Speaking on stage at the conference in Beijing, Intel corporate vice president Naveen Rao made the announcement.

“The next few years will see an explosion in the complexity of AI models and the need for massive deep learning compute at scale. Intel and Baidu are focusing their decade-long collaboration on building radical new hardware, codesigned with enabling software, that will evolve with this new reality – something we call ‘AI 2.0.’

Intel’s so-called Neural Network Processor for Training is codenamed NNP-T 1000 and designed for training deep learning models at lightning speed. A large amount (32GB) of HBM memory and local SRAM is put closer to where computation happens to enable more storage of model parameters on-die, saving significant power for an increase in performance.

The NNP-T 1000 is set to ship alongside the Neural Network Processor for Inference (NNP-I 1000) chip later this year. As the name suggests, the NNP-I 1000 is designed for AI inferencing and features general-purpose processor cores based on Intel’s Ice Lake architecture.

Baidu and Intel have a history of collaborating in AI. Intel has helped to optimise Baidu’s PaddlePaddle deep learning framework for its Xeon Scalable processors since 2016. More recently, Baidu and Intel developed the BIE-AI-Box – a hardware kit for analysing the frames of footage captured by cockpit cameras.

Intel sees a great deal of its future growth in AI. The company’s AI chips generated $1 billion in revenue last year and Intel expects a growth rate of 30 percent annually up to $10 billion by 2022.

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Brian Krzanich made the comment during an on-stage interview at the WSJD Live conference in Laguna Beach, California. The news Intel is working on its own AI chips is no surprise, but the choice of partner may be.

“This is the first piece of silicon,” Krzanich said. “We have a whole family planned for this, (Facebook) is helping us, along with others, as to where this is going.”

Many consumers are wary of Facebook because, like Google, the company relies on collecting vast amounts of data about users. While it’s unlikely Intel would allow Facebook to perform any data collection of its users; there will doubtless be some concerns.

Facebook was the only named company but Intel is also collaborating with others for its AI chips. The extent of the partnerships, or what benefits the partners receive for providing their resources, is currently unknown. We’ve reached out to Facebook and Intel for clarification.

Intel is aiming to build the first Neural Network Processor (NNP) before the end of this year. The company is calling this ambition Nervana, following the company of the same name Intel acquired in August last year, and it promises to “revolutionise AI computing” across a myriad of industries.

In a blog post, Krzanich provided the following examples:

• Healthcare: AI will allow for earlier diagnosis and greater accuracy, helping make the impossible possible by advancing research on cancer, Parkinson’s disease, and other brain disorders.
• Social media: Providers will be able to deliver a more personalized experience to their customers and offer more targeted reach to their advertisers.
• Automotive: The accelerated learning delivered in this new platform brings us another step closer to putting autonomous vehicles on the road.
• Weather: Consider the immense data required to understand the movement, wind speeds, water temperatures and other factors that decide a hurricane’s path. Having a processor that takes better advantage of data inputs could improve predictions on how subtle climate shifts may increase hurricanes in different geographies.

Krzanich says multiple generations of Nervana products are in the pipeline. Last year, the company set the goal of achieving 100 times greater AI performance by 2020. Intel believes these NNPs will help them achieve this lofty goal.

Nervana, even prior to its acquisition by Intel, has been working on neuromorphic chips for years and even developed its own called ‘Lake Crest’ as it found traditional GPUs to be unsuitable for neural networking. These chips are designed to mimic the human brain to make decisions based on patterns and associations. Intel announced its own ‘Loihi’ chip self-learning neuromorphic chip back in September.

According to Naveen Rao, co-founder of Nervana, the first member of the NNP family will begin shipping “soon”. We’ll keep you informed of all developments.

What are your thoughts on the NNPs being developed by Intel and partners?

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