IBM power systems and Yamagata University collaborated to develop an AI-enabled cloud platform and geoscope that uncovered mysterious and ancient geoglyphs. Could robots become archaeological assistants, shuffling or trudging across sandy terrain like R2D2 and C3P0 in 1977's original " Star Wars?" Artificial Intelligence (AI) and machine-learning algorithms, along with geospatial data, are being used to uncover mysterious and ancient geoglyphs, courtesy of a collaboration between IBM power systems and Yamagata University. And, using the new AI, scientists discovered a new formation of very large geoglyphs in the soil on the Nazca Lines in southern Peru-- the first to be found using AI. While straight lines dominate the Nazca desert landscape, figurative designs of animals and plants have evolved.

CORAL GABLES, Fla., August 13, 2019 – What if massive data sets could be accessed and analyzed in just an hour, instead of a day? It could change the field of genomics, help researchers predict impacts of climate change more expediently, and help understand the origins of the universe. Today, the University of Miami (UM) announced that their new supercomputer, Triton, is installed and helping their researchers and analysts explore these possibilities. The new high-performance system uses the same AI-optimized architecture as the most powerful supercomputers in the world, the U.S. Department of Energy's Summit and Sierra supercomputers. The $3.7 million system was assembled and validated distally by IBM and the University's Center for Computational Science (CCS) personnel.

Many organizations have started to build infrastructure for AI using IBM Power Systems, which leverage NVIDIA GPUs. Enterprises often focus on building AI solutions that provide high availability, automated orchestration and the like, which can add to the cost of the solution. Educational institutions and research organizations, however, often look for solutions that give them more flexibility in utilizing underlying resources optimally for their machine learning and deep learning (ML/DL) workloads, and with much lower costs. Researchers may require running parallel DL training jobs using different AI runtimes. Professors may require allocating and deallocating AI runtimes to multiple students for AI assignments.

Morgan Stanley was another customer that showcased its work with IBM Power Systems at the event. Morgan Stanley executive director Marcelo Labre speaking with IBM's Sumit Gupta says that IBM Power Systems' computing power and AI-readiness is enabling the organization to explore new AI/ML use cases in finance, with the overall goal of increased efficiency and alignment with customer needs. For example, Morgan Stanley's Labre elaborated at THINK 2019 on how his organization is utilizing AI to challenge outdated risk models. Using AI to improve risk models is a common theme I hear over and over in the industry. You truly need big data to do this well and Power fits the bill.

There is the old saying that "it takes a village," and that couldn't be more true when it comes to building the best solutions for companies on the journey to AI. No one company has all the answers and with new technologies emerging daily, it is important to partner with the right trailblazers. IBM Power Systems is committed to bringing together the best and brightest innovators in both hardware and software. For several years, we have collaborated closely with many companies, like NVIDIA and Mellanox, to develop industry-leading accelerated hardware like the AC922. We also work with software leaders like Hortonworks, MongoDB and EnterpriseDB Postgres to optimize their software for Power Systems servers.

Driverless AI, the automated machine learning platform from H2O.ai, is now available for ordering through IBM . For a more comprehensive description of Driverless AI, see the H2O.ai website. IBM and H2O.ai collaborate to enable you to order Driverless AI directly from IBM. H2O Driverless AI is a high-performance, GPU-enabled software application for the rapid development and deployment of advanced predictive analytics models. It lowers the barrier to entry for machine learning by automating a large portion of the process of algorithm selection and model building and tuning. Driverless AI uses machine learning interpretability to create easy-to-follow visualization and explanations of models, which are especially useful in regulated industries.

Today real-time database company ScyllaDB announced a new Scylla Enterprise release with optimizations for IBM Power System Servers with the IBM POWER9 multi-core architecture. By combining Scylla's highly performant, close-to-the-hardware design with next-generation IBM Power System Servers, organizations can reach new levels of performance while also reducing the footprint, cost and complexity of their systems. ScyllaDB has designed a powerful distributed database that extends the performance advantages we've introduced with our multi-core POWER9 processors," said Tim Vincent, IBM Fellow and Vice President of IBM Cognitive Systems. "The combination of the Scylla NoSQL database and our Power System Servers enables our shared customers to scale up their systems rather than continually scaling out, creating new opportunities for data center consolidation and price performance." This integration builds upon a multi-faceted relationship between ScyllaDB and IBM. In 2016, IBM Compose began providing Scylla as part of their database-as-a-service offering. The collaboration has since grown to include additional IBM divisions, including IBM Systems (both IBM Power Systems and Z Systems), IBM Cloud (including IBM Graph as a service) and IBM's internal use of Scylla to power the IBM Cloud Service Catalog. Scylla is an open source drop-in replacement for Apache Cassandra. It delivers scale-up performance of 1,000,000 IOPS per node, scales out to hundreds of nodes, and consistently achieves a 99% tail latency of less than 1 millisecond. Scylla's pioneering shard-per-core implementation, asynchronous architecture and auto-tuning capabilities enable organizations to immediately leverage the full advantages of the multi-core POWER9 chip. IBM Power Systems servers are designed for mission-critical applications and emerging Cognitive Era workloads including artificial intelligence, machine learning, deep learning, advanced analytics and high-performance computing. Whether deployed in a private, public or hybrid cloud, Power System Servers are capable of performing millions of I/O operations per second. Because Scylla operates asynchronously, it is able to take full advantage of the speed of the POWER9 processor, driving both I/O and CPU processing in a way that scales linearly with the number of cores on the CPU. We are excited by the many advancements IBM has made with its Power System Servers," said Dor Laor, CEO of ScyllaDB.

IBM today made a major announcement about new products and services aimed at helping alleviate the roadblocks to AI (artificial intelligence) adoption in the enterprise. It is only a beginning, but it's very interesting in the breadth and comprehensiveness of IBM's plan. On the infrastructure front, they announced enhancements to the AC922 Server, primarily be improved integration of NVIDIA V100 GPUs and NVLink for faster system communications. This server is for the heavy lifting, training of AI models and processing in HPC (High Performance Computing) systems. They also announced the LC921 and LC922 servers aimed at data intensive applications.

The media coverage of artificial intelligence (AI) would have you believe that most people in the room raised their hands for the first question. But from my (unscientific) count, only 20 people raised their hands for #1, while close to 500 raised their hands for #2. It is obvious that we need to help IT leaders get from here to AI. Which is exactly why we invited thought leaders and technical realists from NVIDIA, Hortonworks, IBM Cognitive Systems and CloudPulse Strategies to cut through the AI hype and give us tips on how to get started. Deep learning could be the easiest place to start.

In 2011, Watson made a dramatic public debut on the Jeopardy! Using IBM Power Systems and analytics software developed with open frameworks like Apache Hadoop and UIMA, Watson showcased a cutting-edge ability to understand complex natural language questions and sift through vast libraries of unstructured human knowledge. And Watson proved to know a thing or two about Beatles songs and Olympic history too. But while the show served as a great platform to introduce amazing new technology to the world, the intelligence behind Watson was designed to solve real business problems. IBM Watson Analytics allows business users to better compete by helping them get more value from their data.