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IBM's Big Bet On Cloud AI Will Pay Off

This article is more than 6 years old.

Gaining an advantage in the global high-tech market is often the result of research and development (R&D) combined with execution and incremental improvement. Today’s emerging cloud-based artificial intelligence (AI) platforms are a perfect example of R&D-fueled competition. With the cloud giants and many governments investing heavily in AI R&D, what’s a mere multinational corporation to do?

IBM spent the past few years restructuring to address the combination of “cognitive services” (AI-based services) and cloud platforms. During that time, IBM continued to invest in R&D, but focused their efforts on AI software, “as-a-service” initiatives and scale-out systems designed for delivering cloud-based analytics and AI services. As part of this transition, IBM opened its cloud infrastructure development to a much broader community and also partnered with other AI leaders like NVIDIA to provide high-performance AI systems.

In a few weeks, IBM will highlight all its efforts in AI at Think 2018, IBM’s combined partner, customer and developer conference, in Las Vegas. The following is what we expect to see at Think and why IBM should be successful in betting big on AI.

Partnerships for AI Acceleration

NVIDIA’s CEO Jensen Huang will speak at the Think opening keynote “The Journey to AI” on Tuesday morning. IBM partnered with NVIDIA over the past several years to engineer some of the most advanced GPU-accelerated server systems in the industry today. Aspects of NVIDIA NVLink high-speed interconnect technology were designed into IBM’s Coherent Accelerator Processor Interface (CAPI) and then opened to a much broader server ecosystem via the OpenCAPI Consortium.

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IBM has also worked closely with Mellanox Technologies, Micron Technology and Xilinx on network and compute acceleration solutions. In addition, NVIDIA, Mellanox, Micron and Xilinx are all board members of OpenCAPI and Platinum members of the OpenPOWER Foundation. IBM formed the OpenPOWER Foundation to foster a multi-vendor ecosystem around IBM’s POWER architecture. The third OpenPOWER Summit will be collocated with Think this year.

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Partnering increases access to innovation needed to fuel short-term success. Cross-licensing patents with partners contributes to long-term roadmap improvements. At Think, we’ll listen for how partners position themselves with IBM on technology development and product positioning.

Value of Long-Term R&D

IBM inventors have cumulatively received over US 100,000 patents, with 9,043 (about 1% of total) in 2017 alone. In 2017, over 1,900 of these were cloud patents. IBM did not share the number of AI related patents it was granted, but a large part of AI progress today is being made in software and algorithms, which are harder to patent. If quantum computing is included as an AI initiative, then IBM is competitive there, as well.

Patents are important in the context of long-term improvements to business. Across IBM’s business segments, last quarter’s financial results (adjusted for currency) were flat-ish except for the Systems segment, which is all of IBM’s datacenter hardware and operating systems software, and cloud revenue. IBM’s Systems Segment was up 28% on revenue of $3.3 billion and cloud revenue was up 27% on revenue of $5.5 billion. Let that sink in. In the fourth quarter, IBM made a lot more money on cloud services than selling hardware. IBM’s cloud services include Watson AI services and other IBM analytics services.

Also, IBM has implemented “strategic imperatives” of cloud, analytics, mobile and security across the company. Last quarter, IBM’s Technology Services & Cloud Platforms segment saw strategic imperatives grow 15% and Global Business Services saw strategic imperatives grow 9%.

We expect to see a continued focus on AI and cloud at Think, from processors and hardware platforms to software-as-a-service (SaaS).

Quantum Next

IBM is a pioneer in the next generation processor architectures that are likely to take AI to new levels, including quantum computing and neuromorphic computing. There is really no other way to say that. IBM was early in delivering cognitive computing as a service with Watson and as a result, has absorbed some of the early learning pain that most of the AI industry has yet to experience. Likewise, IBM has been investing in quantum computing R&D for two decades.

General-purpose quantum computing will be hard to realize. It still has a long R&D road ahead before deployment and commercialization. However, IBM is cloud-hosting evaluation systems, having simulated 56-qubit quantum computers on classical high-performance computing (HPC) gear and demonstrated a working quantum computer using 50 physical qubits.

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Final Thought

IBM is a significant force across general analytics, HPC and AI, and IBM is investing to remain a technology leader. IBM Think 2018 should give a better glimpse into some of these investments and IBM innovation. Being a leader in AI is a significant accomplishment for a company that is in its second century.

IBM is a significant force across general analytics, HPC and AI, and IBM is investing to remain a technology leader

-- The author and members of the TIRIAS Research staff do not hold equity positions in any of the companies mentioned. TIRIAS Research tracks and consults for companies throughout the electronics ecosystem from semiconductors to systems and sensors to the cloud.

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