Deep Learning Chipset Market Poised for Explosive Growth, Reaching $72.8 Billion by 2033

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As per a new market study report published by Fact.MR, deep learning chipset sales are expected to reach US$ 4.7 billion globally by 2022. By the end of the forecast period, the market is expected to reach a valuation of US$ 72.8 billion, with a projected Compound Annual Growth Rate (CAGR)

As per a new market study report published by Fact.MR, deep learning chipset sales are expected to reach US$ 4.7 billion globally by 2022. By the end of the forecast period, the market is expected to reach a valuation of US$ 72.8 billion, with a projected Compound Annual Growth Rate (CAGR) of 27.9% from 2023 to 2033.

The Deep Learning Chipset Industry sales report provides a thorough examination of a range of aspects, such as manufacturing capabilities, global Deep Learning Chipset market forecast, product innovations, demand for Deep Learning Chipsets, and sales income generation.

A growing number of consumer devices, including smartphones, smart speakers, AR/VR headsets, and deep learning chipsets for AI processing, are also using deep learning chipsets.

Download a Sample Copy Of Report: https://www.factmr.com/connectus/sample?flag=S&rep_id=8736

The market is expected to grow in tandem with the rising usage of deep learning chips in consumer electronics, the advent of quantum computing, and the improved use of deep learning chips in robots. Deep learning is being used more and more in smart home appliances, like smart speakers, smart lights, and smart thermostats. This is because deep learning can be used to gather daily data from users' devices and use that data to deliver products and functions that are tailored to their specific needs.

Key Companies Covered

  • Alphabet Inc.
  • Amazon.Com, Inc.
  • Advanced Micro Devices
  • Baidu, Inc.
  • Bitmain Technologies Ltd.
  • Intel Corporation
  • Nvidia Corporation
  • Qualcomm Incorporated
  • Samsung Electronics Co. Ltd.
  • Xilinx, Inc.

The primary driver propelling the market's expansion in North America is the increasing adoption of deep learning in cloud computing across many sectors. In addition to cloud computing, deep learning chip-using smart home products are becoming more and more common in the area.

It is anticipated that by 2022, there will be around 112 million smart homes in the region. During the evaluation period, it is anticipated that the market for deep learning chips in the area would grow due to the growing popularity of deep learning in smart home appliances.

Key factore:

  • The deep learning chipset market has been growing in recent years due in large part to the increased need for deep learning across a number of industries, including consumer electronics, healthcare, automotive, and aerospace & military. The large amounts of data that businesses employ to train deep learning and machine learning models to comprehend customer behavior are the cause of the demand spike.

 

  • The market is expected to grow in tandem with the rising usage of deep learning chips in consumer electronics, the advent of quantum computing, and the improved use of deep learning chips in robots. Deep learning is being used more and more in smart home appliances, like smart speakers, smart lights, and smart thermostats. This is because deep learning can be used to gather daily data from users' devices and use that data to deliver products and functions that are tailored to their specific needs.

 

  • A smart house is one that has two or more smart appliances, such smart lightbulbs and thermostats. There were 258 million smart homes globally in 2021, and by 2025, that number is expected to rise to over 478 million. The demand for deep learning chips has increased as a result of consumers' growing need for smart home appliances; as a result, the deep learning chip market is anticipated to grow over the assessment period.

 

  • A growing number of consumer devices, including smartphones, smart speakers, AR/VR headsets, and deep learning chipsets for AI processing, are also using deep learning chipsets.

Read More: https://www.factmr.com/report/deep-learning-chipset-market

Competitive Analysis :

A few of the recent developments in the market are :

  • In March 2022 - Google and UC Berkley announced that they have found a way to use artificial intelligence to design faster and smaller chips. Using this, google aims to produce smaller and more efficient chips.
  • In May 2020 - Neuchips Corporation, announced the world’s first recommendation engine RecAccel which can perform 500,000 interfaces per second.
  • In December 2019 - Intel Corporation acquired HABANA labs ltd., an Israeli start-up that is working on deep learning algorithms. This acquisition will strengthen the AI capability of Intel Corporation.
  • In November 2019 - Intel Corporation launched Nervana Neural Network processors for deep learning. This chip will enable intel to strengthen itself in the deep-learning chip market.

Segmentation of the Global Deep Learning Chipset Market :

  • By Type :
  • Central Processing Units - CPUs
  • Graphics Processing Units - GPUs
  • Field Programmable Gate Arrays - FPGAs
  • Application-Specific Integrated Circuits - ASICs
  • Others (NPU & Hybrid Chip)
  • By Technology :
  • System-on-chip - SOC
  • System-in-package - SIP
  • Multi-Chip Module
  • By Region :
  • North America
  • Latin America
  • Europe
  • Asia Pacific
  • Middle East and Africa

The Deep Learning Chipset Market is poised for substantial growth, driven by increasing applications in AI and machine learning across various sectors. As demand for computational efficiency and processing power rises, semiconductor manufacturers are innovating to meet these needs. With advancements in neural networks and deep learning algorithms, the market is expected to expand further, offering opportunities for both established players and new entrants to capitalize on this burgeoning technology landscape

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