The rapid adoption of artificial intelligence (AI) for practical
business applications has introduced a number of uncertainties and risk
factors across virtually every industry, but one fact is certain: in
today’s AI market, hardware is the key to solving many of the sector’s
key challenges, and chipsets are at the heart of that hardware solution.
Given the widespread availability of AI, it is almost certain that every
application in the future will require some sort of acceleration using
AI chipsets whether it is in the data center or at the edge. The
acceleration could take a wide variety of forms, ranging from a simple
AI library running on a CPU to more sophisticated custom hardware.
According to a new report from Tractica,
the potential for AI is best fulfilled when the chipsets are optimized
to provide the appropriate amount of compute capacity at the right power
budget for specific AI applications, a trend that is leading to
increasing specialization and diversification in AI-optimized chipsets.
Tractica forecasts that this growth and evolution of the AI market will
drive deep learning chipset unit shipments from 164.9 million units in
2018 to more than 2.9 billion units annually by 2025. By the end of that
forecast period, the global market for deep learning chipsets will reach
$72.6 billion. The market intelligence firm anticipates that
application-specific integrated circuits (ASICs) will represent the
largest share of total revenue by 2025, followed by graphics processing
units (GPUs), central processing units (CPUs), system-on-chip (SoC)
accelerators, and field programmable gate arrays (FPGAs).
“During the past 2 years, the deep learning chipset market has
experienced a dramatic period of evolution, led by NVIDIA and Intel,”
says principal analyst Anand Joshi. “Yet, the upstart ASIC chip
companies are somewhat behind in their delivery schedule. Smaller chips
aimed at the edge (embedded) market are shipping, but larger chips aimed
at the enterprise market are seeing delays. Meanwhile, market validation
has already begun for the edge market and should begin for the
enterprise market in 2019. A rapid ramp-up in deep learning chipset
volumes will start in 2020, and the winners will begin to emerge during
that timeframe.”
Tractica’s report, “Deep
Learning Chipsets”, assesses the industry dynamics, technology
issues, and market opportunity surrounding deep learning chipsets,
including CPUs, GPUs, FPGAs, ASICs, and SoC accelerators. The report
provides market sizing and forecasts for the period from 2018 through
2025, with segmentation by chipset type, compute capacity, power
consumption, market sector, and training versus inference. The study
also includes 19 profiles of key industry players. An Executive Summary
of the report is available for free download on the firm’s website.
About Tractica
Tractica, an Informa business, is a market intelligence firm that
focuses on emerging technologies. Tractica’s global market research and
consulting services combine qualitative and quantitative research
methodologies to provide a comprehensive view of the emerging market
opportunities surrounding Artificial Intelligence, Robotics, User
Interface Technologies, Advanced Computing, Connected & Autonomous
Vehicles, and Wearables & Digital Health. For more information, visit www.tractica.com
or call +1.303.248.3000.
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