Industry Essence Published Artificial Intelligence (AI) Accelerator Market Guide for Venture Capitalists

Top Quote 38% VC professionals favored AI chipset market for investment over other emerging technologies, 31% VC professionals consider AI hardware market as 'high risk-high return' market, 61% VC professionals consider AI processor startups as 'hard to exit' compared to AI software startups. End Quote
  • (1888PressRelease) June 11, 2019 - Industry Essence published a handbook on "Artificial Intelligence (AI) Accelerator Market Guide for Venture Capitalists: Investment Trends, Technological Insights, High-Growth Potential Markets, Promising Startups, & Forecasts 2018-2025"

    Joseph Schumpeter (1883-1950), an Austrian economist, economic historian & capitalist developed innovation theory of trade cycles in 1942. According to Schumpeter’s ‘Creative Destruction’ theory, creative destruction is a process in which new technologies, new products, new methods of production and distribution make old ones obsolete, forcing existing entrepreneurs to quickly adapt to a new environment or fail. Schumpeter’s theory is still appropriate in the Artificial Intelligence era. Industry has seen striking growth in the field of Artificial Intelligence (AI) over the past decade. The technology isn’t completely new to us; though the term “AI” initially coined in 1955, scholars have been originating it from centuries. AI and Internet of Things (IOT) have propelled industrial revolution 4.0, which is projected to completely transform our lives. Considering major developments in the AI, Machine Learning (ML), and Deep Learning (DL) technologies, Industry Essence has published several technology and market research reports in the past, covering AI hardware, software, and service markets. However, after conducting over 400 primary interviews for our AI and associated technology research reports, our team identified a need to offer a comprehensive market and technological insight research report, particularly for investors. Just to be sure, we then connected with around 52 Venture Capitalists (VCs) over the globe and discussed on rapidly growing AI, ML, & DL technology markets, VCs role, investor specific market insight needs, technological research needs, and on other associated areas. From these discussions, we learn the need to work on a specific syndicate research report related to- AI accelerators/chipsets for VCs, angel investors, incubators, corporate investors, banks, investment bankers, and government agencies.

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    AI performs complex tasks of learning and cognition at a level that matches or exceeds that of human performance; therefore it’s a distinct technology from the perspective of business models and value creation. Every time a new technology has successfully developed in the AI market, it has been tagged as a complete new industry, for example, search engines, speech recognition, voice recognition, industrial robotics, autonomous vehicles, computer vision, and many others. Rapid emergence of AI technology is majorly driven by six factors- development of advanced AI algorithms, easy availability of vast data to train AI systems, development of technologically advanced processors and Accelerators for AI training and inference processes, rising datacenter based AI services by technology companies for Machine Learning and Deep Learning engineers and developers, rapidly developing Open Source AI software platforms, and growing investments in AI technology by investors. Globally business leaders have great expectations from the AI technology than any other emerging technologies, including Internet of Things (IoT), Blockchain, and Augmented and Virtual Reality.

    The AI technology adoption rate was tripled globally in 2018, with one in seven companies have adopted the technology. Maturing AI technology, increasing awareness and investments, falling technology cost, and easy availability of open source APIs are motivating the enterprises to adopt the technology quickly. Chinese companies are frontrunners in terms of AI adoption rate, around 31% companies have already adopted the AI technology in some form in mainstream operations and rests are rapidly finding their ways to implement it. US ranked second with 23% AI adoption rate, followed by India, UK, France, Germany, Japan, and many others.

    Considering the huge potential of AI to create a massive impact on global economies in the coming years, investors are aggressively investing in AI technology startups. In 2018, Venture Capitalists (VCs) invested around 25 Billion USD worldwide in AI technology startups. In past six years, the market has witnessed hefty million dollar investments in AI startups.
    In the global AI technology market, over 150 VCs are actively investing in AI startups. Some of these are Google Ventures, Y Combinator, Kleiner Perkins Caufield & Byers, Data Collective, New Enterprise Associates, Accel, Norwest Venture Partners, Techstars, Khosla Ventures, and Intel Capital among many others.

