Last Updated on October 22, 2023 by Kevin Chen
Image of AI chip source DesignNews
Artificial intelligence is poised to be the driver of the current and future economies. Most products will be powered by AI chips. We are already witnessing it in the automotive industry(autonomous cars). Smart homes, computer vision, robotics and even service industry are likely to be affected by the development of AI technology.
AI chips are basically microprocessors that specialize on handling the AI workload. They are faster, robust and more efficient than the normal chips.
Who makes AI chips?
There is quite a number of manufacturers that have jumped into this ship.
In this guide, we are going to look at the to 10 AI chip makers that you should know.
Alphabet is Google’s parent company that has been known for making major strides in the field of AI and general electronics. In the recent years, the company has focused its effors on the building of AI chips.
The Tensor Processing Unit is a known ASIC chip that Google developed explicitly for its TensorFlow AI programming framework. This chip is used in various AI-related fields such as machine learning, deep learning and neural network.
The Edge TPU is another chip that the company developed mainly for the “edge” electronic devices such as smartphones and other smart devices.
Google has collaborated with other major chip makers such as AMD in integrating its chips with AMD processors.
Having created its semiconductors for quite a while, you should expect Apple to eb on the list of the best AI chip makers in the world. In the recent years, the company has been putting efforts in getting into the field of artificial intelligence. Cutting ties with Qualcomm seems to have made things better.
The most recent products from the company are run by the A11 and A12 “Bionic” chips. This family of chips is known for its advanced AI capabilities. The chips feature 16-core Neural Engine which can perform a number of intelligent functions such as natural language processing, augmented reality and image recognition.
The Bionic chips from Apple are also faster and more efficient than their previous chips.
Being a dominant force in the chip making business for years, we should expect major moves from Intel. The company is performing quite well when it comes to the AI chips. Reports claims that Intel has made billions from the sale of AI chips alone. It may not be biggest chip maker right now but it is still at the top of the list.
Intel has quite a diverse portfolio when it comes to the AI chips. Some of its products include AI-centered CPUs, ASICs and FPGAs. Just for illustration, Intel Xeon processor has been used for AI model training and inference.
Known for heavily dominating the field of GPUs, Nvidia has also made some serious strides in the field of artificial intelligence. It is ranked to be the leading AI chip manufacturer and reports indicate that it boasts of a market share of over 70%.
Nvidia has a reputation of its AI-based GPU accelerators such as the Titan and Tesla. These two are widely used for AI model deep learning and inference. For example, the latest chips from the manufacturer such Jetson Xavier and A100 are designed for high-precision training where they deliver better performance. The Nvidia GPUs are customize for both software and hardware packages
Arm is a major player in the field of chipsets. For years, it has been designing semiconductors that are used by other electronic manufacturers such as Apple. The main attribute that distinguishes Arm from other companies in this list is a designer of semiconductors and not a chips manufacturer. This alone gives it some power in the manufacturing of the AI chips.
When it comes to the AI-specific projects, Arm is designing a advanced AI chips that are aimed at increasing the speed and efficiency of machine learning. For example, the Arm NN AI chip is designed to work with different ML frameworks such as Caffe and TensorFlow. In general, Arm has the capacity to influence the AI market towards a particular direction.
Qualcomm is quite a big name in the mobile devices market. It makes chips that are used to run performance-oriented smartphone devices. With the rising popularity of AI, the company has shifted to developing AI chips for mobile devices.
The Snapdragon processors from Qualcomm have advanced AI functionalities such as image recognition, voice recognition, natural language processing and even computer vision.
The company has made some heavy investments in the development of AI chips and we should expect more products and chips from it. Currently they are working on the theme “Making on-device AI ubiquitous” whereby they channel their resources towards research and development of AI devices.
Xilinx boasts of manufacturing chips that have the largest number of transistors. The company has ventured into AI and claims that its Everest chipsets have up to 50 billion transistors.
Versal is another AI chip from Xilinx and is used for both model training and inferencing.
Other than Versal and Everest, Xilinx also manufactures FPGA and claims to be among the leading manufacturers of this AI chips. The company has also been collaborating with other players such as AMD and aims to expand its efforts towards making more adaptive solutions for the AI and machine learning technologies.
Known for manufacturing cutting-edge electronics, Huawei has also entered into then AI chips market. Most of its AI processors are designed for mobile devices since this is the field that the manufacturer has dominated.
Huawei boasts of its Kirin processor which is embedded with a couple of AI capabilities including image recognition, natural language processing and voice recognition.
