Samsung, this does not mean that Meta has given up its AI chip ambitions.
In contrast, Mark Zuckerberg's corporation is still investing heavily in the MTIA chip line to serve new generation AI models.
What will happen next?
If Meta continues to rely on NVIDIA, the cost of building AI data centers could continue to increase sharply.
If Meta finds another manufacturing partner like TSMC, the competition in the AI ββsemiconductor market will be even hotter.
If SamSupplement cannot retain large AI customers, its position in the foundry field may come under more pressure from TSMC.
Impact on the technology industry
Objects of Influence
Meta Slow chip autonomy plan
Samsung Lost a big revenue opportunity
NVIDIA Continues to Benefit
TSMC May attract more orders
AI market Competition is more fierce
More broadly, this is not just a story between Meta and Samsung.
This is a sign that creating an AI chip capable of competing with NVIDIA is currently an extremely difficult task, even for corporations with hundreds of billions of dollars in resources.
The AI ββwar is no longer just a war on software or language models.
It is a war on semiconductors, computing infrastructure and the global supply chain.
And any delay in the field of AI chips could change the world's technology landscape for years to come.
#Meta #Samsung #AIChip #MetaAI #SamsungFoundry #NVIDIA #AMD #GoogleAI #TriTueNhanTao #CongNghe #TinCongNghe #ChipBanDan #DataCenter #AI2026 #MarkZuckerberg