    AI startups use these investments for further R&D and product enhancement, talent acquisition and retention, global business expansion, and marketing activities- market share acquisition. Though the VCs are raising large capital to invest in AI technologies, Industry Essence analyst team has critically analyzed the AI trend- AI just a technological hype or it will actually deliver what it promises?
    AI Accelerator market offers range of attractive investment opportunities for VCs. The AI technology market can be segmented by different AI accelerators by infrastructure, technology types, chipset type, processors, by technology types, innovative AI computing, end-user industry applications, regions and countries. Industry Essence is analyzing these market segments and potential investment opportunities for VCs.
    While conducting primary interviews, we came across different challenges faced by VCs and startups at different stages, our analyst team has analyzed and offered solutions and recommendations on these topics.

    In this research report, we comprehensively analyze AI Accelerator market including AI network and memory segments and cloud/datacenter & on edge accelerators. The report will definitely add a great value at multiple decision points for VCs, right from primary market understanding to VC investment decisions at various funding stages in AI startups. There are more than 5000 startups worldwide, developing AI, ML, DL, and other intelligent technologies. In this report, we are analyzing entire market ecosystem, analyzing VCs (investors), Intellectual Property (IP) vendors, technology giants, startup ecosystem, IC & semiconductor companies, and end industry users.

    The AI data center accelerator market was valued at USD 2.84 Billion in 2017 and it is projected reach USD 99.1 Billion by 2025, at a CAGR of 55.8% between 2018 and 2025. In this revamp report, we are increasing our growth forecasts (CAGR) from 46.1% to 55.8% CAGR from 2018 to 2025. The revision is made due to the significant growth in new product launches in early 2018. The report qualitatively and quantitatively analyzes revenue drivers, restraining factors, and opportunities present for active companies in this market. In the coming three to four years, the AI market is projected to grow exceptionally due to the rising demand for AI solutions at edge/device computing.

    We analyze the market attractiveness with help of Porter’s five forces model. This model is based on the qualitative and quantitative inputs from primary respondents and secondary data sources such as annual reports, press releases, company websites, and Industry Essence’s paid databases. This model analyzes most influential factors for the market and assists companies in taking key decisions such as exploration of investments avenues, expansion plans, production enhancement, market strategy building, pricing and product positioning, revenue enhancement, and deciding backward/forward integration steps.

    AI functions- training and inference are performed either on cloud or at device level (on edge) or in some cases partially on cloud and edge. We’ve segmented AI accelerator market based on the infrastructure computing- data center and on edge. Currently more than 50% AI operations (training and inference) are performed by cloud based accelerators, however, with development of advanced AI processors for smartphones, tablets, automotive vehicles (AV), smart speakers/devices, fitness bands and healthcare devices, Head Mounted Displays (HMDs), drones, robotics, and many other devices, the market for on edge accelerators will increase exceptionally in the years to come.

    In this report, we have segmented AI Data Center Accelerator Market by processor types- Central Processing Unit (CPU), Graphics Processing Unit (GPU), Field-programmable Gate Array (FPGA), and Application-specific Integrated Circuits (ASICs). The market for ASICs is projected to grow at a highest CAGR of 91.9% between 2018 and 2022. ASICs have the best performance, power, and efficiency in performing specific applications and therefore they’re expected to be employed in most of the AI data centers.

    Hey! Have you already invested in AI accelerator/chipset company/companies and looking to invest in a technology pioneer? Yes, there’s plenty of room! In past couple of years, few startups are innovating at architecture level to accelerate neural networks to next level. It includes optical computing, analog computing, Processing in Memory (PiM), and neuromorphic computing architectures. These startups are projected to disrupt the market exceptionally in the coming years, therefore VCs can go a step further and invest in these multi-billion dollar technologies. We’ve analyzed a range of promising startups working on these innovative technologies and profiled them in the report.

    AI Data Center Accelerator Market is segmented on the basis of technologies- machine learning, natural language processing, vision computing, and contextual computing. Machine learning market is further sub segmented as- deep learning, supervised learning, un-supervised learning, and reinforcement learning among others.

