IBM has recently announced that it plans to incorporate the new RAPIDS open source software into its enterprise-grade data science platform for on-premises, hybrid, and multicloud environments. 'IBM has a long collaboration with NVIDIA that has shown demonstrable performance increases leveraging IBM technology, like the IBM POWER9 processor, in combination with NVIDIA GPUs,' said Bob Picciano, senior vice president of IBM Cognitive Systems. 'We look to continue to aggressively push the performance boundaries of AI for our clients as we bring RAPIDS into the IBM portfolio.' RAPIDS will help bring GPU acceleration capabilities to IBM offerings that take advantage of open source machine learning software including Apache Arrow, Pandas and scikit-learn. Immediate, wide ecosystem support for RAPIDS comes from key open-source contributors including Anaconda, BlazingDB, Graphistry, NERSC, PyData, INRIA, and Ursa Labs.

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."

More important to me is how this will change our lives. I spent some time last week talking to IBM about how its partnership with NVIDIA and its advancements with Watson and OpenPOWER will be changing the world around us. We spoke about a number of artificial intelligence trends and several stood out for me. Artificial Intelligence and Credit Card Security Every year, financial institutions write of billions in losses due to credit card fraud, and a great deal of focus has been placed on stopping this steady drip, drip, drip of illegal cost. Currently, systems are advanced enough to do four fraud checks at the time of the transaction, but they simply aren't enough to stop the flood of people cloning, stealing and skimming credit cards to steal money.

On Monday, IBM announced that it collaborated with Nvidia to provide a complete package for customers wanting to jump right into the deep learning market without all the hassles of determining and setting up the perfect combination of hardware and software. The company also revealed that a cloud-based model is available as well that eliminates the need to install local hardware and software. To trace this project, we have to jump back to September when IBM launched a new series of "OpenPower" servers that rely on the company's Power8 processor. The launch was notable because this chip features integrated NVLink technology, a proprietary communications link created by Nvidia that directly connects the central processor to a Nvidia-based graphics processor, namely the Tesla P100 in this case. Server-focused x86 processors provided by Intel and AMD don't have this type of integrated connectivity between the CPU and GPU.

IBM and Nvidia said they are collaborating on a deep learning tool that trains computers faster and scales better. Specifically, IBM launched a software kit dubbed PowerAI that will run on its OpenPOWER LC servers for high performance computing. The Power S822LC for high performance computing (HPC) uses Nvidia NVLink technology to work with IBM's architecture. IBM and Nvidia said that the S822LC system can run AlexNet with Caffe faster than x86 servers with multiple configurations. Caffe is a deep learning framework created by Berkeley Vision and Learning Center (BVLC).