Intel AI- building on Xeon

Intel launches two Xeon D processors for edge work as prelude to MWC | Fierce Electronics

Suppose you are of the opinion that artificial intelligence is super special and only used by scientists for niche areas of specialization. In that case, you will be surprised that it is not the case.

Ai is becoming ubiquitous and indispensable in all business areas and its functions. The new reality of AI is that it is slowly becoming part and parcel of the life of a wide variety of people, and it is no longer restricted to scientists to play with. AI has found a wide range of usage amongst business applications, optimization of IT processes, recommendations, and predictions, and improved employee and consumer experiences.

With Ai having an indisputable role in the future, one feels only thankful for already expecting it. In response, Intel has ensured that all its processors of data centers for the general purpose are adept with future demands and requirements and optimized well with AI. Intel provides acceleration programs for its AI, which are built-in and compatible with almost all the popular AI frameworks.

The Intel Xeon scalable series processors are considered the only CPUs for data centers that have an in-built AI acceleration. Furthermore, Intel also enhances the hardware to increase security, and the optimization of the software can be found built right into the silicone.

The CPUs of Intel Xeon are empowered by one API standard, which runs on open-source code. This makes it easier for you to create and deploy smarter and more beneficial models for your customers. This combo of API-CPU has won a lot of attention because of its capability to simplify the ability of your consumer to migrate from AI concepts to full-on function. These updated new processors enable your customers to make a selection out of a wide range of options of verified and pre-integrated solutions for AI and data analytics. This is inclusive of database enterprises and a variety of applications.

Some of the perfect examples of Intel AI building on Xeon processors can be noted below:

  • Burger King – AI deep learning is used to create a recommendation system for fast food. AI was deployed with the goal of increasing sales but also improving the experiences of the customer. The system correlated various attributes such as time, location, and weather while the customer placed an order. The recommendation system works by using Apache Spark to integrate and process the data. Apache Spark is an analytical engine that is open source in nature. It was trained by the distribution of MXNet, which again is a deep learning framework that is open source, and all this uses an Intel Xeon cluster of processors.
  • SK Telecom: one of the biggest mobile operators in South Korea deployed intel Xeon processors when it wanted to analyze data across all its cell towers. They constructed a complete end to end pipeline of AI. using a combination of the library of math software, tensor plow ability of intel, its unified analytics, Apache Spark, ad analytcas Zoo. all this running on a cluster of servers that is run by Xeon processors, deep learning from Intel.
  • HYHY is a Chinese company that is involved in developing deep learning-oriented tech and computer vision programs. This company managed to create an imaging system that was of great help to the medical industry in diagnosing various diseases. The system relies on Intel technology to achieve its results. Xeon Scalable processors empowered by deep learning from Intel in combination with the Open Vino toolkit, specifically designed to use speech recognition, computer vision, natural language processing, and more.

Artificial intelligence is definitely the big next wave in the computing industry. We are making our world increasingly smart and more connected with each passing day. The developments by a team of Intel Xeon processors have helped fuel and act as catalysts in the computing era dominated, which is to be dominated by AI. Ai can be well utilized to tackle problems of large scale that otherwise would be so complicated and time-consuming to be resolved. It is fair to expect an overwhelming help in quickening the process of inventions and scientific discoveries. These managing tasks are monotonous and also act as an extension of our capabilities and senses. Deep learning is one of the fastest emerging sections in machine learning. Neural networks can be trained to infer or interpret the data at better accuracy and speed, which is much faster. These are exceptionally helpful in recognition of speech and searching images, processing natural language, or any such complex tasks. The eon processors help boost the performance of AI to the net level using its deep learning capabilities. The processor technology has been revamped to accelerate the deep learning of AI.


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