    AI technology is used in various applications around the globe and therefore accelerator market is further segmented as end user industries- agriculture, automotive, FinTech, healthcare, human resources, law, manufacturing, marketing, retail and security. In 2017, more than 30% market was occupied by marketing industry wherein more than 60% market value was attributed to search advertising and social media advertising. In this report, we are comprehensively covering all the sub segments of these industries. AI accelerator market in marketing industry was valued at USD 0.94 Billion in 2017 and it is projected to reach USD 20.17 Billion by 2025 at a CAGR of 45.5%.

    Global AI accelerator markets are covered in the report- North America, Europe, APAC, Latin America, and Middle East and Africa. The report further sub segments regional markets by major countries including- US, Canada, Mexico, UK, Germany, France, Italy, Spain, China, Japan, India, Korea, Middle East & Africa, and Latin America among others. North America is the largest market for AI accelerators, largely dominated by US. Most of the AI technology giants are headquartered at US such as- Intel Corp (US), Nvidia (US), Google LLC (US), IBM Corporation (US), Apple Inc (US), Qualcomm Inc (US), and many others along with many startups. China is one of the major AI technology adopter with many AI software startups and with recent government support many organizations have started developing in-house chipsets.

    The market for Artificial Intelligence (AI) accelerator market is highly competitive due to the presence of many Tier I, Tier II companies, and startups competing on the basis of innovation and product positioning. In 2016, there were less than 20 companies in AI processor market however; by the end of 2018 there are more than 100 companies that are competing in the space around the globe. Apart from US market, which dominates silicon chipset manufacturing business; there are new startups around the globe, serving range of different AI applications by innovation.

    In this report we have analyzed key organic and inorganic strategies adopted by different companies between 2013 and 2017 to remain competitive in the market. This section helps our clients to understand competitor strategies well and in adapting market needs quickly. The report profiles major companies and their thorough analysis (it includes* business summary, key financials, business diversification, market competence, expansion strategies, and SWOT analysis of major companies). Industry Essence ‘Vision Matrix’ analyze and position market participants based on two parameters- market competitiveness of product (based on many sub-factors) and growth strategy execution capability (based on many sub-factors). We’ve given snapshots from the report here; you can find the detailed analysis in the report.

    A list of Venture Capitalists actively investing in AI & Associated Technologies
    500 Startups
    Accel Partners
    AI Capital
    Alpine Technology Fund
    Amadeus Capital Partners
    AME Cloud Ventures
    Andreessen Horowitz
    Balderton Capital
    Battery Ventures
    Bessemer Ventures
    Bloomberg Beta
    C4 Ventures
    Charles River VC
    Citi Ventures
    Cognitive Ventures
    Combient AB
    Comcast Ventures
    Comet labs
    Data Collective
    Dell Technologies Capital
    Enterprise Ireland
    Entrepreneur First
    Ericsson Ventures
    Felicis Ventures
    First Round
    Founder Collective
    Founders Fund
    GE Ventures
    General Catalyst
    GGV Capital
    Google ventures
    Horizons Ventures
    IA Ventures
    Intel Capital
    Khosla Ventures
    Kima Ventures
    LDV capital
    Lightspeed Venture Partners
    London Co-Investment Fund
    Lux Capital
    M12 VC (Microsoft)
    Madrona Venture Group
    Mahindra Partners
    Motorola Solutions Venture Capital
    New Enterprise Associates
    Octopus Ventures
    Passion Capital
    Pi Ventures
    Plug and Play
    Qualcomm Ventures
    Rakuten Ventures
    Real Ventures
    Robert Bosch VC
    RRE Ventures
    SAIC Capital
    Salesforce Ventures
    Samsung Ventures
    SEED Capital Denmark
    Sequoia Capital
    Social Starts
    Sunstone Capital
    SV Angel
    Touchstone Innovations
    True Ventures
    Two Sigma Ventures
    Wipro Ventures
    Y Combinator
    Zeroth AI
    Zetta Venture Partners

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