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Without doubts, AI's impact remains immense. Yole Developpement analysts estimate the 2024 total market for AI hardware computing for consumer applications to reach $15.6 billion. This market can be shared between two market segments: the stand-alone chip at $3.8 billion and the embedded one, especially supported by the smartphone, up to $11.8 billion.
The market research and strategy consulting company has released its AI report, Artificial Intelligence Computing for Consumer. The aim of this analysis is to reveal an AI scenario within dynamics of the consumer industry. This report evaluates the AI impact on the semiconductor industry and proposes an in-depth understanding of the AI ecosystem and related players. Yole’s analysts have anticipated for a few years now the move from the cloud to the edge. Today, transition is happening faster than ever, especially within the imaging market segment. Facing this disruption, AI algorithms require powerful hardware.
With the end of Moore’s law and the need for power demanded by AI algorithms, it was necessary to create a new type of dedicated architecture. This unit has different names: deep learning accelerator, neural engine, neural processing unit, AI-processing unit. The goal is the same: To allow, without the need of a power-hungry GPU, to parallelize numerous calculations in deep learning algorithms, and thus bring intelligence directly to the device level, independent of the cloud. Yole’s report distinguishes two types of technologies: either the AI is entirely dedicated to the analysis due to a stand-alone chip, or the unit dedicated to this task is embedded in a SoC whose objective is not centered on the analysis.
To name a few examples, on the one hand, for the stand-alone chip, Intel Movidius is a perfect example. On the other hand, an “application processor”, like Qualcomm’s Snapdragon series, which is the central chip of smartphones containing a neural engine, are representative of the embedded category.
Even if the IP players propose solutions for the whole ecosystem, it is obvious that there is a strong stake to bring the calculation close to the sensor or centralize it in a multifunction chip. In the first case, Yole finds the historical actors as well as the suppliers of sensors who want to add value to their product; for example, ON Semiconductor, Ambarella, TI, Sony, Knowles, ams. On the other, more and more OEMs also wants to capture this value by designating their own chip. Apple, Samsung, Huawei (with HI Silicon) and more famous players such as Intel or Qualcomm are part of this ecosystem. The latter stands out by offering this type of computing for other markets than the smartphone such as virtual personal assistant, drones or smart camera.
At the top of the pyramid, the tech giants are also designing their own hardware, especially at the level of cloud computing, where the value is even stronger and the clear objective of the data, today's equivalent of currency, different.
