Nvidia and Intel have been quarreling recently about who will be the "brain" of the future.

Nvidia believes that GPUs (graphics processing units) are far ahead in the field of artificial intelligence deep learning and will expand their advantages, while Intel believes that its CPUs (central processing units) will be able to replace the role of GPUs in accelerating computing.

On September 13, GTC CHINA 2016 (GPU Technology Conference) was held in Beijing. Nvidia launched two of its latest deep learning and autonomous driving products for the world, and announced a strategic cooperation with JD.com and the establishment of a joint laboratory. At the Baidu World Conference held last week, NVIDIA co-founder, president and CEO Jensen Huang announced that NVIDIA and Baidu will cooperate in the field of autonomous driving.

Due to its earlier layout, Nvidia has a major advantage in the deep learning market. At present, the vast majority of deep learning companies and institutions at home and abroad rely on NVIDIA's GPU acceleration. Global Internet giants including Facebook, Google, Alibaba, Baidu, etc. all have cooperative relationships with NVIDIA. Google's AlphaGo, which was unique last year, also has 170 GPUs connected to it.

“Currently, the standard configuration for neural network computing is GPU. In this regard, Intel currently does not invest enough and the CPU runs too slow.” The person in charge of Turing Robot, a leading domestic artificial intelligence developer, told Jiemian News.

In an interview with a reporter from Jiemian News, Hu Rui, senior R&D director of the Artificial Intelligence Group of the Microsoft (Asia) Internet Engineering Academy, believed that GPUs have become a mainstream component of artificial intelligence computing architecture because GPUs used in the fields of graphics and image processing can process large amounts of data in parallel and are very suitable for highly parallel and highly localized data scenarios of deep learning.

In the field of artificial intelligence, most companies currently use a "CPU+GPU" collaborative computing combination. In this heterogeneous mode, the serial part of the application runs on the CPU, and the GPU, as a co-processor, is mainly responsible for the heaviest part of the computing task.

Due to the strong demand for GPUs from deep learning, Nvidia’s data center department performance increased by 109% year-on-year. According to Nvidia’s latest financial report released in August, its total revenue was US$1.428 billion, a year-on-year increase of 24%, while profit reached US$253 million, a year-on-year increase of 873%. At the same time, the number of developers using NVIDIA has tripled to 400,000, and the number of artificial intelligence developers using NVIDIA GPUs has increased 25 times.

"NVIDIA is an artificial intelligence computing company." Huang Renxun said at the Baidu Conference.

NVIDIA's sudden rise in the field of artificial intelligence computing has made processor giant Intel, which is in the stage of transformation, feel threatened. Without fully grasping the situation, Intel adopted a strategy of recruiting troops and deploying extensively.

In May this year, Intel announced the acquisition of computing vision software company Itseez; in June, Intel acquired FPGA manufacturer Altera for US$16.7 billion to strengthen its dedicated chip manufacturing capabilities; on August 9, Intel announced the acquisition of deep learning startup Nervana Systems; on September 7, Intel acquired machine vision startup Movidius to continue to strengthen deep learning solutions from devices to the cloud.

Among them, Nervana was founded in 2014 by the former head of Qualcomm neural network R&D. It has the fastest deep learning framework currently and is expected to launch a deep learning dedicated chip next year, which is said to be 10 times faster than GPU.

After saving a certain amount of energy, Intel couldn't wait to launch a fierce counterattack against Nvidia, and a war of words between the two sides was about to break out.

At the Intel Information Technology Summit (IDF 2016) held in August, Intel launched Knights Mil, a new product in the Xeon Phi series, and stated in a test report that the newly launched Intel Xeon Phi processor has higher computing power than the GPU processors currently on the market, and the training speed is 2.3 times faster than the GPU - pointing the finger directly at Nvidia.

At the same time, Intel said it will launch an artificial intelligence-specific chip in 2017, which will introduce the function of accelerating artificial intelligence computing tasks for applications in areas such as speech recognition, image recognition, and autonomous driving.

Subsequently, Nvidia made a strong rebuttal to Intel’s statement that “GPUs are not as good as CPUs”.

Ian Buck, vice president of Nvidia's Accelerated Computing Business, published a blog post titled "Let's talk about the mistakes Intel made on the Deep Learning Benchmark." He pointed out that Intel used data from 18 months ago when comparing, and if you use the updated Caffe AlexNet data, you will find that four Maxwell GPUs are 30% faster than four Xeon Phi processors.

"Intel should get the facts straight first." Ian Buck said without hesitation.

Regarding Intel's various layouts in the field of artificial intelligence, Huang Jenxun expressed doubts on behalf of Nvidia: If the Xeon Phi coprocessor is very suitable for AI, why did it acquire Altera? Since you bought Altera, and Altera is very suitable for AI, why buy Nervada Systems? If Nervada Systems is the real AI technology that needs to be developed and launched, what about the Xeon Phi co-processor? If these three are suitable for AI, does that mean that the Xeon Phi coprocessor is not suitable for AI?

“I don’t quite understand their strategy at the moment, and our strategy should be very beautiful and clear: that is GPU.” Huang Renxun said.

In response to Nvidia’s doubts, Intel China general manager Rupal Shah (Xia Lebei) said in interviews with Jiemian News and other media on September 6 that in fact, Intel’s strategy is not only positioned in the “deep learning” link, but also lays out the entire artificial intelligence as an ecosystem.

“Competition is a good thing for any industry. We hope to transform the benefits of the overall technological development of artificial intelligence into business results for consumers and achieve a two-way flow from the cloud to the terminal.” Rupal Shah said.

Song Jiqiang, President of Intel China Research Institute, explained that Intel’s layout in the field of artificial intelligence adopts a combination of software and hardware, and implements computing in a low-energy, efficient way on the hardware.Calculation, and the software will perform algorithm optimization to reduce the amount of calculation.

Such a response is obviously too broad and weak, but Gartner senior semiconductor industry analyst Sheng Linghai believes that since Intel itself is much larger than Nvidia, as a leader in the chip industry, "it has its own logic."

"Intel is currently at a disadvantage in the artificial intelligence market. In order to provide more choices for enterprise customers in the future and build a complete ecosystem of artificial intelligence, Intel needs to have greater coverage, so it must invest in and acquire new technologies that may appear or be used in the future." Sheng Linghai told Jiemian News that whether a market advantage can be formed in the future depends on whether the acquired technologies can be integrated and developed.

In fact, since the artificial intelligence market is still in its early stages, processor manufacturers hope to occupy a place through their own products. Due to its focus on high-complexity neural network applications, Nvidia's GPUs have not formed a monopoly. In heterogeneous mode, Nvidia has collaborative working relationships with Intel, IBM power and ARM.

“This stage of letting a hundred flowers bloom and competing for the throne will last for 5-10 years, and it will take at least 3-5 years to see what kind of architecture will become a stable mainstream.” Sheng Linghai predicted.

Data shows that the artificial intelligence market will reach a scale of US$36 billion by 2025. Artificial intelligence will become the fastest growing part of the IT field and may lead the fourth industrial revolution after steam engines, electricity, and computers.

This is also the reason why Nvidia and Intel are fiercely competing for the artificial intelligence market. However, the difference is that Intel hopes to have a "tortoise and the hare" with Nvidia, and firmly believes that it will overtake in corners; but Nvidia feels that this latecomer does not follow the road at all, and it is unclear whether the two parties are on the same track.

So it seems that the war of words between the two sides will continue.

To read more about technology, please click View>>.