The Future of Computing Belongs to Hybrid Architectures -> Classical + AI Algorithms + Quantum

Per IDC research, the AI server infrastructure will reach $17.6 billion by 2022. Per a ResearchAndMarkets.com report, quantum computing is expected to hit $64.99 billion by 2030.

We are at the cusp of the 5th generation of computing paradigms. We are generating the data everywhere, from smartwatches to self-driving cars. The computing requirements are doubling every 3.5 months.

What does the future of computing look like? Does AI-tuned computing systems replace classical computing systems? Do Quantum Computing systems replace AI systems?

Let me distill these three questions to understand the future of computing.

1. Where does classical computing fit in?

• Web, enterprise business, database management systems, and low sensitivity applications use classical computing.
• Classical Computing is ideal for handling high-volume enterprise workloads. These include transaction processing, large-scale mathematical and logical computation, and persistent data stores.
• Classical Computing is slicon dependent. Through virtualization, they deliver energy efficiency and performance density.

Transistor scaling and energy consumption are the fundamatel limitations of classical computers. -Khwaja Shaik, IBM Thought Leader

• Scale-out infrastructure is not energy efficient. This is due to the saturation of Moore's Law. Advancements in classical computing will plateau due to slower new transistor technology nodes.

The next-generation applications demand new programming models. And new design patterns due to the limitations of Moore's Law. - Khwaja Shaik, IBM Thought Leader

2. Does data-driven AI to need a different type of computing?

As discussed above, Moore's Law is nearing its end by 2025. The computing requirements are doubling every 3.5 months. So, the industry demands new technologies, architectures, and materials for chip design.

• Data is everywhere. The code must follow the data due to the IoT's distributed environment.

With the proliferation of 5G the computing will follow where ever there is data. This drives the distributed programming models. - Khwaja Shaik, IBM Thought Leader

• Neuroscience inspires AI systems. AI systems can surpass human performance on many perception-related cognitive functions associated with human minds, such as perceiving, reasoning, and learning.
• AI systems need vast volumes of labeled data to learn single, specialized tasks. These systems combine biology and information to create neural networks driven AI models. AI models identify patterns by learning from large data sets of examples.
• All AI workloads must be capable of training and inference. AI workloads need high memory-bandwidth and parallel computing. AI software must optimize each specific AI use case.
• Compute requirements for AI workloads vary by Use Case. It is important to choose optimal AI hardware architecture. For example, route-planning applications have unique requirements for processing speed, hardware interfaces. At the same time, applications for autonomous driving have a different need.

We need smart algorithms and optimized hardware that can consume less data. We need systems that consume less power to deploy and scale complex models and networks. - Khwaja Shaik, IBM Thought Leader

• Computing requirements for production AI workloads differ from AI training workloads. It is important to infuse sound architecture governance. These architectures tailor to unique training models and inference models.
• AI workloads demand interoperability, security, accelerator memory, and host CPU performance.

GPUs are cost effective for ML workloads. But, they are experiencing heat limits due to the limitations of Moore's Law. - Khwaja Shaik, IBM Thought Leader

AI systems can find business insights and patterns by deciphering large amounts of data. These systems are of no use in the absence of any such recognizable patterns. This is where quantum computing complements.

3. Where does Quantum Computing fit in?

Quantum bits – or qubits – combine laws of quantum physics with information. Qubits are the basic units of a quantum computer. Classical computing work with 0 and 1; quantum computing has qubits that can represent a 0, a 1, or both at the same time. 

• Quantum Computer is not a general-purpose computer like a classical computer.
• Tailored drugs and predicting the landfall of the hurricane with an exact time is complex. With variables, they have huge amounts of possible outcomes. Quantum Computing Systems support many states.

Classical Computing excels at problems with big data while quantum excels at small data/big compute problems. -Khwaja Shaik, IBM Thought Leader

• Look for use cases that demand simulation of complex data, computing power, memory, cost efficiency, accuracy, and faster results in terms of days instead of months.

If you are a CISO, explore Quantum-safe algorithms as replacements for existing RSA. -Khwaja Shaik, IBM Thought Leader

• Car batteries, modeling bacteria by studying molecules, route optimization for logistics, financial modeling are some of the key use cases for quantum.
• Quantum circuits drive the power of quantum computing.

Quantum needs AI/ML and AI/ML needs Quantum. There is so much potential to leverage from each other. -Khwaja Shaik, IBM Thought Leader

• Quantum uses quantum entanglement to store and process computations.
• Unlike x86, quantum computing is developed by various vendors using different types of hardware technologies-Super conducting, Trapped Ion, Topological, Annealing/Hybrid, Super conducting/spin, and photonic. Super conducting looks very promising. For example, IBM and Google both use super conducting qubits.

