IBM Announces z16 to Deliver AI and Quantum Enabling Safer Levels of Security

IBM Announces z16 to Deliver AI and Quantum Enabling Safer Levels of Security

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On April 5th, 2022, IBM announced the IBM Z system, IBM z16, to deliver AI and quantum enabling safer levels of security; the most significant inclusions to the platform being a dedicated on-chip AI accelerator and the addition of quantum-safe cryptography.

IBM z16 is the latest addition to the IBM mainframe that not only delivers AI and quantum-safe cryptography but also has several unique features that can improve upon traditional security methods.

IBM helped to pioneer the computer and has been a leader in protecting data for decades. The team behind IBM Z continues to push the envelope in terms of innovation, and with every release, they make huge advancements.

The IBM z16 is designed to provide enhanced cybersecurity with innovation that enables specific security capabilities that address a number of industry challenges, including the acceleration of transactions, rapid response to data breaches, and the deployment of AI and quantum applications.

In addition to new features, IBM is also pushing the boundaries in performance. The new z16 is capable of running two extreme speed workloads called analytics and machine learning (ALM) and business-critical throughput (BCT). Both of these workloads are designed to run at a sustained 5.5-7.5 exaops (so 16,000-26,000 quadrillion calculations per second, 1 exaop = 1018 operations per second). Yes, you read that correctly; biochemists will be able to run their algorithms faster than any other system on the market today.

IBM Z continues to be the industry's most secure, most reliable, and highest-performing business-critical system. While you won't find any unicorns inside every IBM Z server, you will find a lot of practical experience, real-world knowledge, and expertise.

With the launch of the z16, IBM is offering a more flexible architecture that consists of three core modular components; Processors, Memory, and I/O. This new modular design not only makes upgrading easier but will also scale workloads into the future.

The ability to process data on the chip, in real-time is an exciting development. The hardware is certainly more advanced today, but the algorithms are equally important. A dedicated accelerator will run neural networks and other deep learning algorithms to detect fraud and present opportunities for banks to tackle emerging challenges such as digital identity protection.

How IBM Is Taking AI to the Mainframe

Many cloud data warehouse and analytics vendors say, "Bring me the data." IBM is flipping the script because IBM Z already houses clients' most critical customer and operational data. In the future, z16 will be shipped with an on-chip integrated accelerator for AI. It's symbolic of how a competitive market should operate — not just one vendor claiming a competitive advantage over another.

IBM z16 will be shipped with an AI accelerator for on-chip inference.

Forty years ago, Big Data was synonymous with big computers. No more. Now that today’s business-critical data is distributed across both mainframes and the cloud, IBM is taking AI to the mainframe.

Let's start with the basics. Big data warehouses and online transaction processing systems are most often deployed using traditional computing architectures. Why does this matter? With more workloads collocated in one physical space, the opportunity for cooling is optimized. Moreover, internal interconnects push latency lower.

One of the main benefits of big data is that it provides us with an opportunity to approach problems in a new and innovative manner. This would include streamlining our processes to make them more streamlined, personalizing our communications and products with our customers, and making better business decisions that take into account things such as the distinctive market conditions in different parts of the world.

One of the main benefits of big data is that it provides us with an opportunity to approach problems in a new and innovative manner. This would include streamlining our processes to make them more streamlined, personalizing our communications and products with our customers, and making better business decisions that take into account things such as the distinctive market conditions in different parts of the world.

Your Software Ecosystem Is Pivotal to Your AI Infrastructure

The z16 hardware and software were designed in tandem with AI libraries, compilers, and frameworks. It supports a wide selection of ML/AI libraries and compilers to enable customers to build and train models in a variety of popular frameworks. These include TensorFlow, SAS, Microsoft Cognitive Toolkit, PyTorch, and Keras, along with others.

While there are certainly advantages to a proprietary stack, with an open ecosystem, developers and data scientists have more choices and flexibility than ever before in developing and deploying AI models. The z16 AI accelerator is one example of how IBM is supporting the open-source community and ecosystem.

