Quantum // next bubble is coming after AI, Crypto
Despite decades of research, quantum computing still lacks practical use cases, yet hype around it continues to be generated
Quantum computing (QC) is gaining momentum in the market. In a recent survey of 24 senior executives, academics, and start-up executives and founders,1 33 percent said they are developing new QC use cases (as opposed to QC hardware), either for their direct use or for the benefit of third parties. Some of these use cases — such as quantum random-number generators — have already been implemented and have demonstrable outcomes. Other use cases that are still under development typically use QC technology to address problems that classical machines cannot solve efficiently, such as molecular dynamic simulation.
Lol: quantum number generators:) // great use case for billion-dollar QCs
Quantum simulators hold promise, yet they are limited to simulating quantum systems themselves.
Despite this growth in QC, 67 percent of survey respondents did not yet have a use case in production. They pointed to several reasons for this. Some companies specializing in QC hardware are focused on developing and improving the QC hardware itself, rather than creating specific practical uses for it. Other companies found that there were only limited practical applications for QC in their everyday business operations. Most QC use cases focus on solving complex scientific and mathematical problems, including cryptography, optimization, and simulations. For many companies, these applications may not align with their immediate needs or goals. Finally, QC is still an emerging field, and the technology is not yet fully mature.
“Let’s build tech that works like nature.” — for what?
Here is a summary of the key points from the video:
- Scientists and companies are working to develop quantum computers, which operate based on the principles of quantum mechanics at the subatomic level. This has the potential to vastly increase computing power and ability to model and understand the natural world.
- Quantum computers use qubits (quantum bits) that exist in a state of superposition, allowing them to perform many calculations simultaneously, rather than the binary 1s and 0s of classical computers.
- However, engineering quantum computers is extremely challenging as the qubits are extremely fragile and easily disturbed by noise or heat. They must operate at temperatures near absolute zero.
- Major players like IBM, Google, and China are investing heavily in quantum computing research, seeing it as the next technological frontier with applications in fields like energy, climate change, encryption, and more.
- While early quantum computers exist, achieving a large-scale, error-corrected, fault-tolerant quantum computer is still likely a decade away. But the race is on to be the first to fully unlock the potential of this technology.
This document is the introduction to IBM’s report titled “The Quantum Decade: A Playbook for Achieving Awareness, Readiness, and Advantage”. The key points are:
1. Quantum computing is rapidly progressing and will drive a significant computing revolution in this decade, disrupting business models and industries.
2. The power of quantum computing lies in the principles of quantum mechanics — superposition, interference, and entanglement — which allow quantum computers to process information in a fundamentally different way than classical computers.
3. Quantum computing will not replace classical computing, but will extend and complement it by intersecting with classical computing and AI to form a new paradigm — the future of computing.
4. The report outlines three phases organizations should go through — awareness of the changing landscape, readiness by experimenting and building capabilities, and finally achieving quantum advantage when quantum computing provides superior performance over classical methods alone.
5. Preparing for the quantum era requires enhancing classical computing capabilities like data, AI and cloud now, while exploring quantum computing’s potential disruptions and use cases.
6. Attaining quantum advantage will open up new opportunities like discovering new materials, personalized treatments, and transformative business models across industries.
The report urges leaders to start mobilizing resources to understand and get quantum-ready now to avoid being left behind in this upcoming revolution.
The document discusses the rise of quantum computing and how it is driving a new “Quantum Decade” alongside classical computing and AI. The key drivers for this Quantum Decade include:
1. Mounting pressure to solve exponentially complex computational problems faced by business and society, such as discovering new materials, managing financial risk, and re-engineering supply chains.
2. Quantum technology reaching a tipping point, with hardware scaling from 127 qubits in 2021 to over 1,000 qubits in 2023, and IBM outlining a roadmap towards frictionless, scalable quantum computing.
3. Growing quantum ecosystems and communities of developers being trained to apply quantum computing to real-world problems through open innovation platforms like IBM’s Qiskit.
The document explains how the triad of quantum, classical, and AI computing will enable a shift from just analytics towards an age of accelerated discovery and experimentation. Quantum computing allows modeling complex systems more accurately based on quantum physics principles.
It highlights potential quantum use cases like personalized medicine, materials discovery, and solving global challenges. The document also discusses partnerships like between IBM, University of Chicago, and University of Tokyo to develop quantum-centric supercomputers with 100,000+ qubits by 2033 to tackle previously unsolvable problems.
