AI Chip Market is Booming: Top 25 Players in AI Chip Market in 2020

In this era of technology, Artificial Intelligence has brought a
revolutionary change in every aspect of our life. When you see
autonomous cars, smartphones, electronic devices, or robotics
around us, you can easily discover a glimpse of the opportunities
that can be created by incorporating AI. Besides, new generation AI
processors are much more powerful, and tasks like Image processing,
machine vision, and machine learning, deep learning, artificial
neural networks can be done more efficiently. The list of top AI
chip manufacturers also displays the interest of big players like
Intel, Apple, Nvidia in this industry and establish themselves as a
key contender in the AI chip market. So it can be easily assumed
that as the leading tech giants are involved, we can expect the
growth of AI technologies to a great extent in the coming
years.

Best Players in AI Chip
Market

---

There are many companies out there who have been successful and
hold a prestigious position when it comes to manufacturing AI
processors. You can get a look at the below-mentioned list to get a
brief idea of the current AI chip market and which companies are
playing a big role.

1.
ARM

---

ARM is in the AI chip market for quite a long time now.
Currently, many leading tech companies, alongside Apple, are using
their chip for developing their products. ARM is known for
producing high-quality products that include sensors, servers, SoC
designs, a wide range of IoT solutions, software, and tools. They
are also working on security intelligence known as Platform
Security Architecture that can be employed in devices to fight
against hazardous environments. ^[1]

Besides, ARM^[2]
is working to enable the future of computing by driving the fifth
wave of computing while the social sectors, business operations,
IoY endpoints, industrial efficiency remain the main priority.
Currently, Cortex-A Processor Series, Cortex-M Processor Series,
Mali Graphics Processors, Ethos Processors, and ARM NN are in their
product line while they focus on ultra-efficiency and scalability
to work with machine learning applications and deep learning
frameworks.

2. Google

---

The tech giant Google^[3]
has also entered in this list with their AI-powered Edge TPU.
Although they are not using this hardware in any of their products
like smartphones or tablets currently, this coin-sized hardware has
already grabbed many people’s attention due to its capability of
interference at the edge to enable high accuracy AI. It is also
important to connect with the data center known as Google’s Cloud
TPU.

The main purpose of building the Edge TPU is not only to leave
their footprint in the AI chip market but also to make programming
easy in Google’s TensorFlow programming framework used for machine
learning and deep learning. The performance of this tiny hardware
is amazing, yet it consumes low power and provides end-to-end,
cloud-to-edge, hardware and software infrastructure and
customer-centric AI solutions. Also, some companies are using Edge
TPU in high-end, enterprise, and expensive machines.

3. Intel

---

Intel is one of the leading manufactures in the AI chip market.
They have already lost their position to other companies, but
Intel® Xeon® Scalable Processors are still great when it comes to
handling AI better. Xeon is not an AI processor, but one can easily
include memory analytics, autonomous driving, high-performance
computing, and network transformation alongside hardware-enhanced
security, and the deployment of dynamic service delivery. On top of
that, the 3rd generation of Xeon processors come with built-in AI
acceleration to provide a better business-to-business and
business-to-consumer experience.

Recent reports suggest that Intel^[4]
is raising the bar again to claim their position as they are
offering a wide range of AI hardware such as Intel® FPGAs, Intel®
Movidius™ Vision processing units, Intel® Xe® based GPU, INTEL®
NEURAL COMPUTE STICK 2, and Intel® RealSense™ depth and tracking
cameras. While FPGAs can handle any kind of workloads and datasets,
the VPU is designed to work with computer vision and neural network
applications.

4. Apple

---

Apple is considered as one of the most selling smartphones
manufactured available out there. They were using chipsets made by
Intel in their smart devices, but now they are determined to
develop their own Artificial Intelligence Processor to bring a huge
shift in their business. They are investing more in machine
learning research and have already started using A11, A12, and A13
“Bionic” chips in the latest phones and tablets.

These chips are way faster than the previous incarnation while
using half of the power. The latest A13 comes with a quad-core
graphics processor, an Apple-designed image processor, and an
octa-core neural engine, which lets you complete five trillion
operations within a second. But the only limitation it has is you
can not work with any third-party applications or buy one for
yourself as Apple has not yet entered the AI chip market. However,
it has a readymade market and dedicated followers.

5. Advanced Micro
Devices

---

Advanced Micro Devices, which is commonly known as AMD, has
gained a huge reputation for its products that are capable of
producing high computing power. They are always focused on
employing machine learning and deep
learning^[5] to get human-like
reflexes from intelligent applications. They are highly dedicated
to building machine learning processors that handle complex data
sets coming from thousands of input streams that come with open
core ecosystems to help software developers bring the most out of
it.