Other than Kirin, the company has launched Ascend 910 and claims to the world’s most powerful AI processor. This chip has a powerful AI computing capabilities and is heavily used in the model training. The processor meets the need of modern applications of AI such as autonomous driving and training.
IBM is quite a big name when it comes to the world of data and computing. Although it is expected to be way ahead of the rest in the pack, it has still achieved some major milestones.
IBM PowerAI Vision is one of the most popular chips from IBM. It is mainly used for training the deep learning models. This chip is well optimized for performance, data handling and energy management.
IBM has a dedicated IBM Research AI Hardware Center that specializes in creating computer chips for AI workload. The company hopes to create more advanced steps in the AI chip technology.
Known for its popularity in ecommerce and cloud computing(AWS), Amazon is also a big player in the AI chip technology. Amazon owns the Infrentia chip which is mainly used for the inference and training of the deep learning models. The chip is designed for low latency while at the same time deliver high throughput. It is capable of performing common AI tasks such as natural language processing, image recognition, and speech synthesis.
Amazon has been continuously developing and tuning the Infrentia accelerators to an extent that it can power both the hardware and software AI applications. Amazon also has the AWS Neuron which has the image recognition, voice recognition, language translation and speech recognition capabilities.
Well, these are the 10 manufacturers that are spearheading the investment in AI chips technology.
Things to look for when choosing AI chip makers
From the above list of the top AI chip manufacturers, you can tell that each company is committed to delivering the best chip. So which one should you choose? To help you make the right decision, I have compile a list of factors that you should consider when choosing AI chip manufacturers.
The cost of the chip
What is the price of the AI chip that you want to buy? Generally, we tend to assume that AI chips are expensive. While it could be true that they are costlier than the traditional computer chips, you can get a good deal if you buy from affordable AI chip maker.
Most AI chip manufacturers in China are more affordable than their counterparts in the USA. Take time to compare the prices of the chips before you decide on one. However, this does not mean that you should pick the cheapest option available.
Buying AI chips in bulk is also an effective way of getting them at affordable prices. Find out the suppliers or manufacturers that have such offers or deals.
Direct support from the manufacturer matters when it comes to buying sensitive electronic components such as AI chips. Choose a manufacturer that offers detailed, and timely support regarding their chips.
Support comes in different forms including technical documentation, on-site and online training, products updates among others. The support can also come in the form of the available forums and groups about the chip.
Research and innovation
All the chip manufacturers we have listed seem to have invested significantly on research and development. However, you should still choose a manufacturer that seems committed to R&D. They should show effort that they are continuously building and improving their products. An innovative company will eventually improve the quality of the chips over time.
This factor requires that you always stay updated on news about AI chips. Subscribe to websites such as this and other news outlets for the latest innovations that companies are making in the field of AI.
Before you even focus on the manufacturer, take time to look at the technical specifications of the AI chips that you want to buy. The specs will eventually determine the overall performance of the chip.
The specs that determine the performance of the chip include the processing power, energy efficiency, architecture, memory bandwidth, among others.
After listing down all these specs, you can go to the websites of the manufacturers and choose one whose specs match your requirements.
Other than the performance, you should also consider the compatibility of the chip with your device or application. The chips from the manufacturers should be compatible with your software ad hardware infrastructure. For example, AI chips from Google are perfectly compatible with the TensorFlow framework.
Beyond the performance factor, you should also consider the security factor of the AI chip that you want to buy. The mere fact that AI chips will be handling and processing large volumes of data means that they must have strong security features.
The big question that you should ask is; which is the most secure AI chip? The manufacturers should clearly state the security features that they have implemented on the chip. This can be in the form, of data encryption, secure boot and other protection mechanisms against possible attacks.
Once you consider all these factors, you should be able to choose the best AI chip manufacturer with full confidence.
There you have it! Now you know the top AI chip makers that deserve your full attention. From the list, you can tell that each AI chip maker has a unique profile and are located in different places.
Some companies have better chip manufacturing capacity than others. So, you should take your time to analyze the manufacturer that is likely to meet your needs.
Other than the manufacturer, you should also focus on the supply chain of the AI chips. Choose the best supplier of artificial intelligence chips.
This is where ICRFQ comes in. We are a leading AI chips distributors at the global scale. We have the full capacity to supply the chips to our clients across the world without any restriction.
We source AI chips from the best manufacturers so you can be sure of quality. You can also be sure of the quantity as we can meet your demand if you want to buy AI ships in bulk. All you need is to contact us and place your request for the AI chips. All you need is to contact us and place your order for the AI chips in China.
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