The z16 is a system designed to drive insights and actions, which is why it solves the issues that have historically plagued on-premises AI initiatives. What if the hard part wasn't writing the code itself, but rather identifying what you want to do with AI once you've written it? And what if you could use familiar tools like Tensorflow, SAS, Microsoft Cognitive Toolkit (Microsoft CNTK), PyTorch, and Keras or build your own model in Scala, R, or Python/Jupyter and deploy it directly to the z16?

While there are certainly advantages to a proprietary stack, with an open ecosystem, developers and data scientists have more choices and flexibility than ever before in developing and deploying AI models. The z16 AI accelerator is one example of how IBM is supporting the open-source community and ecosystem.

Your software ecosystem is pivotal to your AI infrastructure. Transforming your existing applications and integrating AI models into them are both critical steps on the path to business value. Supporting this approach, the z16 uses a purpose-built Linux operating system and libraries provide deep ML/AI capabilities in an open environment. Because the z16 was designed with servers in mind, clients can use whatever tools they want. This flexibility is also vital to support cross-silo AI collaboration where individuals in marketing or customer service might need to take advantage of deeper insights from their data. The z16 supports a wide range of machine learning (ML) technologies, and it's easy for developers and data scientists to use the ML and artificial intelligence (AI) tools that they know and trust, not those that come pre-loaded on the system.

IBM Z Tech Goes to the Cloud While Mainframe Stays On-Prem

Ideally, an 11-9 durability is advised for cloud-based infrastructures. You may be wondering what difference can a nine make? Five nines mean 99.999% availability while four nines (99.99%) might result in 47 more minutes of downtime per year.

Many-a-times businesses have explored the possibility of transitioning off the mainframe; however, most of them still remain on the mainframe because of resilience, predictability, and security.

The cloud is increasingly being endowed with the services from the IBM mainframe. Recently, IBM announced IBM Z testing in the cloud. Similarly, the Cloud Hyper Protect Crypto Services by IBM offer a key management approach by leveraging a specific security chip module that is enabled by IBM Z technology.

Owing to the latency, security, resilience, governance, and compliance issues, it will take a long time until you migrate or send your mainframe workloads to the cloud. No one right now can expect z17-as-a-service. There are absolutely merger business cases for moving many mainframe workloads to the cloud.

Conclusion

To sum it all up – moving AI closer to data just makes sense.

Quantum-safe security is a growing concern for highly regulated organizations in the banking, insurance, and governmental segments. Over the last several years, financial industry CIOs and CISOs/CSOs at large financial services organizations were focused on establishing a zero-trust approach to security. However, as attacks become more sophisticated, security teams are starting to perform risk assessments on their approach to cryptography. The inclusion of quantum-safe cryptography is important for IBM Z customers.

Many businesses have huge amounts of data, and they do an excellent job retrospectively analyzing that data. However, real-time data-driven decision-making remains a challenge because of latency and the fact that moving data between on-premises and cloud systems raises security and governance risks (in addition to costs).

Quantum computing is closer than it's ever been and we're starting to see actual quantum-safe cryptography gear up. It's unfortunate because SSL – while not perfectly secure – was a workhorse until relatively recently. Quantum computers, theoretically at least, will be able to crack open and read encrypted data at speeds that leave current hardware scrambling to keep up. While we're no sooner ready with a new approach than we are with quantum-resistant cryptography (QRC), there are steps you can take right now to make yourself safer.

About IBM

IBM is one of the world's leading technology companies, with more than 100 research labs worldwide. For more than six decades, IBM Research has defined the future of information technology with more than 3,000 innovations (including the floppy disk, hard drive, and magnetic stripe card) that have helped millions of people around the world solve complex problems. Today, IBMers are on the leading edge of innovation across a spectrum of emerging technologies from nanotechnology to neural networks to embedded systems in cars and medicine.

On April 5th, 2022, IBM announced the IBM Z system, IBM z16, to deliver AI and quantum enabling safer levels of security; the most significant inclusions to the platform being a dedicated on-chip AI accelerator and the addition of quantum-safe cryptography.

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