If you are an artificial intelligence enthusiast, you will admit
that, in most cases, the performance of an intelligent application
depends on the speed, capacity, and organization managed by
hardware. AMD^[6]
is focused on releasing the high-end microprocessors and associated
software to facilitate the ML and DL testing and development
process. Recently, AMD has released 2nd Gen AMD EPYC™ that is able
to optimize enterprise workloads and equipped with 7nm technology
and works 4x faster than the 1st Gen AMD EPYC™.

6. Graphcore

---

This is a start-up company that started its journey to build and
supply AI Processors of a wide range. Their main priority was to
become able to go to any level of computation to handle data of any
quantity. Although Graphcore^[7]
is a relatively new player in the artificial intelligence chip
market, it is backed by companies like BMW and Microsoft, who
invested $300 million to start its operation.

After successful operations over the years, the valuation of
this company can go up to $2 billion in today’s day. The main
product of this company is Rackscale IPU-Pod™, which comes with
scale-up and scale-out features, and you can accomplish any sort of
machine intelligence training tasks. Besides, due to its elastic
design, it can support massive levels of computation while you can
do training and inference on the same hardware. It consists of over
30,000 parallelly working independent IPU program threads that
reside inside the memory.

7. Nvidia

---

You may have already heard the name of this company due to the
extreme popularity of its graphics card. They are already in the
leading position among the gamers who choose the Nvidia Geforce
graphics card in the first place. Again, the GPUs can process
faster and better than the all-purpose chips, which make it obvious
for Nvidia to fold a strong position in the AI chip market. Nvidia
offers chipsets that are compared with AI accelerators, while the
advanced GPUs boost AI development.

If you see the market, you will discover that Tesla chipset,
Volta, and Xavier are all powered by Nvidia^[8]. At the same time,
Xavier provides a solution for autonomous driving and Volta powers
data centers. However, these are graphical processing units packed
with hardware and software solutions to provide AI solutions^[9]. Alongside machine
learning, deep learning is the main interest of this company. They
are investing regularly to get data-driven decisions derived from a
huge data set and examined over a longer period of time.

8. Baidu

---

It may sound interesting that some people compare Baidu as the
Chinese Google, although Baidu is also a search engine used mostly
by the people living in china. Baidu is only available in China and
offers applications like Maps, keyword-based discussion forums, and
also many other community services. Baidu has declared their vision
and goals to distribute business in other sectors like driverless
cars, and they need powerful microprocessors to reach the target
within the expected time.

Like Nvidia, Baidu is also interested in deep learning. They are
working on machine learning algorithms to integrate with a platform
called PaddlePaddle. They are focusing on Machine Learning
Processors, which can train themselves from interactions with
humans and the environment. Besides, they are also working on
Natural language processing based products, Baidu Mobile Assistant, voice-activated
assistant, production-quality text-to-speech system, AI-Powered
Transcription Software, and so on, which will make the path
smoother for Baidu to enter into the Machine Learning Chip Market.
^[10]

9. Mythic AI

---

Mythic started its journey to make AI available for everyone.
After successfully raising more than 40millions fund, Mythic
implemented a data center to match their philosophy to make
borderless AI technologies. Their current projects include smarter
cities and spaces, personalized devices and services, safer and
simpler vehicles, intelligent machines and robots, and so on. When
it comes to deploying accurate, powerful AI anywhere anytime, then
Mythic can be considered as one of the best.

Intelligent processing units offered by Mythic^[11] can be considered to
produce more power and better performance at a lower cost, which
can enable many people to generate AI solutions. These Artificial
Intelligence Processors come with a unique architecture for
leveraging analog computation. Mythic has recently attracted many
AI developers as their processors can help to deploy any
sophisticated neural networks to connect data centers and the edge
devices.

10. Zero ASIC

---

This company is exceptional and unique. Unlike other companies
in this list, they focus on building the cheapest AI processors to
enable people to work with AI technologies, which have a great
interest in it. As a part of this, they have already released the
cheapest supercomputer available out there. After starting its
journey back in 2008, they released 16 core 65nm SoC and 64 core
28nm SoC respectively, in 2010 and 2011.