The main points covered in the next part of the paper are:
1. The emerging “discovery-driven enterprise” enabled by the combination of cloud computing, AI, and quantum computing. Quantum computing will open up new possibilities for intelligent, AI-driven workflows and business platforms.
2. The importance of experimenting and iterating with quantum computing now through techniques like:
- The pyramid approach — Using classical methods to generate potential solutions which quantum systems then optimize
- The analyze-and-extract approach — Extracting components solvable by classical vs. quantum
- The benchmarking approach — Benchmarking problems against evolving classical and quantum capabilities
3. Evaluating quantum computing in the context of intelligent workflows that combine technologies like automation, AI, blockchain etc. Quantum can plug into and accelerate portions of these workflows.
4. The benefits of partnering with quantum computing ecosystems, which provide access to technology, talent and expertise that may be difficult to build in-house.
5. The three anticipated waves towards achieving broad quantum advantage:
- Wave 1 (Low tide): Low-key results from research
- Wave 2 (High tide): More structured, commonplace breakthroughs
- Wave 3 (Tsunami): Complex, revolutionary, industry-transforming breakthroughs
6. An overview of potential applications and use cases across different domains like chemistry, physics, logistics etc. where quantum computing may provide advantage.
Overall, it discusses pragmatic steps enterprises can take now to prepare for and integrate quantum computing capabilities when the technology matures.
The document discusses potential applications of quantum computing in the chemicals and petroleum industry. It identifies three main use cases:
1. Developing chemical products like catalysts and surfactants: Quantum computers can perform accurate simulations of molecular structures and chemical reactions, which could accelerate the discovery and development of new chemicals and materials.
2. Optimizing feedstock routing, refining, and product distribution: Similar techniques used for molecular modeling can be repurposed to solve optimization problems in transportation logistics, supply chains, and investment portfolios, potentially improving profit margins.
3. Expanding reservoir production: Using quantum computers to model molecular-scale physics in unconventional oil and gas reservoirs could help explain non-Darcy flow behaviors. This improved understanding could reduce the number of wells needed and increase production efficiency.
The document highlights that quantum computing has the potential to fundamentally disrupt the chemicals and petroleum landscape by providing more accurate simulations, enabling better optimization of complex systems, and advancing the understanding of subsurface reservoir dynamics. While still in early stages, these quantum applications could accelerate product development cycles, optimize operations, and increase profitability for companies in this industry.
This document discusses the potential applications of quantum computing across various industries, including electronics, government, healthcare, insurance, life sciences, and logistics. Here are the key points:
- In the electronics industry, quantum computing could aid in materials development, product design, and smarter manufacturing through improved simulations, optimization, and machine learning.
- For governments, quantum computing may help in emergency preparedness/response, optimizing transport systems, and detecting fraud in social programs through enhanced modeling, optimization, and pattern recognition.
- In healthcare, quantum computing shows promise for diagnostic assistance, insurance pricing, and precision medicine by enabling more accurate classification, risk analysis, and individualized treatment modeling.
- For insurers, quantum computing could improve customer/risk classification, risk concentration analysis, and catastrophe/mortality projection through better optimization, machine learning, and simulation capabilities.
- In life sciences, potential use cases include creating precision therapies by linking genomes and outcomes, enhancing small-molecule drug discovery, and developing novel biological products through improved protein folding predictions.
- For the logistics industry, quantum computing may aid in last mile delivery optimization, disruption management through better simulations, and sustainable maritime routing to reduce costs and emissions.
The document highlights how quantum computing’s enhanced computational power could help tackle extremely complex problems across these domains that are currently intractable using classical computing methods.
Large Language Models (LLMs) such as ChatGPT have transformed how we interact with and understand the capabilities of Artificial Intelligence (AI). However, the intersection of LLMs with the burgeoning field of Quantum Machine Learning (QML) is only in its nascent stages. This paper presents an exploration of this niche by detailing a comprehensive framework for implementing the foundational Transformer architecture — integral to ChatGPT — within a quantum computing paradigm. We meticulously design quantum circuits that implement adapted versions of the transformer’s core components and the generative pretraining phase. By integrating quantum computing with LLMs, we aspire to open new avenues for research in QML and contribute to the ongoing evolution of AI technologies.