 Increase efficiency, minimize costs, eliminate friction, and enhace visibility by tacking supply chain problems using quantum. -Khwaja Shaik, IBM Thought Leader

• Quantum computers can perform many computations simultaneously. Use your imagination for infinite possibilities with a business outcome mindset.
• Make better products at a lower cost in less time with quantum computers.

Quantum Computer is a sweet spot to solve a very narrow complex problems, optimization problems, faster. A classic computer cannot solve this. - Khwaja Shaik, IBM Thoought Leader

• Quantum computers will complement classical computers. Leverage your enterprise architecture to embrace and communicate the value proposition of hybrid architecture.
• In less than 3 years, quantum computers will outperform supercomputers. So it is imperative to put quantum in your technology roadmap. The sweet spot use case lies at the intersection of classical and quantum computing.

Look for use cases that benefit from open hybrid architectures - Classical + AI + Quantum.

Conclusion

Mainframe still powers the world's economy. Applications will be running on open hybrid architectures. This includes heterogeneous computing, quantum computing, accelerated computing, multi-core design, memory-centric computing, and open source frameworks.

Start assessing suitable quantum use cases using your enterprise archictecture team. -Khwaja Shaik, IBM Thought Leader

Quantum algorithms and machine learning are like a marriage made in heaven. With Quantum, you can scale AI through data clustering. Use machine learning to better understand quantum systems. Look for qubit volume, interoperability, and scalability metrics as you evaluate your quantum vendors.

If you are a CIO, the number 1 skill you should invest now is quantum competency to stay ahead of the innovation and talent war. -Khwaja Shaik, IBM Thought Leader

References

• Quantum logic and entanglement: what's next in computing - Dario Gil, Director of IBM Research

Question

What strategic actions are you taking to start experimenting with Quantum? Have you engaged the Enterprise Architecture team to define problems that are fit for quantum to solve? Where are you in aligning your compute strategy with your quantum strategy? Are you playing in the quantum ecosystem with joint ventures and university relationships?

Please share your thoughts in the comments section below.

For professional insights into complex issues, join the conversation by tweeting Khwaja at @Khwaja_Shaik or connecting with him on LinkedIn.

ABOUT KHWAJA SHAIK

Khwaja Shaik is the award-winning global IT Executive with 25+ years of business technology leadership with IBM, Bank of America, PwC, and GE. He has a worldwide reputation and a proven track record in driving digital transformation and the newest innovations.

As IBM’s Thought Leader, Khwaja’s role is to help clients stay ahead of the digital disruption curve by leveraging Design Thinking, Cloud, IoT, Blockchain, Artificial Intelligence, Cybersecurity, and Quantum Computing. Khwaja is among the most exceptional IBMers appointed with the rare distinction of IBM Academy of Technology member. Top 100 technical leaders providing the direction of IBM with innovation that matters.

As a strong proponent of talent development, Khwaja serves as IBM’s Design Thinking Coach for IBM’s Developer Jumpstart Program, IBM’s BlueHack Mentor driving innovation, and IBM’s Blockchain Mentor to spur the blockchain ecosystem.

Khwaja also serves as McKinsey Global Institute’s Executive Panel Member, MIT Sloan CIO Forum Member, Gartner’s Research Circle Member, MarketsANDMarkets Advisor, and HBR’s Advisory Council Member driving global thought leadership.

As a global influencer, Khwaja frequently blogs on exponential technologies at IBM, LinkedIn, and Twitter. With his passion for interfaith and nurturing global talent in STEM, he serves on the Advisory Boards of Interfaith Center of Northeast Florida and Museum of Science & History, and the University of North Florida’s Computing Advisory Board.

Recipient of outstanding service awards from the University of North Florida, Bank of America, IBM, and Indo US Chamber of Commerce of Northeast Florida. He is frequently interviewed for industry insights or cited in the news, Thought Leadership POVs, and blogs on disruptive technologies.

Khwaja holds an MBA and Engineering degree. He is a frequent speaker on exponential technologies at various forums, including the CIO IT & Security Forum, MHI Supply Chain Conference, IIT Hyderabad, and Indo US Chamber of Commerce of Northeast Florida.

More details on Khwaja’s career and thought leadership activities could be found via Linkedin, Khwajashaik.com or follow him on Twitter @Khwaja_Shaik

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