In 2017, the company was known as Adapteva before relaunching as
“Zero ASIC” in 2020. The most successful product of this company is
known as Epiphany, released in 2014. More than ten thousand AI
developers are using this 5G licensed and 16 core SoC. Epiphany got
the attention due to its capability of parallel and heterogeneous
computation. Besides, it can be scaled to billions of processors,
which makes it the only open computing platform. The success of
Epiphany will surely help Zero ASIC^[12] to re-enter into the
Artificial Intelligence chip market.

11. Qualcomm

---

Qualcomm is quite a familiar name among
the AI developers due to its interest to make AI ubiquitous for
expanding its usability beyond smartphones. They have made a lot of
money as they were the primary chip supplier for Apple from the
journey of its Smartphone production, which eventually helped them
to hold a strong position in the AI chip market and invest more in
R&D for exploring new opportunities. ^[13]

Their main interest lies in ensuring user privacy, immediacy,
and enhanced reliability through the use of AI augmentation.
Gaining efficiency in the existing processes is also highlighted,
which you can sense after they have released Cloud AI Chip that has
brought a revolutionary change in the fifth generation
telecommunication. Besides, they are also working on delivering AI
hardware, software development kits, Power Efficiency, and seamless
personalization to make AI available to people of all kinds.

12. Blaize

---

Blaize, which has recently changed its name from Thinci has been
there in the AI chip market for quite a lot of time now. They
started their journey to make AI widely available to not only the
enterprise but also the people. They have introduced a silicon
architecture based Artificial Intelligence Processor that comes
with innovative software to enable engineers to extract the maximum
amount of benefit out of AI^[14]. Besides, they are also
expecting to release the best tech transformation of today’s
world.

Their BLAIZE GRAPH STREAMING PROCESSOR is extremely powerful
enough to break the limit of any amount of computing required to
handle machine learning, deep learning, and artificial intelligence
at a time. Also, Blaize^[15] offers a software
platform known as graph-native Picasso, which is radical and simple
so that users can deploy any AI application from data centers to
the edge of anywhere anytime. GSP-based hardware is also available
to the selected customers.

13. Taiwan Semiconductor
Manufacturing Company

---

It is one of the leading companies that had come under the light
when they started supplying AI chips to Apple. They are backed by
some investors, although this company does not want to show off
their actual work a lot. But if you explore their website, you will
discover that building an intelligent manufacturing environment is
what they are interested in through the application of integrated artificial
intelligence, machine learning, expert systems, and advanced
algorithms. ^[16]

They are working on maximizing the innovation to optimize
quality, productivity, efficiency, and flexibility. Besides,
TSMC^[17] has become interested
in developing applications to enable AI intelligence in mobile
devices, IoT, and mobile robots. It is also known for its data
collection, stable manufacturing, and efficient use of resources to
render fast ramp-up and quality satisfaction to worldwide
customers. You can also get support f to reach your goal if you
choose to become a user of its products.

14. Samsung

---

As people of today’s day and age, we already know Samsung as one
of the largest smartphone manufacturers available out there. But
you will be surprised to see that they have also overtaken Intel
and become the largest Artificial Intelligence Processor creator
around the world. Alongside smartphones, the Exynos processors are
also used in smart speakers, smart tv, and other electronics and
home appliances.

Samsung R&D is working to develop AI core algorithms and
expand the use of on-device AI and home edge platforms. Samsung
started its journey in the Artificial Intelligence chip market to
extract meaning from user’s visual, tactile, and emotional cues and
use it on their products, which helped them to boost the business
growth to a great extent.

Besides, Samsung^[18] examines the lifestyle
and behavior of its global consumers regularly to add more to their
AI features. It has enabled users to integrate AI into the IoT and
unlock the boundless opportunities. As a result, there is no other
company like Samsung that has contributed more to the new era of
technology and living.

15. Xilinx

---

Xilinx can be considered as the manufacturer of the
microprocessor that contains the maximum number of transistors.
They have declared that their chipsets will include up to 50
billion transistors, which are quite astonishing. Besides, they are
also working on several hardware products such as Vivado Design
Suite – HLx Editions, Intellectual Property, System Generator for
DSP, Model Composer, and so on. You can also get the
industry-standard AI inference acceleration from them.

It has also introduced the Xilinx Edge AI^[19] Platform, which is
capable of handling machine learning and AI models. You can
classify objects, process images, and complete segmentation using
this intelligent platform as well. Besides, Face detection,
Landmark Localization, Face recognition, Face attributes
recognition, Pedestrian Detection, Pose Estimation, Car Attributes
Recognition, Lane Detection are also made easy through this
platform. On top of that, the developers can also access the AI
solutions offered by the Xilinx.

