From Concept to Reality, investments in Physical AI are accelerating. After attending the GTC conference, Morgan Stanley reassessed the investment prospects in the fields of Robotics and Physical AI.$NVIDIA (NVDA.US)$In a report on March 24, Morgan Stanley indicated that after this year's GTC, Analysts found that Physical AI would have a significant revenue impact on the Semiconductors Industry earlier than expected, due to two key factors changing this determination:

Investment is accelerating: Companies have started to allocate funds to develop models in the physical domain.

• Physical AI is becoming a core feature of the next generation of AI models: The next generation of AGI models being developed will integrate physical simulation capabilities.

• Previously, Morgan Stanley tended to believe that Physical AI was still quite far from true commercialization, affecting Stocks valuation multiples more than directly contributing to revenue. However, now Morgan Stanley has observed a significant increase in clients' interest in Robotics and Physical AI compared to a year ago.

Current Physical AI is similar to Generative AI four to five years ago, or Autonomous Driving seven to eight years ago. In other words, companies are now starting to spend money on developing models in the physical field.

The key conditions for the development of physical AI are now in place, and semiconductor companies will benefit.

Morgan Stanley noted that companies are actively investing in the development of physical AI models.

These models require multimodal AI modeling capabilities that can handle visual, audio, and language data, and possess reasoning abilities. These capabilities have only started to mature in the past few months. Companies also emphasize the significant differences in building physical AI models compared to investing in language or visual AI domains. They are actively investing in the collection of real-world data and creating simulated data, such as that from NVIDIA's Isaac project.

As large model developers seek to further differentiate their models in the future, better integration of physical AI data has become a focus.

Just like the progress made by large language models (LLMs) in handling novel data in the past 12 months, the next generation of Artificial General Intelligence (AGI) models will also incorporate physical simulations into their intelligence systems. Robotics startups are also leveraging large language models as a starting point for developing physical intelligence.

So who benefits, and to what extent? Morgan Stanley pointed out that,

In the field of physical AI, startups are receiving funding in the scale of billions of dollars. Hardware will be the primary beneficiary of early investments, but considering that the market size of datacenter AI semiconductor processors will exceed $200 billion this year, smaller projects may not have a significant impact on the market. However, if a sustained increase in cluster scale can be seen, the situation may change.

Among them, NVIDIA is the core beneficiary, as most developers use NVIDIA for data simulation, training, and device building. Ecosystem participants, such as $Advanced Micro Devices (AMD.US)$ 、 $Broadcom (AVGO.US)$ and $Marvell Technology (MRVL.US)$ Other companies will also benefit.

However, Morgan Stanley also stated that it is cautious about the idea of 'robots entering every household' in the short term, given that the substantial investments in Datacenter for the autonomous driving sector over the past few years have not yet fully translated into revenue. Morgan Stanley believes it is necessary to closely monitor the development of physical AI.

Editor/Rocky