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엣지 AI 칩셋 : 기술 전망과 이용 사례

Edge AI Chipsets: Technology Outlook and Use Cases

리서치사 ABI Research
발행일 2019년 08월 상품 코드 909245
페이지 정보 영문 29 Pages
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엣지 AI 칩셋 : 기술 전망과 이용 사례 Edge AI Chipsets: Technology Outlook and Use Cases
발행일 : 2019년 08월 페이지 정보 : 영문 29 Pages

세계 엣지 AI 칩셋(Edge AI Chipsets) 매출은 2018년에 106억 달러를 기록했습니다. 이 시장은 향후 31%의 CAGR(연간 복합 성장률)로 확대되며, 2024년까지 710억 달러로 확대할 것으로 예측됩니다.

엣지 AI 칩셋 시장에 대해 조사했으며, AI 및 엣지 AI 칩셋의 정의, 주요 엣지 AI 칩셋, 시장 동향, 시장 예측 및 주요 기업 개요 등의 정보를 정리하여 전해드립니다.

제1장 개요

제2장 인공지능(AI)의 정의

제3장 엣지 AI 칩셋의 요구

  • AI의 엣지 이동
  • 엣지 이용 사례의 다양성과 복잡성
  • 주요 AI 이용 사례의 리스트

제4장 엣지 AI 칩셋의 정의

제5장 주요 엣지 AI 칩셋 벤더

  • IP 코어 라이선싱 벤더
  • 반도체 벤더
  • 캡티브 벤더

제6장 오픈소스 엣지 AI 칩셋

  • 오픈소스 칩셋의 베스트 프랙티스

제7장 "VERY EDGE"의 등장

제8장 시장 예측

  • 시장 규모
  • AI
  • 매출 예측

제9장 주요 제안·결론

게재 기업

  • AAEON
  • Achronix
  • ADLINK
  • Adnes Technology
  • AISpeech
  • AlphaIC
  • Ambarella
  • Amlogic
  • Apple
  • ARM
  • Baidu
  • Bitmain
  • Bragi
  • Brain Corp.
  • Broadcom
  • C-Sky
  • Cadence
  • Cambricon Technologies
  • CEVA
  • ChipIntelli
  • DJI
  • Ecovacs
  • Efinix
  • Esperanto Technolgies
  • FANUC
  • Google
  • Greenwave Technologies
  • Gyrfalcon Technology
  • Hailo
  • Hangzhou NationalChip
  • Horizon Robotics
  • Huawei
  • iFlytek
  • Imagination Technologies
  • InCore Semiconductors
  • Intel
  • Intuition Robotics
  • iRobot
  • Kneron
  • Lattice Semiconductor
  • LGE
  • MediaTek
  • Mobvoi
  • Nissan
  • NVIDIA
  • NXP
  • OPPO
  • Qualcomm
  • Quicklogic
  • Renesas
  • RISC-V
  • Rockchip
  • Samsung
  • SiFive
  • Sonos
  • Synopsys
  • Syntiant
  • TCL
  • Tesla
  • Unisound
  • VeriSilicon
  • videantis
  • Vivo
  • Volvo
  • Wave Computing
  • Whirlpool
  • Xiaomi
  • Xilinx
  • Yamaha Motor
  • Zenrin
KSA 19.09.06

As AI moves to the edge, edge AI chipsets becomes more important. Edge AI chipsets refers to computational chipsets focusing on AI workload that is typical deployed in edge environments, which include end devices, gateways and on-premise servers. This chipset is generally designed for AI inference workload, though in some cases, they can also support some level of AI training, particularly the training of deep learning models.

Overall, ABI Research estimates that the annual global edge AI chipset revenues for 2018 is US$10.6 billion. The market has experienced strong growth in the past and is expected to continue to grow to US$71 billion by 2024, with a CAGR of 31% between 2019 and 2024. Such strong growth is propelled by migration of AI inference workload to the edge, particularly in the smartphones, smart home, automotive, wearables, and robotics industry.

This report explores the dynamic landscape of edge AI landscape. By looking at chipset architecture, their respective computational requirements and use cases, the report provides a holistic view on the current state and future trends of edge AI chipset. Key players in the edge AI chipset industry have also been profiled with their key capabilities highlighted.

In addition, the report also looks into current development in open-source chipset. Under RISC-V, open-source chipset startups have started to develop AI-dedicated chipset with high parallelistic computing capabilities. Due to participation and contributions from across the industry, open-source AI chipsets will be more in line with market requirements and expectations, significantly reducing the cost of error and development costs in product maintenance and upgrade.

Table of Contents

1. EXECUTIVE SUMMARY

2. DEFINITION OF ARTIFICIAL INTELLIGENCE

3. THE NEED FOR EDGE AI CHIPSETS

  • 3.1. AI Migration to the Edge
  • 3.2. Diversity and Complexity of Edge Use Cases
  • 3.3. List of Key AI Use Cases

4. DEFINITIONS OF EDGE AI CHIPSETS

5. KEY EDGE AI CHIPSET VENDORS

  • 5.1. IP Core Licensing Vendors
  • 5.2. Semiconductor Vendors
  • 5.3. Captive Vendors

6. OPEN-SOURCE EDGE AI CHIPSETS

  • 6.1. Best Practice for Open-Source Chipsets

7. THE EMERGENCE OF THE "VERY EDGE"

8. MARKET FORECASTS

  • 8.1. Market Size
  • 8.2. Location of AI Inference and Training Workloads
  • 8.3. Revenue Forecasts

9. KEY RECOMMENDATIONS AND CONCLUSIONS

Companies Mentioned

  • AAEON
  • Achronix
  • ADLINK
  • Adnes Technology
  • AISpeech
  • AlphaIC
  • Ambarella
  • Amlogic
  • Apple
  • ARM
  • Baidu
  • Bitmain
  • Bragi
  • Brain Corp.
  • Broadcom
  • C-Sky
  • Cadence
  • Cambricon Technologies
  • CEVA
  • ChipIntelli
  • DJI
  • Ecovacs
  • Efinix
  • Esperanto Technolgies
  • FANUC
  • Google
  • Greenwave Technologies
  • Gyrfalcon Technology
  • Hailo
  • Hangzhou NationalChip
  • Horizon Robotics
  • Huawei
  • iFlytek
  • Imagination Technologies
  • InCore Semiconductors
  • Intel
  • Intuition Robotics
  • iRobot
  • Kneron
  • Lattice Semiconductor
  • LGE
  • MediaTek
  • Mobvoi
  • Nissan
  • NVIDIA
  • NXP
  • OPPO
  • Qualcomm
  • Quicklogic
  • Renesas
  • RISC-V
  • Rockchip
  • Samsung
  • SiFive
  • Sonos
  • Synopsys
  • Syntiant
  • TCL
  • Tesla
  • Unisound
  • VeriSilicon
  • videantis
  • Vivo
  • Volvo
  • Wave Computing
  • Whirlpool
  • Xiaomi
  • Xilinx
  • Yamaha Motor
  • Zenrin
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