16. HiSilicon

---

If you have not heard the name of this AI player yet, then you
do not need to be surprised because you are surely familiar with
the name of Huawei. They are one of the largest smartphone
manufacturers around the world, where AI chips play the most
important role. Huawei introduced its Kirin chip as a Machine
Learning Processor, which eventually boosted its revenue of
smartphone business to a great extent in between the years of 2018
and 2019.

HiSilicon^[20] is currently working on
its artificial intelligence chip to render end-to-end video
capabilities. It comes with the most advanced image processing unit
and can detect any object with the help of AI and ML. It can
generate 4Tops computing power, which enables users to get 8K
real-time encoding, and shoot 4K60 HDR video. Being the business
unit of Huawei, HiSilicon will surely help them to accelerate the
number of consumers and establish a strong position in the AI Chip
Market.

17. LG

---

LG has been holding a special place in the consumer’s heart as a
reliable and leading supplier of home appliances and smartphones.
To remain on the top in the Machine Learning Chip Market, they were
one of the early achievers of AI to bring it to the edge. They have
recognized the importance of AI and have been working to make life
smarter and easier for the consumers for quite a lot of time while
their smart tv can be easily considered the best AI TV available
out there.

They are working on behavior patterns of users and proprietary
AI algorithms to improve the performance of the data. LG is trying
to integrate AI experience in all aspects of life. Alongside home,
vehicles and public spaces are also part of their project. They
have a goal to render maximum convenience for their users so that a
sustainable change can be brought for a longer period of time,
which they term as Evolve, Connect, and Open.

18. IBM

---

You can probably expect the name of this company in any list of
top technologies. They are a big player in this field and have a
reputation for conducting well-funded research and development.
Their innovation and contribution to the growth of the artificial
intelligence chip market are unimaginable, and no one can doubt it.
They are currently working on infusing artificial intelligence in
Automation, Cloud Computing, IoT, IT Infrastructure, Security, and
Supply chain.

They have also introduced a platform known as IBM^[21] Watson, which is a
computer system and can predict future outcomes, automate complex
processes, and optimize the time. You can easily integrate AI in
any organization to increase efficiency. Besides, this will help
you to detect hidden problems, find solutions, and take necessary
actions. It comes with a multi-cloud platform^[22] designed by ML to build
powerful models from scratch. To facilitate the health sector, they
have also introduced Watson Health that uses AI for advanced
health.

19. Imagination
Technologies

---

If you consider PowerVR GPU, then Imagination Technologies^[23] can be considered as
the best player available in Machine Learning Chip Market. This
company solely focuses on the highest efficiency, lowest power, and
smallest area silicon IP cores. They are in the market for more
than twenty-five years now and render processing solutions for
graphics, vision, and artificial intelligence. Many leading tech
companies have partnered with them to generate innovations for
solving key problems through technologies.

Their PowerVR GPU comes with a complete neural network
accelerator solution for AI chips that can complete four tera
operations within a second. With the support of a wide range of
neural networks and low-power and low-bandwidth architectures, they
are playing a big role in the mobile, consumer, automotive, IoT,
AR/VR, security, and AI segments. They are also delivering EnSigma
Communications, Ethernet, SoC, Design optimization kit, and
Products demos. They have a goal to deliver AI in the palm of your
hand, industrial robots, and cloud server as well.

20. Via

---

Via has named their AI chip as Edge AI Developer Kit, which can
be used to develop any kind of smart camera, signage, kiosk, and
robotics systems. Besides, it can significantly reduce production
time, and the developers can release products faster. Alongside the
design, Edge Kit has made testing and deployment easy for the
systems and devices that use Artificial Intelligence. On top of
that, manufacturers can reduce the cost and complexity for
maximizing efficiency.

The Edge Kit comes with VIA SOM-9X20 SOM Module and SOMDB2
Carrier Board. At the same time, you will also get a 13MP AI camera
module, intelligent real-time video capture, image processing, and
edge analysis with the package. You will get this product in the
VIA Embedded online store, where you will find two variants.
However, Via^[24] has already contributed
a lot to AI, IoT, computer vision, autonomous vehicle, healthcare,
and smart city applications through its high standard embedded
systems and solutions.

21. Amazon

---

In this world of digitalization, we will probably not find
anyone who has not heard the name of Amazon^[25] – the best online
retailer in the world. They have already created a massive impact
in the field of AI technology through their AWS platform. Every
tech enthusiast out there knows that Amazon is working on deep
learning, machine learning, and AI for many years to make Anomaly
Detection, Fraud Detection, Image, and Video Processing, Speech
Recognition, Natural Language Understanding easily available to
their consumers.

