Cloud and AI strategies are not one-size-fits-all. From client engagements, we understand the journeys to cloud and AI are complex and unique to each organization. Cloud strategies can include many dimensions of cloud consumption, including public and private, shared, dedicated, on premises and off premises. The average enterprise is leveraging multiple clouds. AI adds another layer of complexity as organizations experimenting with AI struggle to find the right infrastructure to run these compute-intensive workloads.

We are in the midst of a global transformation and it is touching every aspect of our world, our lives and our businesses. Many in the industry believe artificial intelligence (AI) is the key to fundamentally changing how organizations will derive insights from data. We know that AI will be a game-changer for our clients, but we also know that there is no "magic bullet" when it comes to AI. For most of our clients, AI will be a journey. This is demonstrated by the fact that most organizations are still in the early phases of AI adoption.

IBM and Hewlett Packard Enterprise this week introduced new servers optimized for artificial intelligence, and the two had one thing in common: Nvidia technology. HPE this week announced Gen10 of its HPE Apollo 6500 platform, running Intel Skylake processors and up to eight Pascal or Volta Nvidia GPUs connected by NVLink, Nvidia's high-speed interconnect. A fully loaded V100s server will get you 66 peak double-precision teraflops of performance, which HPE says is three times the performance of the previous generation. The Apollo 6500 Gen10 platform is aimed at deep-learning workloads and traditional HPC use cases. The NVLink technology is up to 10 times faster than PCI Express Gen 3 interconnects. For its part, IBM held its OpenPOWER Summit in Las Vegas this past week and announced that more than 325 member companies are working on products and services for A.I.-themed workloads in the enterprise.

Have you noticed that interest in artificial intelligence (AI) has really taken off in the last year or so? A lot of that interest is fueled by deep learning. Deep learning has revolutionized the way we use our phones, bringing us new applications such as Google Voice and Apple's Siri, which are based on AI models trained using deep learning. Deep learning is a new machine learning method based on neural networks that learns and becomes more accurate as we feed the model more data. A widely-accepted principle of deep learning is shown on the left-hand side of the chart below: deep learning–based AI models have much higher accuracy than traditional machine learning methods, but require much more data to train to achieve that accuracy.

A translation widget is provided for your convenience to facilitate translation of the English language version of this blog into several languages. If you choose to utilize this automated translation facility, please understand there may be deviations between the automated translation and the original English version. IBM is not responsible for any such automated translation deviations and offers the translated version "AS IS" without warranties of any kind. This is an exciting time for IBM Business Partners and their customers, as IBM unveils its next-generation Power Systems servers incorporating its newly designed POWER9 processor. Built specifically for compute-intensive AI workloads, the new POWER9 systems are capable of improving the training times of deep learning frameworks by nearly 4x,[i] allowing enterprises to build more accurate AI applications, faster.

IBM on Tuesday unveiled a chip that is designed for the new Artificial Intelligence-powered world that requires crunching of humongous amounts of data at high speeds to get the most accurate results. Called POWER9, it uses some of the latest technologies, resulting in two significant advantages: one, increased bandwidth, and two, ability for main processors and accelerators to work coherently and simultaneously on data. Stating that it is a one of its kind in the industry, Dipankar Sarma, distinguished engineer, Linux Technology Center, IBM Systems, said the new chip doubles the bandwidth by which one can get more data really fast. "We significantly increase the ability to process data; five to 10 times faster," he said. He spoke of two applications.

Growing up and playing sports through college, I learned that winning is a team effort. No single player, no matter how spectacular, can carry a team to a championship alone. This analogy resonates as that's what we are now seeing as we embark on the artificial intelligence (AI) era. I believe that the whole is greater than the sum of its parts. This mindset serves particularly well in the "post-CPU-only" era, where chips alone can't deliver a complete solution and the industry can't ever get to zero nanometer silicon.

The latest proprietary Power servers from IBM, armed by the long-awaited IBM Power9 processors, look for relevance among next-generation enterprise workloads, but the company will need some help from its friends to take on its biggest market challenger. IBM emphasizes increased speed and bandwidth with its AC922 Power Systems to better take on high-performance computing tasks, such as building models for AI and machine learning training. The company said it plans to pursue mainstream commercial applications, such as building supply chains and medical diagnostics, but those broader-based opportunities may take longer to materialize. "Most big enterprises are doing research and development on machine learning, with some even deploying such projects in niche areas," said Patrick Moorhead, president and principal analyst at Moor Insights & Strategy. "But it will be 12 to 18 months before enterprises can even start driving serious volume in that space."

HAMPTON, N.H. – IBM (NYSE: IBM) recently unveiled the newest member of the Power Systems family, the POWER9 chip which is uniquely designed for artificial intelligence (AI), deep learning and advanced analytics workloads as the vendor seeks to become the infrastructure foundation provider for the cognitive era. Along with POWER9 came the announcement of the IBM Power System AC922, designed to accompany the increased compute capabilities of POWER9 and touted by IBM as a system likely to become the most powerful supercomputer in the world. A key use case IBM highlighted was that of the CORAL (Collaboration of Oak Ridge, Argonne and Livermore) supercomputer, which the U.S. government uses for massive volumes of AI workloads. To achieve the promises of Power Systems, IBM innovated across its hardware and software stacks to optimize the interworking of the two. The inclusion of NVIDIA graphics processing units (GPUs), second generation NVLink, PCIe 4.0 and OpenCAPI all increase the functionality of AC922 when compared to older solutions. Further, these developmental advancements enable IBM to tout five times more I/O bandwidth when compared to x86 servers, creating an environment ripe with pushback on industry standard servers as IBM seeks to take some of its lost market share back with its AI-centric platform.

There's a big connection between my love for water sports and hardware design -- both involve observing waves and planning several moves ahead. Four years ago, when we started sketching the POWER9 chip from scratch, we saw an upsurge of modern workloads driven by artificial intelligence and massive data sets. We are now ready to ride this new tide of computing with POWER9. It is a transformational architecture and an evolutionary shift from the archaic ways of computing promoted by x86. POWER9 is loaded with industry-leading new technologies designed for AI to thrive.