To The Moon

Honestly, not an easy decision to decide whether to be a short term or long-term holder for Nvidia. Of course the company continues to grow and make super profit from the AI frenzy. However, not to forget that many strong competitors are catching up and maybe one day, they will catch up Nvidia and grab some of their market shares. 

For example, Meta Platforms $Meta Platforms, Inc.(META)$ , the parent company of Facebook, will use new self-developed chips to drive artificial intelligence (AI) services, aiming to reduce its dependence on semiconductors from external companies such as NVIDIA.

Meta released on Wednesday (10th March) the latest version of the "Meta Training and Inference Accelerator" (MTIA) chip, which is used to help rank and recommend content on Facebook and Instagram. The first version of MTIA was launched last year.

Meta's shift to AI services requires more powerful computer computing power. Last year the social media giant released its own AI model to compete with OpenAI's ChatGPT. At the same time, it has also added new generative AI features to its social applications, including customized stickers and chatbot characters with celebrity faces.

More and more technology giants are developing self-developed chips. In addition to Meta, Amazon cloud business AWS, $Microsoft(MSFT)$  and $Alphabet(GOOG)$   are all trying to get rid of this very expensive dependence. However, efforts do not come overnight. So far, they have not been able to reduce the industry's strong demand for NVIDIA AI accelerators.

American chip giant $Intel(INTC)$   will join hands with South Korean network giant Naver to open an artificial intelligence (AI) semiconductor research institute as part of efforts to strengthen its efforts to counter Nvidia's dominance of the AI chip market.

Intel also released its latest AI accelerator chip Gaudi3 at this event, which significantly reduces the training time of AI models. It claims that the training speed is twice that of NVIDIA H100. It also said that the test results of Meta's LaMa2 model showed that the inference performance is 50 times higher than that of H100. %, and the energy saving efficiency is also increased by 40%.

Not to deny, the AI craze has helped Nvidia become the third largest technology company in the world by market value, ranking behind Microsoft and Apple. NVIDIA's data center sales in fiscal year 2024 will jump from US$15 billion in 2023 to US$47.5 billion. However, we can't deny that many competitors are trying hard to catch up NVIDIA and NVIDIA might lost some gap advantages to them over the time.

How do you think? 

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