Besides, they have also released a custom-built AI chip to
accelerate deep learning named as AWS Inferential. It comes with
four neuron cores, which can process 128 trillions of operations
per second. You will be surprised to know that Inferential can take
a 32-bit model as input and can run as a 16-bit model using
BFloat16. Also, you can expect to overcome the latency and any kind
of computational issues to improve the performance of ML algorithms^[26].

22. Wave Computing

---

This company is known for accelerating AI to the edge of the
data centers. They have also gained a reputation of being the
specialist AI platform provider and well known to the industry
leaders. They have already introduced an artificial intelligence
chip known as TritonAI, which comes with a 64bit Platform dedicated
to AI-enabled Edge SoCs. On top of that, it is supported by Linux,
and a driver layer is integrated for technology mapping.

TritonAI is known for three key features which are MIPS64 and
SIMD Multi-CPU, WaveFlow Technology, and WaveTensor Technology.
While wavetensor^[27] makes it a
highly-efficient processing engine, waveflow works as a scalable
dataflow platform that can execute the existing and new algorithms.
Besides, Virtualization extensions and Superscalar 9-stage pipeline
sets it apart from other AI chips. However, embedded, RISC and
multi-threaded CPU IP alongside the AI-Native Platform offered by
Wave Computing will surely take you to the next level of
computing.

23. MediaTek

---

MediaTek has become a familiar name in AI Chip Market like
Qualcomm after the industry of Smartphones has seen huge growth.
Although they do not build AI chips, they design and develop the
chips by themselves. Like other industry leaders, MediaTek is
working on the ecosystem of Edge-AI hardware processing, which
comes with a combination of a wide range of software to make the
most out of it. MediaTek AI chip is not only being used in
smartphones but also in smart homes, wearables, IoT, and connected
cars.

It has released an AI Processing Unit known as MediaTek
NeuroPilot. It comes with a huge computation ability yet consumes
less power, which makes it ideal for devices like smartphones and
tiny gadgets. Besides, it comes with AI operation processing, and
the SDK is supported by all MediaTek^[28] enabled hardware.
Developers can work on any applications and use all the best
frameworks available out there, such as TensorFlow, TF Lite, Caffe,
Caffe2 Amazon MXNet, and Sony NNabla.

24. Kalray

---

This company has already created an impression of being
enthusiastic for Robotics and Automation. They understand the
necessity of high computation capability at low power and focus on
real-time low-latency processing operation. Alongside artificial
intelligence, they are currently involved in improving technologies
like computer vision, autonomous vehicles, and aerospace as well.
Kalray has a goal to enable customers to take advantage of
deploying AI in embedded technologies. This European company is
also accelerating the German automotive industry.

When it comes to deep learning, Kalray^[29] offers one of the best
processing solutions available out there, which they call MPPA®.
This manycore architecture comes with high-performing deep learning
inference that allows the Neural Network layers to work
concurrently. Besides, the built-in on-chip memory can process any
number of frames per second. Its CNN capability can provide an
embedded solution rather than only running CNNs. Besides, fast
communication between layers and NoC multicasting has helped this
chip to get all the attention.

25. Groq

---

This company was founded by some of the former employees of
Google, so you can undoubtedly expect great quality. They have
already got many people’s attention through their high computing
hardware designed for working with next-generation machine
learning. The hardware offered by this company is known for using
less power to compute any number of units. It can also help to
reduce the CO2 footprint and provides zero overhead in context
switching.

Groq has a goal to make computation easy and accessible from
anywhere anytime. As a part of this goal, they are offering the
fastest ResNet-50 performance among any other hardware available
out there. You can even complete 400,000 multiplications without
using a single byte from the GPU. On top of that, Groq^[30] offers a cloud platform
for maintaining on-site machine learning infrastructures. With the
combination of AI and cognitive computing, you can easily avoid the
cost of investing in machine learning processors for ML.

Finally, Insights

---

Artificial intelligence is the future of technology. In the near
future, you can expect not to find a single device that does not
come with AI capabilities. As a result, all the leading companies
are investing and researching more to establish a strong position
for the coming war in the AI Chip Market.

Besides, machine learning and deep learning also play an
important role to make AI more powerful and improve the performance
to a great extent. The companies, as mentioned above, are bringing
AI processors every year, which has made it easy for the
manufactures to bring AI to the edge of the data centers. It does
not matter which company will lead the race; the consumers will be
benefited in every aspect.